{"kind":"expression","expression":{"expr_id":"244","doc_id":"244","label":"SL 11 of 2012","is_as_enacted":"t","commenced_on":null,"superseded_on":null,"valid_from":null,"valid_to":null,"is_current":"t","incorporating":null,"akn_expr_iri":"\/akn\/ky\/act\/sl\/2012\/11\/eng@2012-01-01","akn_envelope":"{\"_canary\": {\"iri\": {\"work\": \"\/akn\/ky\/act\/sl\/2012\/11\", \"expression\": \"\/akn\/ky\/act\/sl\/2012\/11\/eng@2012-01-01\", \"manifestation\": \"\/akn\/ky\/act\/sl\/2012\/11\/eng@2012-01-01.pdf\"}, \"pdf\": {\"md5\": \"66fbc3e48f8014f95d19e6a94964adc7\", \"path\": \"\/Users\/q\/kyleg-data\/working\/SUBORDINATE\/2012\/2012-0011\/2012-0011_SL 11 of 2012.pdf\", \"pages\": 93, \"filename\": \"2012-0011_SL 11 of 2012.pdf\"}, \"errors\": [], \"extraction\": {\"model\": null, \"stats\": {\"word_count\": 20565, \"paragraph_count\": 8, \"text_char_count\": 135547}, \"usage\": null, \"method\": \"pymupdf-text\", \"version\": \"kyleg-akn-1.0\", \"extracted_at\": \"2026-06-22\"}, \"classification\": \"text_layer\", \"validation_flags\": [], \"docai_processor_id\": null}, \"akomaNtoso\": {\"act\": {\"body\": [{\"eId\": \"sec_n1\", \"num\": null, \"text\": \"Electricity Regulatory Authority Law ELECTRICITY REGULATORY AUTHORITY (STANDARD OF PERFORMANCE) RULES, (SL 11 of 2012) SL 11 of 2012 PUBLISHING DETAILS Arrangement of Rules SL 11 of 2012 Electricity Regulatory Authority Law ELECTRICITY REGULATORY AUTHORITY (STANDARD OF PERFORMANCE) RULES, (SL 11 of 2012) Arrangement of Rules Rule 1. 2. 3. 4. 5. 6.\", \"element\": \"section\", \"heading\": null}, {\"eId\": \"sec_7\", \"num\": \"7.\", \"text\": \"SCHEDULE 1 IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity SCHEDULE 2 IEEE Guide for Electric Power Distribution Reliability Indices Rule 1 SL 11 of 2012 Electricity Regulatory Authority Law ELECTRICITY REGULATORY AUTHORITY (STANDARD OF PERFORMANCE) RULES, (SL 11 of 2012) In exercise of the powers conferred by sections 66 and 89(3) of the Electricity Regulatory Authority Law (2010 Revision), the Authority, after consultation with the Governor and the licensee, makes the following Rules \u2014\", \"element\": \"section\", \"heading\": null}, {\"eId\": \"sec_1\", \"num\": \"1.\", \"text\": \"Citation 1. These Rules may be cited as the Electricity Regulatory Authority (Standard of Performance) Rules, 2012.\", \"element\": \"section\", \"heading\": null}, {\"eId\": \"sec_2\", \"num\": \"2.\", \"text\": \"Definitions 2. In these Rules \u2014 \u201cEAF\u201d means the Equivalent Availability Factor as defined by ANSI\/IEEE Standard 762-1987(R2002) (set out in Schedule 1) which is the fraction of the maximum generation that could be provided if limited only by outages and deratings (per unit or plant basis) and is calculated as available generation divided by maximum generation multiplied by 100% (unit or total plant basis); \u201cIG\u201d means Imperial Gallon, corrected to ISO standard conditions; \u201cInitial Period\u201d  means the period commencing on 1st January, 2011, and terminating on 31st December, 2012; Rule 3 SL 11 of 2012 \u201cNet Fuel Efficiency\u201d means the annual total plant net actual generation divided by the annual total plant fuel consumption for electrical generation during the year; \u201cplanned outage\u201d means the state in which a unit is unavailable due to inspection, testing or overhaul and that outage is scheduled in advance of its occurrence; \u201cPlanned Outage Factor\u201d means planned outage hours divided by the period hours and multiplied by 100% when measured on a per unit basis or the sum of the planned outage hours multiplied by the gross maximum generation per unit for all of the units in the active state and then divided by the gross maximum generation for the plant on a total plant basis; \u201cSAIDI\u201d means the System Average Interruption Duration Index which is the total hours, on average, that a customer could expect to be without electricity over a year, calculated as the sum of the duration of each customer interruption (in hours), divided by the total number of connected customers averaged over the year; \u201cSAIFI\u201d means the System Average Interruption Frequency Index which is the number of occasions per year when each customer could, on average, expect to experience an unplanned interruption, calculated as the total number of customer interruptions, divided by the total number of connected customers averaged over the year and unless otherwise stated, SAIFI excludes momentary interruptions; \u201cService Territory\u201d means the entire area of the island of Grand Cayman; \u201cT&D Licensee\u201d means Caribbean Utilities Company Ltd. as the exclusive holder of the T&D licence for the Service Territory under the Law; \u201cTarget\u201d means the quantity or figure that shall provide the benchmark for Caribbean Utilities Company Ltd.\u2019s performance; \u201cThe Generator\u201d means Caribbean Utilities Company Ltd. as the holder of a generation licence for the Service Territory under the Law; and \u201cZone of Acceptability\u201d means the range above and below the Target that is exempt from any reward or penalty, intended to allow for the normal variation of the performance measures.\", \"element\": \"section\", \"heading\": null}, {\"eId\": \"sec_3\", \"num\": \"3.\", \"text\": \"Initial Period 3. The T&D Licensee shall, during the Initial Period, meet with the Technical Committee of the Authority on a quarterly or semi-annual basis, as requested by the Technical Committee, to discuss its performance during the prior period in all areas related to these standards. Rule 4 SL 11 of 2012\", \"element\": \"section\", \"heading\": null}, {\"eId\": \"sec_4\", \"num\": \"4.\", \"text\": \"Rewards and penalties 4. (1) Rewards and penalties shall be excluded from the calculation of changes to the base rate. (2) The effect of any rewards or penalties recognized in the applicable financial balances of the T&D Licensee shall be removed before calculating Return on Rate Base in determining the RCAM annual base rate adjustment.\", \"element\": \"section\", \"heading\": null}, {\"eId\": \"sec_5\", \"num\": \"5.\", \"text\": \"T&D standards and requirements 5. (1) The T&D Licensee shall, for SAIDI and SAIFI during the Initial Period, adopt its average historical performance over the past ten years, excluding the calendar years 2005 and 2006, as the Targets. (2) The T&D Licensee shall, as it has in the past, measure SAIDI and SAIFI in the future according to the methodology prescribed in the IEEE Standard No. 1366 set out in Schedule 2. (3) The annual Target for SAIDI and SAIFI shall exclude any year substantially affected by an event of force majeure, as defined in the T&D licence and generation licence, for up to two years, unless otherwise approved by the Authority. (4) In paragraph (3), \u2015substantially affected\u2016 means an event which causes SAIDI and SAIFI to vary by more than 10% from the Target figure. (5) The T&D Licensee shall request and receive the Authority\u2019s approval for such exclusions. (6) Using this metric during 2011, the SAIDI shall be 5.5 hours per year, and the SAIFI Target shall be 4.2 interruptions per year. (7) The Zone of Acceptability shall be a range 10% above and below the foregoing Targets, rounded to the nearest tenth, on an annual basis. (8) During 2011, the ranges shall be \u2014 (a) 5.0 to 6.1 hours per year for SAIDI, using the 5.5 hour Target, plus and minus 10%, and (b) 8 to 4.6 interruptions per year for SAIFI, using the 4.2 Target, plus and minus 10%. (9) The increments for potential rewards and penalties shall be tenths of an hour (six minute increments) for SAIDI, and 0.1 interruptions per year for SAIFI, each valued at five thousand dollars per increment, subject to a maximum of one hundred thousand dollars during the Initial Period. (10) There shall be, during the Initial Period, no reward or penalty for better or worse performance outside this range. (11) The T&D Licensee shall report, with monthly detail, its SAIDI and SAIFI performance on or before 15th January, 15th April, 15th July and 15th October Rule 6 SL 11 of 2012 of each year, in conjunction with the quarterly management reports that the T&D Licensee shall provide to the Authority. (12) The reports shall enable the Authority and the T&D Licensee to determine during the year whether performance is likely to be within or outside the Zone of Acceptability for that year and, if it is likely that performance shall be outside the Zone of Acceptability, the Authority and the T&D Licensee shall discuss the reasons for such performance, and if it is expected to be worse than the relevant limit of the Zone of Acceptability, the T&D Licensee shall propose and implement corrective actions, which in its judgment will correct the likely deficiency. (13) The T&D Licensee shall, in January of each year, immediately following the submission of its report to the Authority of its prior year\u2019s performance on SAIDI and SAIFI, file a report with the Authority indicating whether a reward or penalty is due, based on the prior year\u2019s performance. (14) Where a reward or penalty is due, the T&D Licensee shall recommend changes to modify monthly consumer billings to reflect any applicable reward or penalty, using the T&D Licensee\u2019s forecast of sales to spread those amounts evenly over the balance of the year so that the balance of any reward due to or penalty imposed on, the T&D Licensee shall be zero at the end of that year. (15) A recommendation made under paragraph (14) shall be approved by the Authority prior to its implementation and the T&D Licensee shall, upon implementation, establish a tracking account to monitor the balance in this account. (16) Rewards and penalties shall be reflected as a \u2015z factor\u2016 on a consumer\u2019s bill. (17) The T&D Licensee shall, in January, in the report to the Authority on its annual performance for the prior year, provide information to the Authority on the means by which it intends to meet the T&D standards for the coming year. (18) The T&D Licensee shall, within six weeks of the date of commencement of these Rules, provide a recommendation for the Authority\u2019s consideration for a performance standard for T&D losses. (19) The T&D Licensee shall, together with the recommendation, provide the Authority with the data for the performance standard for at least the preceding two years. (20) The T&D Licensee shall include this figure in its quarterly performance reports to the Authority, with monthly detail, and by 1st November of each year, the T&D Licensee shall justify the level of anticipated T&D losses for the coming year, and provide notice of the dates of any planned T&D outages. Rule 6 SL 11 of 2012\", \"element\": \"section\", \"heading\": null}, {\"eId\": \"sec_6\", \"num\": \"6.\", \"text\": \"Customer service standards 6. (1) The T&D Licensee shall measure the customer service standards specified using the following figures specified as indicative Targets \u2014 (a) the time it takes for the T&D Licensee to reconnect customers after an outage - a maximum of twenty-four hours; (b) connection of new accounts - a maximum of seven calendar days; (c) reconnection after shutoff for non-payment, once payment is made - a maximum of twenty-four hours; and (d) response time to billing complaints - a maximum of ten business days. (2) The reconnection standards in paragraphs (a) and (c) shall be measured in terms of hours, and the connection and response time standards in paragraphs \u2014 (b) and (d) shall be measured in parts of days. (3) The T&D Licensee shall collect comprehensive data to document its performance on these measures of customer service during the Initial Period. (4) The Authority shall, upon the compilation and submission of the data to document performance pursuant to paragraph (3), review the performance to determine Target, Zone of Acceptability and the level of reward or penalty for future performance standards. (5) There shall be no rewards or penalties until the Authority has determined the Target, Zone of Acceptability, and an appropriate level of reward or penalty. (6) The T&D Licensee shall, during the Initial Period, provide quarterly reports with monthly detail on the performance for each of the customer service standards. (7) The T&D Licensee shall, within one month of the coming into force of these Rules, provide the Authority with any data that it has in relation to its performance to date of the measures set out in paragraph (1) for the Authority\u2019s consideration in setting performance standards for these measures. (8) The Authority shall, following a review of the performance of the T&D Licensee, set standards, including rewards and penalties, for the measures set out in paragraph (1) and may, in addition, request the T&D Licensee to propose \u2014 (a) Targets, Zones of Acceptability and rewards or penalties for these measures; and (b) additional appropriate performance standards applicable to customer service for the Authority\u2019s consideration and approval. (9) The Authority may provide requests for modification to the T&D Licensee on its most recent customer satisfaction survey for regulatory purposes, and Rule 7 SL 11 of 2012 within four weeks of receiving the requests, the T&D Licensee shall submit an up-to-date customer satisfaction survey to the Authority for approval, which shall be utilized for its 2012 survey. (10) The T&D Licensee shall conduct a customer satisfaction survey and provide a report to the Authority on the results every six months, including actions that the Licensee intends to take to maintain and increase satisfaction with its service and to mitigate dissatisfaction revealed by the survey. (11) The Authority shall, in addition to the determination of the customer service standards, use the customer satisfaction survey to help determine whether the T&D Licensee is taking appropriate actions to provide, maintain and improve upon historical levels of customer service. 7. Generation performance standards and requirements 7. (1) There shall be an annual fuel efficiency standard which shall take into consideration any units that are planned to be added or retired during the year, and if the unit is not added or retired as planned or an event involving a unit occurs that was not planned, The Generator shall notify the Authority as soon as it becomes aware of this change, and shall file with the Authority a revised fuel efficiency standard for the overall generation fleet within fifteen business days of such notification. (2) The Generator\u2019s Net Fuel Efficiency performance target for 2011 shall be set at 18.54 kWh\/IG and The Generator shall \u2014 (a) for 2011, use a range Zone of Acceptability of 18.03 to 19.14 kWh per IG, which is plus-or-minus 3.0% from the 18.58 kWh\/IG target; and (b) report its fuel efficiency performance quarterly, and monthly within fifteen days of each month\u2019s end, with monthly detail on the performance of each generating unit in the fleet. (3) The Authority and The Generator shall use the reports required under paragraph (2)(b) to determine during the year whether performance is expected to be within or outside the Zone of Acceptability for the year. (4) The Generator shall indicate in its quarterly reports whether the annual performance for Net Fuel Efficiency is likely to be outside of the Zone of Acceptability for the year and if any quarterly report indicates that the yearend target will not likely be met, or upon the Authority\u2019s request, the Authority and The Generator shall discuss the reasons for such anticipated performance. (5) Where The Generator is outside of the Zone of Acceptability, The Generator shall propose and implement corrective actions, which in its judgment will correct the likely deficiency, and the Authority and The Generator shall agree upon the nature and timing of the corrective actions. Rule 7 SL 11 of 2012 (6) The T&D Licensee shall, if The Generator\u2019s prior year performance on fuel efficiency as shown in the report submitted pursuant to these Rules is outside of the applicable Zone of Acceptability, implement any necessary changes in consumer billings to reflect any applicable reward or penalty. (7) The T&D Licensee shall, using its forecast of sales figures, determine the amount of any reward or penalty and subject to Authority approval, spread that amount evenly over the balance of the year so that the balance of any reward due to or penalty imposed on the T&D Licensee shall be zero at the end of that year. (8) A penalty shall only apply if The Generator has failed to implement the agreed upon corrective actions. (9) Rewards and penalties shall be reflected as a \u2015z factor\u2016 on a consumers\u2019 bill. (10) The T&D Licensee shall, upon implementation, establish a tracking account to monitor the balance in an account. (11) The Generator shall provide the Authority with a report of the projection of the next year\u2019s expected Net Fuel Efficiency by 15th November of each year. (12) The report required under paragraph (11) shall separate the amount required for station usage from station export. (13) A reward or penalty shall be calculated annually at one thousand dollars for every 0.01 kWh\/IG of total annual Net Plant Fuel Efficiency outside the Zone of Acceptability up to a maximum reward or penalty of one hundred thousand dollars per year during the Initial Period. (14) The EAF Target shall be 81.9 % and the Zone of Acceptability shall be plus or minus 7.5%, or 75.8% to 88.0% in 2011. (15) The EAF Target for 2011 shall be calculated based on the average of the actual annual total plant EAF for the four years ended 31st December, 2007, 2008, 2009 and 2010. (16) The Target for calendar years 2012 and 2013 shall be based on the rolling average of the actual performance for the previous five years, respectively, unless revised by the Authority after the Initial Period. (17) The Generator shall, during the Initial Period, include planned outages in the measure of EAF and in its quarterly reports to the Authority it shall separately provide monthly figures for the elements of the EAF, being planned outages, forced outages and unit seasonal derating outages, as defined by ANSI\/IEEE Standard 762-1987(R2002) set out in Schedule 1. (18) The Generator shall provide the Authority with a projection of its forecasted EAF for the coming year by 15th November of each year and shall divide this projection into the elements of the EAF, being planned outages, forced outages Rule 7 SL 11 of 2012 and unit seasonal derating outages, as defined by ANSI\/IEEE Standard 7621987(R2002), and justify the level of planned outages to the Authority. (19) A penalty or reward amount of five thousand dollars shall be applied for every 0.2% EAF outside the Zone of Acceptability and for the Initial Period, the reward or penalty shall be limited to one hundred thousand dollars and the maximum reward is achieved at 92.0%, or greater, while a maximum penalty will occur at 71.8% or lower being 20 increments of 0.2% outside the Zone of Acceptability. (20) The Authority shall monitor The Generator\u2019s EAF performance during the year and The Generator shall report to the Authority at the end of each quarter on whether it expects that The Generator will be within the Zone of Acceptability for the entire year. (21) The Authority and The Generator shall, if any quarterly report indicates a deficiency in EAF for the year or upon the Authority\u2019s request, discuss the reasons for such anticipated performance and The Generator shall propose and implement corrective actions, which in its judgment will correct the likely deficiency, and the Authority and The Generator shall agree upon the nature and timing of such corrective actions. (22) The Generator shall, when EAF for the prior year is known but no later than the end of January in any year, file a report with the Authority indicating whether any reward or penalty is due to The Generator based on the prior year\u2019s EAF. (23) The T&D Licensee shall, subject to Authority approval, in the event that a reward or penalty applies, using it\u2019s forecast of sales spread the amount of that reward or penalty evenly over the balance of the year, so that the balance of any reward due to or penalty imposed on the T&D Licensee shall be zero at the end of that calendar year. (24) A penalty shall only apply if The Generator has failed to implement the agreed upon corrective actions. (25) Rewards and penalties shall be reflected as a \u2015z factor\u2016 on a consumers\u2019 bill. SCHEDULE 1 SL 11 of 2012 SCHEDULE 1 (Regulations 2 and 7(17)) ANSI\/IEEE Std 762-1987(R2002) (Revision of ANSI\/IEEE Std 762, originally issued for trial use in 1980) IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity Sponsor Power Systems Engineering Committee of the IEEE Power Engineering Society Reaffirmed March 20, 2002 IEEE-SA Standards Board Approved September 19, 1985 IEEE Standards Board Approved August 1, 2002 American National Standards Institute IEEE-SA Standards Board Approved September 19, 1985 Recognized as an American National Standard (ANSI) IEEE Standards documents are developed within the Technical Committees of the IEEE Societies and the Standards Coordinating Committees of the IEEE Standards Board. Members of the committees serve voluntarily and without compensation. They are not necessarily members of the Institute. The standards developed within IEEE represent a consensus of the broad expertise on the subject within the Institute as well as those activities outside of IEEE which have expressed an interest in participating in the development of the standard. Use of an IEEE Standard is wholly voluntary. The existence of an IEEE Standard does not imply that there are no other ways to produce, test, measure, purchase, market, or provide other goods and services related to the scope of the IEEE Standard. Furthermore, the viewpoint expressed at the time a standard is approved and issued is subject to change brought about through developments in the state of the art and comments received from users of the standard. Every IEEE Standard is subjected to review at least once every five years for revision or reaffirmation. When a document is more than five years old, and has not been SCHEDULE 1 SL 11 of 2012 reaffirmed, it is reasonable to conclude that its contents, although still of some value, do not wholly reflect the present state of the art. Users are cautioned to check to determine that they have the latest edition of any IEEE Standard. Comments for revision of IEEE Standards are welcome from any interested party, regardless of membership affiliation with IEEE. Suggestions for changes in documents should be in the form of a proposed change of text, together with appropriate supporting comments. Interpretations: Occasionally questions may arise regarding the meaning of portions of standards as they relate to specific applications. When the need for interpretations is brought to the attention of IEEE, the Institute will initiate action to prepare appropriate responses. Since IEEE Standards represent a consensus of all concerned interests, it is important to ensure that any interpretation has also received the concurrence of a balance of interests. For this reason IEEE and the members of its technical committees are not able to provide an instant response to interpretation requests except in those cases where the matter has previously received formal consideration. Comments on standards and requests for interpretations should be addressed to: Secretary, IEEE Standards Board 345 East 47th Street New York, NY 10017 USA SCHEDULE 1 SL 11 of 2012 Foreword (This Foreword is not a part of ANSI\/IEEE Std 762-1987, IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity.) Measures of generating unit performance have been defined, recorded, and utilized by the electric power industry for over 40 years. Initially, only a few terms, such as forced outage rate and scheduled outage rate, were needed. The increased focus on generating unit performance in recent years has caused regulatory agencies and the industry to place a greater emphasis on performance measures. These contemporary constraints have amplified the difficulties that evolved from having generating unit statistics compiled by different organizations to meet their own specific needs. In the past these difficulties have included the interpretation of data within a given system by an outside agency and the correlation of data among the various systems. The current problems have made clear the need for a standard to overcome these difficulties by providing terminology and indexes for use in existing data systems or in future systems. This standard is directed toward allowing for a meaningful exchange of electric generating unit performance data while attempting to retain as much of existing systems as possible. No attempt is made here to standardize or to recommend methodologies or procedures for the collection of unit performance data. Furthermore, no attempt is made here to address the special requirements of electric generating units limited by fuel supplies, resources such as water (hydro), or environmental restrictions. It is expected that the methods used will continue to vary from system to system according to individual needs. What is attempted is to specify certain common terms and indexes that must be obtainable from each data base to provide for a basis of information exchange. The task force has attempted to keep the list of terms and indexes as brief as possible. Performance cannot be measured by a single parameter, and several indexes are required to indicate the ability of a generating unit to produce power when called upon. The use of any single index to measure the performance of a unit or a class of units is misleading. This requirement has necessitated the inclusion of all of the terms and indexes as given here. SCHEDULE 1 SL 11 of 2012 Some indexes are based on period hours. By use of such a common base, simple additive relationships between various indexes result, and the use of period hours gives sets of indexes that sum to 100%, as described in Appendix C. Other indexes are not based on period hours. For example, in the statistic forced outage rate (see 7.16), (service hours forced outage hours) is used as a base because forced outage rate is intended to estimate the probability of forced outage during the times when there is no planned or maintenance outage. For other than base load service, further modifications are needed to estimate this probability correctly. It is the intent of the task force to define sufficient data categories (states, times, capacity levels) so that suitable indexes for all types of units can be calculated. It should be noted that even the use of all the indexes and terms cannot identify the underlying and sometimes compelling reasons for lost performance. This standard was prepared by the Power Plant Productivity Definitions Task Force of the Applications of Probability Methods Subcommittee of the Power Systems Engineering Committee, whose members were as follows: The following persons were on the balloting committee that approved this document for submission to the IEEE Standards Board: SCHEDULE 1 SL 11 of 2012 When the IEEE Standards Board approved this standard on September 19, 1985, it had the following membership: The task force wishes to dedicate this work to the memory of Veazey M.Cook, a pioneer in the application of generating unit outage data in system planning studies. The format and many of the terms used in this standard can be traced to Veazey Cook's work. SCHEDULE 1 SL 11 of 2012 CLAUSE 1. 2. 3. 3.1 3.2 4. 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 5. 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12 5.13 5.14 5.15 5.16 5.17 5.18 5.19 6. 6.1 6.2 SCHEDULE 1 SL 11 of 2012 6.3 6.4 6.5 6.6 6.7 7. 7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 7.10 7.11 7.12 7.13 7.14 7.15 7.16 7.17 7.18 7.19 7.20 7.21 Annex A Correlation Between Unit State and Capacity Derating Definitions in This Standard and Those Formerly Used by the Industry (Informative).16 Annex C Relationships Between Period-Hour-Based Performance Indexes SCHEDULE 1 SL 11 of 2012 An American National Standard IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity 1. Purpose This standard is intended to aid the electric power industry in reporting and evaluating electric generating unit reliability, availability, and productivity. It was developed to overcome present difficulties in the interpretation of electric generating unit performance data from various systems and to facilitate comparisons among different systems. The standard should also make possible the future exchange o meaningful data among systems in North America and throughout the world. 2. Scope This document standardizes terminology and indexes for reporting electric generating unit reliability, availability, and productivity performance measures. A generating unit includes all equipment up to the high-voltage terminal of the generator step-up transformer. Reliability in this standard encompasses measures of the ability of generating units to perform their intended function. Availability measures are concerned with the fraction of time a unit is capable of providing service, and account for outage frequency and duration. Productivity measures are concerned with the total power produced by a plant with respect to its potential power production. Therefore, productivity measures consider magnitude of outage as well as frequency and duration of outage. NOTE \u2014 This standard was developed for application at the unit level; the definitions are applicable below the unit level in most cases. There are some exceptions, however, such as the definition of in service, which applies only at the unit level. Because of these exceptions, care should be taken when using this standard below the unit level. 3. Unit States A unit state is a particular unit condition that is important for purposes of collecting data on performance. NOTE \u2014 The state definitions are related as shown in Fig 1. The transitions between states are described in Appendix B. The correlation between these definitions and those in use by the industry is shown in Appendix A. 3.1 Active The state in which a unit is in the population of units being reported on. SCHEDULE 1 SL 11 of 2012 NOTE \u2014 A unit generally enters the active state on its service date. 3.1.1 Available The state in which a unit is capable of providing service, whether or not it is actually in service and regardless of the capacity level that can be provided. 3.1.1.1 In Service The state in which a unit is electrically connected to the system. 3.1.1.2 Reserve Shutdown The state in which a unit is available but not in service. NOTE \u2014 This is sometimes referred to as economy shutdown. 3.1.2 Unavailable The state in which a unit is not capable of operation because of operational or equipment failures, external restrictions, testing, work being performed, or some adverse condition. The unavailable state persists until the unit is made available for operation, either by being synchronized to the system (in-service state) or by being placed in the reserve shutdown state. 3.1.2.1 Planned Outage The state in which a unit is unavailable due to inspection, testing, nuclear refueling, or overhaul. A planned outage is scheduled well in advance. 3.1.2.1.1 Basic Planned Outage The planned outage state that is originally scheduled and of a predetermined duration. 3.1.2.1.2 Extended Planned Outage The planned outage state that is the extension of the basic planned outage beyond its predetermined duration. NOTE \u2014 Extended planned outage applies only when planned work exceeds predetermined duration. The extension, due to a condition discovered during the planned outage that has forced the extension of the planned outage, is to be classified as Class 1 unplanned outage (see 3.1.2.2.2). Startup failure would result in Class 0 unplanned outage (see 3.1.2.2.1). SCHEDULE 1 SL 11 of 2012 Figure 1\u2014Relation Between Unit States 3.1.2.2 Unplanned Outage The state in which a unit is unavailable but is not in the planned outage state. NOTES: 1 \u2014 When an unplanned outage is initiated, the outage is to be classified according to one of five classes, as defined in 3.1.2.2.1 through 3.1.2.2.5. Unplanned outage Class 0 applies to a start-up failure and Class 1 applies to a condition requiring immediate outage. Also, unplanned outage starts when planned outage ends but is extended due to unplanned work. Classes 2, 3, and 4 apply to outages where some delay is possible in time of removal of the unit from service. The class (2, 3, or 4) of outage is to be determined by the amount of delay that can be exercised in the time of removal of the unit. The class of outageis not made more urgent if the time of removal is advanced due to favorable conditions of system reserves or availability of replacement capacity for the predicted duration of the outage. However, outage starts when the unit is removed from service or is declared unavailable when it is not in service. 2 \u2014 During the time the unit is in the unplanned outage state, the outage class is determined by the outage class that initiates the state. 3 \u2014 In some cases, the opportunity exists during unplanned outages to perform some of the repairs or maintenance that would have been performed during the next planned outage. If the additional work extends the outage beyond that required for the unplanned outage, the remaining outage should be reported as a planned outage. 4 \u2014 Unlike planned outages, unplanned outages do not have a fixed duration that can be estimated each year. 3.1.2.2.1 Class 0 Unplanned Outage (Starting Failure) An outage that results from the unsuccessful attempt to place the unit in service SCHEDULE 1 SL 11 of 2012 (see 3.1.3.1). 3.1.2.2.2 Class 1 Unplanned Outage (Immediate) An outage that requires immediate removal from the existing state. NOTE \u2014 A Class 1 unplanned outage can be initiated from either the in-service or reserve shutdown states. A Class 1 unplanned outage can also be initiated from the planned outage state. See Note in 3.1.2.1.2. 3.1.2.2.3 Class 2 Unplanned Outage (Delayed) An outage that does not require immediate removal from the in-service state but requires removal within 6 h. 3.1.2.2.4 Class 3 Unplanned Outage (Postponed) An outage that can be postponed beyond 6 h but requires that a unit be removed from the in-service state before the end of the next weekend. NOTE \u2014 Classes 2 and 3 can only be initiated from the inservice state. 3.1.2.2.5 Class 4 Unplanned Outage (Deferred) An outage that will allow a unit outage to be deferred beyond the end of the next weekend but requires that a unit be removed from the available state before the next planned outage. 3.1.2.3 Repair Urgency When a planned or unplanned outage is initiated, the urgency with which repair activities are carried out is classified according to one of three classes as defined in 3.1.2.3.1 through 3.1.2.3.3. 3.1.2.3.1 Maximum Effort Repairs were accomplished in the shortest possible time. 3.1.2.3.2 Normal Effort Repairs were carried out with normal repair crews working normal shifts. 3.1.2.3.3 Low-Priority Effort Repairs were carried out with less than a normal effort. 3.1.3 Starting Attempt The action to bring a unit from shutdown to the in-service state. Repeated SCHEDULE 1 SL 11 of 2012 initiations of the starting sequence without accomplishing corrective repairs are counted as a single attempt. 3.1.3.1 Starting Failure The inability to bring a unit from some unavailable state or reserve shutdown state to the in-service state within a specified period. The specified period may be different for individual units. Repeated failures within the specified starting period are to be counted as a single starting failure. 3.1.3.2 Starting Success The occurrence of bringing a unit from some unavailable state or the reserve shutdown state to the in-service state within a specified period. The specified period may be different for individual units. 3.2 Deactivated Shutdown The state in which a unit is unavailable for service for an extended period of time because of its removal for economy or reasons not related to the equipment. Under this condition, a unit generally requires weeks of preparation to make it available. 4. Capacity Terms Terms that involve capacity can be expressed as gross or net quantities. NOTE \u2014 The capacity definitions are related as shown in Fig 2. The correlation between the capacity-derating definitions in this section and partial-outage definitions in use by industry is shown in Appendix A. SCHEDULE 1 SL 11 of 2012 Figure 2\u2014Unit Capacity Levels 4.1 Maximum Capacity (MC) The maximum capacity that a unit can sustain over a specified period of time. The maximum capacity can be expressed as gross maximum capacity (GMC) or net maximum capacity (NMC). To establish this capacity, formal demonstration is required. The test should be repeated periodically. This demonstrated capacity level shall be corrected to generating conditions for which there should be minimum ambient restriction. When a demonstration test has not been conducted, the estimated maximum capacity of the unit shall be used. 4.2 Dependable Capacity The maximum capacity, modified for ambient limitations for a specified period of time, such as a month or a season. 4.3 Available Capacity The dependable capacity, modified for equipment limitation at any time. 4.4 Seasonal Derating The difference between maximum capacity and dependable capacity. SCHEDULE 1 SL 11 of 2012 4.5 Unit Derating The difference between dependable capacity and available capacity. 4.6 Planned Derating That portion of the unit derating that is scheduled well in advance. 4.6.1 Basic Planned Derating The planned derating that is originally scheduled and of predetermined duration. 4.6.2 Extended Planned Derating The planned derating that is the extension of the basic planned derating beyond its predetermined duration. 4.7 Unplanned Derating That portion of the unit derating that is not a planned derating. Unplanned derating events are classified according to the urgency with which the derating needs to be initiated, as defined in 4.7.1 through 4.7.4. 4.7.1 Unplanned Derating, Class 1 (Immediate) A derating that requires an immediate action for the reduction of capacity. 4.7.2 Unplanned Derating, Class 2 (Delayed) A derating that does not require an immediate reduction of capacity, but requires a reduction of capacity within 6 h. 4.7.3 Unplanned Derating, Class 3 (Postponed) A derating that can be postponed beyond 6 h, but requires a reduction of capacity before the end of the next weekend. 4.7.4 Unplanned Derating, Class 4 (Deferred) A derating that can be deferred beyond the end of the next weekend, but requires a reduction of capacity before the next planned outage. 4.8 Installed Nameplate Capacity The full-load continuous gross capacity of a unit under specified conditions, as calculated from the electric generator nameplate based on the rated power factor. NOTE \u2014 The nameplate rating of the electric generator may not be indicative of the unit maximum or dependable capacity, since some other item or equipment (such as the turbine) may limit unit output. SCHEDULE 1 SL 11 of 2012 5. Time Designations and Dates NOTE \u2014 The time spent in the various unit states defined in Section 3 is defined in 5.1 through 5.10. See Fig 3. In 5.11 through 5.16, the time a unit was subject to the various categories of unit derating defined in Section 4. is defined. Derated time is accumulated only during the available, inservice, and reserve shutdown states. Figure 3\u2014Time Spent in Various Unit States 5.1 Available Hours (AH) The number of hours a unit was in the available state. NOTE \u2014 Available hours is the sum of service hours and reserve shutdown hours, or may be computed from period hours minus unavailable hours (see 5.4). 5.2 Service Hours (SH) The number of hours a unit was in the in-service state. 5.3 Reserve Shutdown Hours (RSH) The number of hours a unit was in the reserve shutdown state. 5.4 Unavailable Hours (UH) The number of hours a unit was in the unavailable state. NOTE \u2014 Unavailable hours are the sum of planned outage hours and unplanned outage hours, or the sum of planned outage hours, forced outage hours, and maintenance outage hours. 5.5 Planned Outage Hours (POH) The number of hours a unit was in the basic or extended planned outage state. 5.6 Unplanned Outage Hours (UOH) The number of hours a unit was in a Class 0, 1, 2, 3, or 4 unplanned outage state. SCHEDULE 1 SL 11 of 2012 5.7 Forced Outage Hours (FOH) The number of hours a unit was in a Class 0, 1, 2, or 3 unplanned outage state. 5.8 Maintenance Outage Hours (MOH) The number of hours a unit was in a Class 4 unplanned outage state. 5.9 Deactivated Shutdown Hours (DSH) The number of hours a unit was in the deactivated shutdown state. 5.10 Period Hours (PH) The number of hours a unit was in the active state. 5.11 Unit Derated Hours (UNDH) The available hours during which a unit derating was in effect. 5.11.1 In-Service Unit Derated Hours (IUNDH) The in-service hours during which a unit derating was in effect. 5.11.2 Reserve Shutdown Unit Derated Hours (RSUNDH) The reserve shutdown hours during which a unit derating was in effect. 5.12 Planned Derated Hours (PDH) The available hours during which a basic or extended planned derating was in effect. 5.12.1 In Service PlAnned Derated Hours (IPDH) The in-service hours during which a basic or extended planned derating was in effect. 5.12.2 Reserve Shutdown Planned Derated Hours (RSPDH) The reserve shutdown hours during which a basic or extended planned derating was in effect. 5.13 Unplanned Derated Hours (UDH) The available hours during which an unplanned derating was in effect. 5.13.1 In-Service Unplanned Derated Hours (IUDH) The in-service hours during which an unplanned derating was in effect. SCHEDULE 1 SL 11 of 2012 5.13.2 Reserve Shutdown Unplanned Derated Hours (RSUDH) The reserve shutdown hours during which an unplanned derating was in effect. 5.14 Forced Derated Hours (FDH) The available hours during which a Class 1, 2, or 3 unplanned derating was in effect. 5.14.1 In-Service Forced Derated Hours (IFDH) The in-service hours during which a Class 1, 2, or 3 unplanned derating was in effect. 5.14.2 Reserve Shutdown Forced Derated Hours (RSFDH) The reserve shutdown hours during which a Class 1, 2, or 3 unplanned derating was in effect. 5.15 Maintenance Derated Hours (MDH) The available hours during which a Class 4 unplanned derating was in effect. 5.15.1 In-Service Maintenance Derated Hours (IMDH) The in-service hours during which a Class 4 unplanned derating was in effect. 5.15.2 Reserve Shutdown Maintenance Derated Hours (RSMDH) The reserve shutdown hours during which a Class 4 unplanned derating was in effect. 5.16 Seasonal Derated Hours (SDH) The available hours during which a seasonal derating was in effect. 5.17 Equivalent Hours (E) The number of hours a unit was in a time category involving unit derating, expressed as equivalent hours of full outage at maximum capacity. Both unit derating and maximum capacity shall be expressed on a consistent basis, gross or net. Equivalent hours can be calculated for each of the time categories in 5.11through 5.16. The symbol designation for the equivalent hours is formed by adding an E in front of the symbol for the corresponding time designation (for example, equivalent unit derated hours is designated EUNDH). Equivalent hours can be calculated from the following equation: SCHEDULE 1 SL 11 of 2012 where E( ) = equivalent hours in the time category represented by parentheses, which can be any one of the time categories in 5.11 through 5.16 D( )i = the derating for the time category shown in parentheses, after the ith change in either available capacity (unit deratings) or dependable capacity (seasonal deratings) NOTE \u2014 In order to apportion equivalent hours among the various time categories, appropriate ground rules shall be established in the reporting system so that after each change in either available capacity or dependable capacity, the sum of all subcategories of unit derating is equal to the unit derating. Ti = the number of hours accumulated in the time category of interest between the ith and the (i + 1)th change in either available capacity (unit deratings) or dependable capacity (seasonal deratings) MC = maximum capacity 5.18 Deactivation Date The date a unit was placed into the deactivated shutdown state. 5.19 Reactivation Date The date a unit was returned to the active state from the deactivated shutdown state. 6. Energy Terms Similar to capacity terms, energy terms can be expressed as gross or net quantities. 6.1 Actual Generation (AAG) The energy that was generated by a unit in a given period. Actual generation can be expressed as gross actual generation (GAAG) or net actual generation (NAAG). 6.2 Maximum Generation (MG) The energy that could have been produced by a unit in a given period of time if operated continuously at maximum capacity. Maximum generation can be expressed as gross maximum generation (GMG) or net maximum generation (NMG). SCHEDULE 1 SL 11 of 2012 MG = period hours \u00b7 maximum capacity = PH \u00b7 MC GMG = PH \u00b7 GMC NMG = PH \u00b7 NMC 6.3 Available Generation (AG) The energy that could have been generated by a unit in a given period if operated continuously at its available capacity. 6.4 Unavailable Generation (UG) The difference between the energy that would have been generated if operating continuously at dependable capacity and the energy that would have been generated if operating continuously at available capacity. This is the energy that could not be generated by a unit due to planned and unplanned outages and unit deratings. UG = (planned outage hours + unplanned outage hours + equivalent unit derated hours) \u00b7 maximum capacity = (POH + UOH + EUNDH) \u00b7 MC 6.5 Seasonal Unavailable Generation (SUG) The difference between the energy that would have been generated if operating continuously at maximum capacity and the energy that would have been generated if operating continuously at dependable capacity, calculated only during the time the unit was in the available state. SUG = equivalent seasonal derated hours \u00b7 maximum capacity = ESDH \u00b7 MC 6.6 Reserve Generation (RG) The energy that a unit could have produced in a given period but did not, because it was not required by the system. This is the difference between available generation and actual generation. 6.7 Derated Generation (DG) The generation that was not available due to unit deratings. DG = equivalent unit derated hours \u00b7 maximum capacity = EUNDH \u00b7 MC 7. Performance Indexes Appendix C discusses the relationships among the performance indexes that are based on period hours. NOTE \u2014 All per unit performance indexes are expressed in percentage. SCHEDULE 1 SL 11 of 2012 7.1 Planned Outage Factor (POF) 7.2 Unplanned Outage Factor (UOF) 7.3 Forced Outage Factor (FOF) 7.4 Maintenance Outage Factor (MOF) 7.5 Unavailability Factor (UF) 7.6 Availability Factor (AF) 7.7 Service Factor (SF) 7.8 Seasonal Derating Factor (SDF) The fraction of maximum generation that could not be produced due to seasonal deratings: SCHEDULE 1 SL 11 of 2012 7.9 Unit Derating Factor (UDF) The fraction of maximum generation that could not be produced due to unit deratings: 7.10 Equivalent Unavailability Factor (EUF) The fraction of maximum generation that could not be produced due to unit deratings and planned and unplanned outages: 7.11 Equivalent Availability Factor (EAF) The fraction of maximum generation that could be provided if limited only by outages and deratings: 7.12 Gross Capacity Factor (GCF) 7.13 Net Capacity Factor (NCF) SCHEDULE 1 SL 11 of 2012 NOTE \u2014 Net capacity factor calculated using this equation can be negative during a period when the unit is shutdown. For meaningful pooling of data on several units, net capacity factor can be defined to be zero when the unit is shutdown. 7.14 Gross Output Factor (GOF) 7.15 Net Output Factor (NOF) 7.16 Forced Outage Rate (FOR) 7.17 Equivalent Forced Outage Rate (EFOR) 7.18 Mean Service Time to Outage 7.18.1 Mean Service Time to Forced Outage (MSTFO) 7.18.2 Mean Service Time to Maintenance Outage (MSTMO) 7.18.3 Mean Service Time to Planned Outage (MSTPO) NOTE \u2014 In 7.18.1, only forced outages occurring from in-service state are considered. The  name for  the  index  could  be  \u2015mean  service  time  to  in-service  forced  outage.\u2016 However, for simplicity in-service is not included in the name. This note is also applicable to 7.18.2 and 7.18.3. Indexes similar to 7.18.1, 7.18.2, and 7.18.3 can also be calculated for outages that occur during reserve shutdown state. SCHEDULE 1 SL 11 of 2012 7.19 Mean Outage Duration 7.19.1 Mean Forced Outage Duration (MFOD) 7.19.2 Mean Maintenance Outage Duration (MMOD) 7.19.3 Mean Planned Outage Duration (MPOD) NOTE \u2014 Similar to 7.18, outage hours and number of outages in 7.19 include outages  that occur from in-service state only. 7.20 Starting Reliability (SR) 7.21 Cycling Rate (CR) Annex A Correlation Between Unit State and Capacity Derating Definitions in This Standard and Those Formerly Used by the Industry (Informative) (These Appendixes are not a part of ANSI\/IEEE Std 762-1987, EEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity.) SCHEDULE 1 SL 11 of 2012 Annex B Transitions Between States (Informative) Section 3 defines three primary unit states: 1) Available 2) Unavailable 3) Deactivated shutdown These three states are mutually exclusive and exhaustive. A unit will be in exactly one of these states at all times. Thus, these states divide calendar time into nonoverlapping segments. The available and unavailable states are each divided into additional, mutually exclusive states. The available state is divided SCHEDULE 1 SL 11 of 2012 into in- service and reserve shutdown states, and the unavailable state is divided into planned and unplanned outage states. These four secondary states, together with the deactivated shutdown state, also form a mutually exclusive and exhaustive set. Finally, the planned outage state is divided into basic and extended planned outage states. Also, the unplanned outage state is divided into five outage classes, according to the urgency with which the outage is initiated. Like the other states, the unplanned outage classes are defined to be mutually exclusive. The unit state structure can also be described by starting with the lowest level states. Thus, there are ten basic states: 1) In service 2) Reserve shutdown 3) Basic planned outage 4) Extended planned outage 5) Class 0 unplanned outage 6) Class 1 unplanned outage 7) Class 2 unplanned outage 8) Class 3 unplanned outage 9) Class 4 unplanned outage 10) Deactivated shutdown These basic states are defined to be mutually exclusive and exhaustive. By grouping various subsets of the basic states together, each of the secondary and primary states can be formed. Once a unit is in a state, it remains in that state until a transition event occurs that causes the unit to move to another state. The possible transition events can be shown by use of a state transition matrix. Figure B.1 shows a state transition matrix for the ten basic states. The left side of the matrix shows the possible unit states before a transition event. The top row of the matrix shows the (same) possible unit states after a transition event. Thus, each (nondiagonal) element of the matrix can be used to describe a transition event from the state on the left to the top state. Figure B.1 shows the transition events that are possible according to the definitions in Section 3. The elements denoted by \\\"x\\\" are not possible. By looking on a particular row of Fig B.1, the possible transition events that can terminate a state can be seen. By looking at a particular column of Fig the possible transition events that can initiate a state can be seen. Detailed definitions for the transition events in Fig have not been included in this SCHEDULE 1 SL 11 of 2012 standard. However, in actual reporting generating unit performance, it is the transition event occurrence times that are in fact reported, from which the state duration times are then calculated. Therefore, the reporting instructions that implement the collection of unit performance data should give careful consideration to defining precisely and clearly the exact point in time at which the various transitions take place. Figure B.1\u2014State Transition Matrix Annex C Relationships Between Period-Hour-Based Performance Indexes (Informative) For purposes of measuring and improving the performance of individual generating units, it is common to emphasize measures that are based on period hours. The performance indexes in Section 7 provide a unified set of period- hourbased indexes (called factors), as follows: AF = availability factor UF = unavailability factor EAF = equivalent availability factor EUF = equivalent unavailability factor FOF = forced outage factor MOF = maintenance outage factor UOF = unplanned outage factor = FOF + MOF SCHEDULE 1 SL 11 of 2012 POF = planned outage factor SDF = seasonal derating factor UDF = unit derating factor These indexes are unified in the sense that they are related in the following ways: Equation C1 shows that equivalent availability can be obtained by subtracting the unit derating factor and the seasonal derating factor from the availability factor. Equation C2 shows that equivalent unavailability can be obtained by adding the unit derating factor, but not the seasonal derating factor, to the unavailability factor. Equation C3 shows that the availability and unavailability factors add to 100%. Equation C4 shows that the equivalent availability, equivalent unavailability, and seasonal derating factor also add to 100%. However, equivalent availability and equivalent unavailability alone do not, in general, add to 100%, because this sum does not include the effect of seasonal deratings. Equation C5 shows that the unavailability factor is the sum of the planned and unplanned outage factors (unplanned outage factor is the sum of maintenance outage factor and forced outage factor). SCHEDULE 1 SL 11 of 2012 Substituting Eq C5 into Eq C2 produces Eq C6, which shows that equivalent unavailability is the sum of the planned and unplanned outage factors and the unit derating factor. Substituting Eq C6 into Eq C4 produces Eq C7. This last equation shows that there are four recognized sources of energy loss: planned outages (full), unplanned outages (full), unit deratings, and seasonal deratings. Each energy loss is represented by a separate index: POF, UOF, UDF, and SDF, respectively. These indexes are defined in such a way as to be additive. Therefore, the total per unit energy loss is the sum of the four indexes, and the remaining per unit energy not lost is called equivalent availability factor (EAF). In order for the four energy loss indexes to be additive, as in Eq C7, it is necessary that the capacity loss due to each source be separated. This means, for example, that a unit cannot simultaneously be subject to full outage and unit derating. Similarly, a unit cannot simultaneously be subject to both seasonal derating and full outage. In order to achieve nonoverlapping energy definitions, the task force agreed to assign full (maximum) unit capacity to the full outage state. This means that both unit deratings and seasonal deratings are considered to end when a full outage starts, as far as the calculation of the unit derating factor (UDF) and the seasonal derating factor (SDF) are concerned. In order to further illustrate the relationship between the period-hour-based performance indexes, Fig C1 shows capacity versus time diagram (all capacity values must be either gross or net). The total height of the diagram is maximum capacity (MC), and the total width of the diagram is period hours (PH). Thus, the total area Y of the diagram is Y = MC \u00b7 PH This is the total megawatthour (MWh) of energy that could have been generated during the period if operating continuously at MC. The area Y is divided into several vertical segments by the various time SCHEDULE 1 SL 11 of 2012 designations in Section 5. The vertical segments involving available hours are further divided into sections to show the energy associated with seasonal derating, unit derating, discretionary reduction, and actual generation. All of the performance factors in Section 7 that are based on period hours can be expressed as simple ratios of the areas in Fig C.1 as follows: Figure C.1\u2014Relation Between Time and Energy Terms Time Indexes SCHEDULE 1 SL 11 of 2012 Energy Indexes NOTE \u2014 Capacity factor is GCF or NCF depending on gross or net basis used for capacity. SCHEDULE 1 SL 11 of 2012 Annex D Glossary of Terms and Abbreviations (Informative) SCHEDULE 1 SL 11 of 2012 SCHEDULE 2 SL 11 of 2012 SCHEDULE 2 (Regulation 5(2)) 1366TM IEEE Guide for Electric Power Distribution Reliability Indices IEEE Power Engineering Society Sponsored by the Transmission and Distribution Committee IEEE Guide for Electric Power Distribution Reliability Indices Sponsor Transmission and Distribution Committee of the IEEE Power Engineering Society Approved 26 April 2004 American National Standards Institute Approved 10 December 2003 IEEE-SA Standards Board Grateful acknowledgment is made to the Edison Electric Institute for the permission to use the following source material: Pages 28\u201330 of the June 2001, Edison Electric Institute 2000 Reliability Report. Abstract: Distribution reliability indices and factors that affect their calculations are defined in this guide. The indices are intended to apply to distribution systems, substations, circuits, and defined regions. Keywords: circuits, distribution reliability indices, distribution systems, electric power, reliability indices SCHEDULE 2 SL 11 of 2012 Introduction (This introduction is not part of IEEE Std 1366-2003, IEEE Guide for Electric Power Distribution Reliability Indices.) This Guide has been updated to clarify existing definitions and to introduce a statistically based definition for classification of major event days. The working group created a methodology, 2.5 Beta Method, for determination of major event days. Once days are classified as normal or major event days, appropriate analysis and reporting can be conducted. After this document is balloted, the working group will continue to investigate the major event definition by reviewing catastrophic events and days with zero events to determine if enhancements are warranted. Patents Attention is called to the possibility that implementation of this standard may require use of subject matter covered by patent rights. By publication of this standard, no position is taken with respect to the existence or validity of any patent rights in connection therewith. The IEEE shall not be responsible for identifying patents for which license may be required by an IEEE standard or for conducting inquiries into the legal validity or scope of those patents that are brought to its attention. Notice to users Errata Errata, if any, for this and all other standards can be accessed at the following URL: http:\/\/standards.ieee.org\/reading\/ieee\/updates\/errata\/index.html. Users are encouraged to check this URL for errata periodically. Interpretations Current interpretations can be accessed at the following URL: http:\/\/standards.ieee.org\/reading\/ieee\/interp\/index.html. Participants At the time this standard was completed, the Working Group on System Design had the following membership: SCHEDULE 2 SL 11 of 2012 The following members of the balloting committee voted on this standard. Balloters may have voted for approval, disapproval, or abstention. SCHEDULE 2 SL 11 of 2012 When the IEEE-SA Standards Board approved this standard on 10 December 2003, it had the following membership: SCHEDULE 2 SL 11 of 2012 CONTENTS 1.1 Scope. 1.2 Purpose. 1 6. Information about the factors which affect the calculation of reliability indices 17 Annex A (informative) Survey of reliability index usage 18 Annex B (informative) Major events definition development. 27 Annex C (informative) Internal data subset. Annex D (informative) Bibliography 36 SCHEDULE 2 SL 11 of 2012 IEEE Guide for Electric Power Distribution Reliability Indices 1. Overview 1.1 Scope This guide identifies distribution reliability indices and factors that affect their calculation. It includes indices, which are useful today, as well as ones that may be useful in the future. The indices are intended to apply to distribution systems, substations, circuits, and defined regions. 1.2 Purpose The purpose of this guide is twofold. First, it is to present a set of terms and definitions which can be used to foster uniformity in the development of distribution service reliability indices, to identify factors which affect the indices, and to aid in consistent reporting practices among utilities. Secondly, it is to provide guidance for new personnel in the reliability area and to provide tools for internal as well as external comparisons. In the past, other groups have defined reliability indices for transmission, generation, and distribution but some of the definitions already in use are not specific enough to be wholly adopted for distribution. Users of this guide should recognize that not all utilities would have the data available to calculate all the indices. 2. References The following standards shall be used, when applicable, in preparing manuscripts. When the following standard is superseded by an approved revision, the revision shall apply. IEEE Std. 859\u2122-1987(R2002), IEEE Standard Terms for Reporting and Analyzing Outage Occurrences and Outage States of Electrical Transmission Facilities.1, 2 IEEE Std 493\u2122-1997(R2002), Recommended Practice for Design of Reliable Industrial and Commercial Power Systems. 1IEEE Publications are available from the Institute of Electrical and Electronics Engineers, 445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 088551331, USA (http:\/\/standards.ieee.org\/). 2The IEEE standards or products referred to in this clause are trademarks of the Institute of Electrical and Electronics Engineers, Inc. SCHEDULE 2 SL 11 of 2012 3. Definitions Definitions are given here to aid the user in understanding the factors that affect index calculation. Many of these definitions were taken directly from The Authoritative Dictionary of IEEE Standards Terms, 7th Edition [B9]3. If there is a conflict between the definitions in this document and the dictionary, the definitions in this document take precedence. Others are given because they have a new interpretation within this document or have not been previously defined. 3.1 connected load: Connected transformer kVA, peak load, or metered demand (to be clearly specified when reporting) on the circuit or portion of circuit that is interrupted. When reporting, the report should state whether it is based on an annual peak or on a reporting period peak. 3.2 customer: A metered electrical service point for which an active bill account is established at a specific location (e.g., premise). 3.3 customer count: The number of customers either served or interrupted depending on usage. 3.4 distribution system: That portion of an electric system that delivers electric energy from transformation points on the transmission system to the customer. NOTE\u2014The distribution system is generally considered to be anything from the distribution substation fence to the customer meter. Often the initial overcurrent protection and voltage regulators are within the substation fence and are considered to be part of the distribution system. 3.5 forced outage: The state of a component when it is not available to perform its intended function due to an unplanned event directly associated with that component. 3.6 interrupting device: An interrupting device is a device whose purpose is to interrupt the flow of power, usually in response to a fault. Restoration of service or disconnection of loads can be accomplished by manual, automatic, or motor- operated methods. Examples include transmission circuit breakers, feeder circuit breakers, line reclosers, line fuses, sectionalizers, motor-operated switches or others. 3.7 interruption: The loss of service to one or more customers connected to the distribution portion of the system. It is the result of one or more component outages, depending on system configuration. See also: outage. 3 The numbers in brackets correspond to those of the bibliography in Annex D. SCHEDULE 2 SL 11 of 2012 3.8 interruption duration: The time period from the initiation of an interruption to a customer until service has been restored to that customer. The process of restoration may require restoring service to small sections of the system (see 5.3.2) until service has been restored to all customers. Each of these individual steps should be tracked collecting the start time, end time and number of customers interrupted for each step. 3.9 interruptions caused by events outside of the distribution system: Outages that occur on generation, transmission, substations, or customer facilities that result in the interruption of service to one or more customers. While generally a small portion of the number of interruption events, these interruptions can affect a large number of customers and last for an exceedingly long duration. 3.10 lockout: Refers to the final operation of a recloser or circuit breaker in an attempt to isolate a persistent fault, or to the state where all automatic reclosing has stopped. The current-carrying contacts of the overcurrent protecting device are locked open under these conditions. 3.11 loss of service: A complete loss of voltage on at least one normally energized conductor to one or more customers. This does not include any of the power quality issues such as: sags, swells, impulses, or harmonics. 3.12 major event: Designates an event that exceeds reasonable design and or operational limits of the electric power system. A Major Event includes at least one Major Event Day (MED). 3.13 major event day: A day in which the daily system SAIDI exceeds a threshold value, TMED. For the purposes of calculating daily system SAIDI, any interruption that spans multiple calendar days is accrued to the day on which the interruption began. Statistically, days having a daily system SAIDI greater than TMED are days on which the energy delivery system experienced stresses beyond that normally expected (such as severe weather). Activities that occur on major event days should be separately analyzed and reported. (See 4.5.) 3.14 momentary interruption: A single operation of an interrupting device that results in a voltage zero. For example, two circuit breaker or recloser operations (each operation being an open followed by a close) that momentarily interrupts service to one or more customers is defined as two momentary interruptions. 3.15 momentary interruption event: An interruption of duration limited to the period required to restore service by an interrupting device. SCHEDULE 2 SL 11 of 2012 NOTE\u2014Such switching operations must be completed within a specified time of 5 min or less. This definition includes all reclosing operations that occur within five minutes of the first interruption. For example, if a recloser or circuit breaker operates two, three, or four times and then holds (within 5 min of the first operation), those momentary interruptions shall be considered one momentary interruption event. 3.16 outage (electric power systems): The state of a component when it is not available to perform its intended function due to some event directly associated with that component. NOTES: (1) An outage may or may not cause an interruption of service to customers, depending on system configuration. (2) This definition derives from transmission and distribution applications and does not apply to generation outages. 3.17 planned interruption: A loss of electric power that results when a component is deliberately taken out of service at a selected time, usually for the purposes of construction, preventative maintenance, or repair. NOTES: (1) This derives from transmission and distribution applications and does not apply to generation interruptions. (2) The key test to determine if an interruption should be classified as a planned or unplanned interruption is as follows: if it is possible to defer the interruption, the interruption is a planned interruption; otherwise, the interruption is an unplanned interruption. 3.18 planned outage: The state of a component when it is not available to perform its intended function due to a planned event directly associated with that component. 3.19 reporting period: The time period from which interruption data is to be included in reliability index calculations. The beginning and end dates and times should be clearly indicated. All events that begin within the indicated time period should be included. A consistent reporting period should be used when comparing the performance of different distribution systems (typically one calendar year) or when comparing the performance of a single distribution system over an extended period of time. The reporting period is assumed to be one year unless otherwise stated. SCHEDULE 2 SL 11 of 2012 3.20 step restoration: A process of restoring interrupted customers downstream from the interrupting device\/component in stages over time. 3.21 sustained interruption: Any interruption not classified as a part of a momentary event. That is, any interruption that lasts more than 5 minutes. 3.22 total number of customers served: The average number of customers served during the reporting period. If a different customer total is used, it must be clearly defined within the report. 3.23 unplanned interruption: An interruption caused by an unplanned outage. 4. Reliability indices 4.1 Basic factors These basic factors specify the data needed to calculate the indices. i denotes an interruption event ri = Restoration Time for each Interruption Event CI = Customers Interrupted CMI = Customer Minutes Interrupted E = Events T = Total IMi = Number of Momentary Interruptions IME = Number of Momentary Interruption Events Ni = Number of Interrupted Customers for each Sustained Interruption event during theReporting Period Nmi = Number of Interrupted Customers for each Momentary Interruption event during the Reporting Period NT = Total Number of Customers Served for the Areas Li = Connected kVA Load Interrupted for each Interruption Event SCHEDULE 2 SL 11 of 2012 LT = Total connected kVA Load Served CN = Total Number of Customers who have Experienced a Sustained Interruption during the Reporting Period CNT(k>n) = Total Number of Customers who have Experienced more than n Sustained Interruptions and Momentary Interruption Events during the Reporting Period. k = Number of Interruptions Experienced by an Individual Customer in the Reporting Period TMED = Major event day identification threshold value. 4.2 Sustained interruption indices 4.2.1 System average interruption frequency index (SAIFI) The system average interruption frequency index indicates how often the average customer experiences a sustained interruption over a predefined period of time. Mathematically, this is given in Equation (1). (1) To calculate the index, use Equation (2) below. (2) 4.2.2 System average interruption duration index (SAIDI) This index indicates the total duration of interruption for the average customer during a predefined period of time. It is commonly measured in customer minutes or customer hours of interruption. Mathematically, this is given in Equation (3). (3) To calculate the index, use Equation (4). SCHEDULE 2 SL 11 of 2012 (4) 4.2.3 Customer average interruption duration index (CAIDI) CAIDI represents the average time required to restore service. Mathematically, this is given in Equation (5). (5) To calculate the index, use Equation 6. (6) 4.2.4 Customer total average interruption duration index (CTAIDI) This index represents the total average time in the reporting period that customers who actually experienced an interruption were without power. This index is a hybrid of CAIDI and is similarly calculated except that those customers with multiple interruptions are counted only once. Mathematically, this is given in Equation (7). (7) To calculate the index, use Equation (8). (8) NOTE\u2014 In tallying Total Number of Customers Interrupted, each individual customer should only be counted once regardless of number of times interrupted during the reporting period. This applies to 4.2.4 and 4.2.5. 4.2.5 Customer average interruption frequency index (CAIFI) This index gives the average frequency of sustained interruptions for those customers experiencing sustained interruptions. The customer is counted once regardless of the number of times interrupted for this calculation. Mathematically, this is given in Equation (9). SCHEDULE 2 SL 11 of 2012 (9) To calculate the index, use Equation (10) (10) 4.2.6 Average service availability index (ASAI) The average service availability index represents the fraction of time (often in percentage) that a customer has received power during the defined reporting period. Mathematically, this is given in Equation (11). (11) To calculate the index, use Equation (12). (12) NOTE\u2014There are 8760 hours in a non-leap year, 8784 hours in a leap year. 4.2.7 Customers experiencing multiple interruptions (CEMIn) This index indicates the ratio of individual customers experiencing more than n sustained interruptions to the total number of customers served. Mathematically, this is given in Equation (13). (13) To calculate the index, use Equation (14). (14) NOTE\u2014This index is often used in a series of calculations with n incremented from a value of one to the highest value of interest. SCHEDULE 2 SL 11 of 2012 4.3 Load based indices 4.3.1 Average system interruption frequency index (ASIFI) The calculation of this index is based on load rather than customers affected. ASIFI is sometimes used to measure distribution performance in areas that serve relatively few customers having relatively large concentrations of load, predominantly industrial\/commercial customers. Theoretically, in a system with homogeneous load distribution, ASIFI would be the same as SAIFI. Mathematically, this is given in Equation (15). (15) To calculate the index, use Equation (16). (16) 4.3.2 Average system interruption duration index (ASIDI) The calculation of this index is based on load rather than customers affected. Its use, limitations, and philosophy are stated in the ASIFI definition in 4.3.1. Mathematically, this is given in Equation (17). (17) To calculate the index, use Equation (18). (18) 4.4 Other indices (momentary) 4.4.1 Momentary average interruption frequency index (MAIFI) This index indicates the average frequency of momentary interruptions. Mathematically, this is given in Equation (19). (19) SCHEDULE 2 SL 11 of 2012 To calculate the index, use Equation (20). (20) 4.4.2 Momentary average interruption event frequency index (MAIFIE) This index indicates the average frequency of momentary interruption events. This index does not include the events immediately preceding a lockout. Mathematically, this is given in Equation (21). (21) To calculate the index, use Equation (22). (22) 4.4.3 Customers experiencing multiple sustained interruption and momentary interruption events (CEMSMIn) This index is the ratio of individual customers experiencing more than n of both sustained interruptions and momentary interruption events to the total customers served. Its purpose is to help identify customer issues that cannot be observed by using averages. Mathematically, this is given in Equation (23). (23) To calculate the index, use Equation (24). (24) 4.5 Major event day classification The following process (\u2015Beta Method\u2016) is used to identify MEDs. Its purpose is to allow major events to be studied separately from daily operation, and in the process, to better reveal trends in daily operation that would be hidden by the SCHEDULE 2 SL 11 of 2012 large statistical effect of major events. This approach supersedes previous major event definitions (see Annex A for sample definitions). For more technical detail on derivation of the methodology refer to Annex B. A major event day is a day in which the daily system SAIDI exceeds a threshold value, TMED. The SAIDI index is used as the basis of this definition since it leads to consistent results regardless of utility size and because SAIDI is a good indicator of operational and design stress. Even though SAIDI is used to determine the major event days, all indices should be calculated based on removal of the identified days. In calculating daily system SAIDI, any interruption that spans multiple days is accrued to the day on which the interruption begins. The major event day identification threshold value, TMED, is calculated at the end of each reporting period (typically one year) for use during the next reporting period as follows: a) Collect values of daily SAIDI for five sequential years ending on the last day of the last complete reporting period. If fewer than five years of historical data are available, use all available historical data until five years of historical data are available. b) Only those days that have a SAIDI\/Day value will be used to calculate the TMED (do not include days that did not have any interruptions). c) Take the natural logarithm (ln) of each daily SAIDI value in the data set. d) Find \uf061 (Alpha), the average of the logarithms (also known as the log-average) of the data set. e) Find \uf062 (Beta), the standard deviation of the logarithms (also known as the log- standard deviation) of the data set. f) Compute the major event day threshold, TMED, using equation (25). (25) g) Any day with daily SAIDI greater than the threshold value TMED that occurs during the subsequent reporting period is classified as a major event day. Activities that occur on days classified as major event days should be separately analyzed and reported. SCHEDULE 2 SL 11 of 2012 4.5.1 An example of using the major event day definition An example of using the major event day definition to identify major events and subsequently calculate adjusted indices that reflect normal operating performance is shown in this subclause. This subclause illustrates the calculation of the daily SAIDI, calculation of the major event day threshold TMED, identification of major event days, and calculation of adjusted indices. Table 1 gives selected data for all outages occurring on a certain day for a utility that serves 2,000 customers. (26) One month of historical daily SAIDI data is used in the following example to calculate the Major Event Day threshold TMED. Five years of historical data is preferable for this method, but printing that many values in this standard is impractical, so only one month is used to illustrate the concept. The example data is shown in Table 2. SCHEDULE 2 SL 11 of 2012 The value of \uf061, the log -average, is the average of the natural logs, and equals \u2013 0.555 in this case. The value of \uf062, the log -standard deviation, is the standard deviation of the natural logs, and equals 1.90 in this example. The value of \uf061 + 2.5\uf062 is 4.20. The threshold value TMED is calculated by e(4.20) and equals 66.69 SAIDI per day. This value is used to evaluate the future time period (e.g., the next year). Table 3 shows example SAIDI\/day values for the first month of 1994. SCHEDULE 2 SL 11 of 2012 The SAIDI\/day on 1\/28\/94 (237.49) exceeds the example threshold value (TMED = 66.69), indicating that the distribution system experienced stresses beyond that normally expected on that day. Therefore, 1\/28\/94 is classified as a major event day. The SAIDI\/day for all other days was less than TMED, indicating that normal stresses were experienced on those days. To complete the example, indices should be calculated for the following two conditions: a) all events included b) major event days removed. In most cases, utilities will calculate all of the indices they normally use (e.g., SAIFI, SAIDI and\/or CAIDI). For this example, only SAIDI will be shown. 1994 SAIDI for condition one, all events included, is given in Equation (27) below. (27) 1994 SAIDI for condition two, major event days removed for separate reporting and analysis, is given in equation 28 below. (28) SCHEDULE 2 SL 11 of 2012 5. Application of the indices Most utilities store interruption data in large computer databases. Some databases are better organized than others for querying and analyzing reliability data. The following section will show one sample partial database and the methodology for calculating indices based on the information provided. 5.1 Sample system Table 4 shows an excerpt from one utility\u2019s customer information system (CIS) database for feeder 7075, which serves 2,000 customers with a total load of 4 MW. In this example, Circuit 7075 constitutes the \u2015system\u2016 for which the indices are  calculated.  More  typically  the  \u2015system\u2016  combines  all  circuits together  in  a region or for a whole company. The total number of customers who have experienced a sustained interruption is 3,215. The total number of customers experiencing a momentary interruption is 2, 400. SCHEDULE 2 SL 11 of 2012 From Table 6, it can be seen that there were eight circuit breaker operations that affected 2000 customers. Each of them experienced 8 momentary interruptions. There were twelve recloser operations that caused 750 customers to experience 12 momentary interruptions. Some of the operations occurred during one reclosing sequence. To calculate the number of momentary interruption events, only count the total number of reclosing sequences. In this case there were five circuit breaker events (records 1, 3, 4, 7, and 9) that affected 2000 customers. Each of them experienced 5 momentary interruption events. There were six recloser events (records 2, 5, 6, 8, 10 and 11) that affected 750 customers each of them experienced 6 momentary interruption events. 5.2 Calculation of indices for a system with no major event days The equations in Clause 4.5 and definitions in Clause 3 should be used to calculate the annual indices (see Equations (29) \u2013 (40)). In the example below, SCHEDULE 2 SL 11 of 2012 the indices are calculated by using the equations in 4.2 and 4.4 using the data in Table 4 and Table 5, assuming there were no major event days in this data set. To calculate CTAIDI and CAIFI, the number of customers experiencing a sustained interruption is required. The total number of customers affected (CN) for this example can be no more than 2000. Since only a small portion of the customer information table is shown it is impossible to know CN; however, it is likely that not all of the 2000 customers on this feeder experienced an interruption during the year. 1800 will be arbitrarily assumed for CN (for your calculations actual information should be used) since the interruption on 9\/3 shows that at least 1500 customers have been interrupted during the year. CTAIDI, CAIFI, CEMIn, and CEMSMIn require detailed interruption information for each customer. The database should be searched for all customers who have experienced more than n interruptions that last longer than five minutes. Assume n is chosen to be 5. In Table 5, customer Willis, J. experienced seven interruptions in one year and it is plausible that other customers also experienced more than five interruptions, both momentary and sustained. For this example, assume arbitrary values of 350 for CN(k > n), and 750 for CNT(k > n). The number of interrupting device operations is given in Table 6 and is used to calculate MAIFI and MAIFIE. Assume the number of customers downstream of the recloser equals 750. These numbers would be known in a real SCHEDULE 2 SL 11 of 2012 system. Using the above sample system should help define the methodology and approach to obtaining data from the information systems and using it to calculate the indices. 5.3 Examples The following subclause illustrates two concepts: momentary interruptions and step restoration through the use of examples. 5.3.1 Momentary interruption example To better illustrate the concepts of momentary interruptions and sustained interruptions and the associated indices, consider Figure 1 and Equation 41, Equation 42, and Equation 43. Figure 1 illustrates a circuit composed of a circuit breaker (B), a recloser (R), and a sectionalizer (S). For this scenario, 750 customers would experience a momentary interruption and 250 customers would experience a sustained interruption. Calculations for SAIFI, MAIFI, and MAIFIE on a feeder basis are shown in Equations 41\u201343 below. Notice that the numerator of MAIFI is multiplied by 2 because the recloser took two shots, however, MAIFIE is multiplied by 1 because it only counts the fact that a series of momentary events occurred. SCHEDULE 2 SL 11 of 2012 5.3.2 Step restoration examples The following case illustrates the step restoration process. A feeder serving 1000 customers experiences a sustained interruption. Multiple restoration steps are required to restore service to all customers. Table 7 shows the times of each step, a description and associated customers interruptions and minutes they were affected in a time line format. Figure 2 illustrates the example described in Table 7. In this example, all of the customers supplied by the circuit were interrupted at the beginning of step 1. Service was restored to a portion of those customers at the end of step 1. Service was restored to another portion of those customers at the end of step 2. Additional customers were interrupted during step 3 (new step 1). Service was restored to additional customers at the end of step 3. SCHEDULE 2 SL 11 of 2012 Table 8 shows the information in a format that explains each step and allows the reader to see the calculation steps. 6. Information about the factors which affect the calculation of reliability indices 6.1 Rationale behind selecting the indices provided in this guide One view of distribution system performance can be garnered through the use of reliability indices. To adequately measure performance, both duration and frequency of customer interruptions must be examined at various system levels. The most commonly used indices are SAIFI, SAIDI, CAIDI and ASAI. All of these indices provide information about average system performance. Many SCHEDULE 2 SL 11 of 2012 utilities also calculate indices on a feeder basis to provide more detailed information for decision making. Averages give general performance trends for the utility; however, using averages will lead to loss of detail that could be critical to decision making. For example, using system averages alone will not provide information about the interruption duration experienced by any specific customer. At the time of this writing, it is difficult for most utilities to provide information on a customer basis. This group envisions that the tracking of specific details surrounding specific interruptions rather than averages will, in the future, be accomplished by improving tracking capabilities. To this end, the working group has included not only the most commonly used indices, but also indices that examine performance at the customer level (e.g., CEMIn). 6.2 Factors that cause variation in reported indices Many factors can cause variation in the indices reported by different utilities. Some examples of differences in the following: \u2014 level of automated data collection \u2014 geography \u2014 system design \u2014 data classification (e.g., are major events in the data set?, planned interruptions?) To ensure accurate and equitable assessment and comparison of absolute performance and performance trends over time, it is important to classify performance for each day in the data set to be analyzed as either day-to-day or major event day. Not performing this critical step can lead to false decision making because major event day performance often overshadows and disguises daily performance. Interruptions that occur as a result of outages on customer owned facilities or loss of supply from another utility should not be included in the index calculation. SCHEDULE 2 SL 11 of 2012 Annex A (informative) Survey of reliability index usage The Working Group on System Design conducted three surveys on distribution reliability index usage. The first one was completed in 1990 and the second was completed in 1995 and the third one was completed in 1997. The purpose of the surveys was to determine index usage and relative index values. In 1990, 100 United States utilities were surveyed, 49 of which responded. In 1995, 209 utilities were surveyed, 64 of which responded. In 1997, 159 utilities were surveyed and 61 responded. Responding utility locations are shown by state in Figure A.1. Newer surveys are being performed by Edison Electric Institute (EEI). The data provided is not comparable because utilities provided whatever information was easily obtainable. All surveys showed that the most commonly used indices are SAIFI, SAIDI, CAIDI, and ASAI. Figure A.2 shows the percentage of companies using specific indices in 1990. Figure A.3 shows the same information for 1995 and 1997. Figures A.4\u2013A.8 show data on the most commonly used indices given by quartiles where Q1 is the top quartile. The data shown in the Q1 column means that 25% of utilities have an index less than the value shown. For further clarification: SCHEDULE 2 SL 11 of 2012 Q1: 25% of utilities have an index less than the value shown Q2: 50% of utilities have an index less than the value shown (the median value) Q3: 75% of utilities have an index less the value shown Q4:100% of utilities have an index less the value shown SCHEDULE 2 SL 11 of 2012 SCHEDULE 2 SL 11 of 2012 SCHEDULE 2 SL 11 of 2012 A.1 Cause codes In the 1997 survey, cause codes were surveyed. The results are shown below in Figure A.9. SCHEDULE 2 SL 11 of 2012 A.2 Results of question # 7 of the 1999 EEI reliability survey The following information was provided by the Edison Electric Institute (EEI) based on a survey they performed in 1999. The text is shown exactly as the survey respondents provided the information to EEI. What definition do you use for major events? 1) Major storm defined as 10% or more of the customer base interrupted in an operating region (based on 8 operating regions) or customers interrupted for 24 hours. 2) Interruptions that result from a catastrophic event that exceeds the design limits of the electric power system, such as an earthquake, tornado, or an extreme storm. 3) A major storm is an event that affects 10% or more of the connected customers with 1% not restored within 24 hours. 4) Ten percent or more of our customers are without power and have been without power for more than 24 hours. 5) The major storm exclusion a criterion is based on a statistical analysis of the last four-year history of reliability data. A cumulative frequency distribution of the number of locations requiring service restoration work per day is calculated SCHEDULE 2 SL 11 of 2012 for the four-year period. When the frequency of the restoration work exceeds the 98.5 percentile, by company or region the major storm criterion work be met for the all interruptions for that day. 6)  Ten percent of customers in a given region affected by an event plus the last customer out greater than 24 hours. All three of the following must be true: \u2014widespread damage \u201410 000 or 10% of customers served in area affected \u2014National Weather Service declares severe weather watch or warning for the area 7) Ten percent customer base and 1 customer for 24 hours. 8) More than 15 000 customers out (out of a total customer base of 450 000). 9) As defined by our PUC as named storms, tornados, ice storms, etc. 10) Events where 10% of your customers (meters) have experienced an interruption due to the event. 11) IEEE Std 1366\u2122-1998; Definition 3.12 major event. Company 1 defined as, 10% of the customers within a region without electricity and not restored within a 24 hour period. 12) Ten percent of the entire electric system\u2019s customers must experience an interruption in service and one percent of the entire electric system\u2019s customers must experience an interruption in service for more than 24 hours. 13) Ten percent of customers out of service and restoration time exceeding 24 hours. 14) Named storms, i.e. hurricane, tropical storms, or tornadoes verified by the National Weather Service. Major forest fires are also included. In addition, Company 2 reporting definition does not include planned interruptions. MAIFI is reported as momentary events. 15) (1) Winds in excess of 90 mph OR (2) 1\/2 inch of ice and winds in excess of 40 mph. NOTE\u2014 The major storm outage minutes in 1999 were minimal for Company 3 and did not impact the reliability measures. SCHEDULE 2 SL 11 of 2012 16) 0.8 hours x customers served for a month, if the customer hours lost for any one day in that month exceed this value it can be removed from our year-end calculations. Interruptions that result from a catastrophic event that exceeds the design limits of the electric power system, such as an earthquake or an extreme storm. These events shall include situations where there is a loss of power to 10% or more of the customers over a 24-hour period and with all customers not restored within 24 hours. 17) State of Connecticut Department of Public Utility Control \u2013 Major Storm Exclusion Definition for 1999 \u2013 Any day or 24-hour period, where 31 restoration steps or greater were experienced. For 2000, the UI storm exclusion is based on 35 restoration steps or greater. The change in storm exclusion restoration step threshold, is based on the previous four-year outage history. 18) A period of adverse weather which interrupts 10% or more of the customers served in an operating area, or results in customers being without power for 24 hours or longer. 19) Weather events that cause more than 100 000 customers to be interrupted, with restoration taking at least 24 hours. 20) (1) A Watch or Warning has been issued by the National Weather Service, (2) Extensive mechanical damage has been experienced and (3) More than 6% of the customers served in a region have been affected by outages during a 12-hour period. 21) A major storm is defined as the interruption to 110 000 customers or more which is about 5 percent of our total customers. The 110 000 was arrived at by going out six standard deviations from the mean of all daily cases of trouble. 22) Any outage lasting longer than 48 hours is capped at 48 hours. 23) Any event outage over 10% of the customers in a region AND requiring over 24 hours to restore service to all customers. (PUC definition) Outages occurring during qualifying major storms are not entered into our system, therefore we can only report on 8B, 11B, and 13B below. 24) Determination is subjective, not strictly defined at this time. 25) Tropical storms, hurricanes, tornados, and ice storms. 26) Interruptions that result from a catastrophic event that exceeds the design limits of the electric power system, such as an earthquake or an extreme storm. SCHEDULE 2 SL 11 of 2012 These events shall include situations where there is a loss of power to 10% or more customers in a region over a 24-hour period and with all customers not restored within 24 hours. 27) >10% of customers out of service for >24 hours. 28) 15 000 or more customers out of service. 29) Ten percent of customers in an area (region) interrupted. 30) (1) 10% or more of customers interrupted in a operating area. And (2) A storm or other large occurrence where customers experience an interruption for 24 or more hours in an operating area. 31) A storm is determined at regional level when in any consecutive 24 hours the cumulative outages reach 15 AND cumulative customer interruption minutes reach 200 000 32) A major storm is defined as an interruption of electric service resulting from conditions beyond the company\u2019s control, which affects at least 10% of the customers in an operating area during the course of an event. 33) Level 3 or above out of 5 according to our emergency plan. About 5 storms per year excluded. 34) Any day during which the number of interruptions are greater than 3 standard deviations above average. 35) CAIDI for the storm period must be 2.5 times normal. Outside crews required to restore damage. Restoration of damage must require 24 hours or more. 36) Named Storms (i.e. hurricane). 37) Extension mechanical damage to the electric system. Outages involving more than 10% of the customers served by district. More than 1% of the customers serviced have not been restored within 24 hours. 38) 15 000 or more customers outages. SCHEDULE 2 SL 11 of 2012 39) (1) > 10% of the customers out of service at any one time, reported on a district basis. and (2) Extraordinary storm event such as a tornado, severe winds, etc. 40) A major storm is one which affects 15 000 of our approximately 120 000 customers AND makes an incremental addition of 10 min to company SAIDI. 41) A storm or equipment failure that would cause widespread serious damage throughout the service area in such proportion that available Company 4 forces would be unable to restore service within 48 hours. We designate this as a Level III event \u2013 Company 4 has 3 levels of event classifications There were no Level III events in 1999. 42) The major storm exclusion criterion is based on a statistical analysis of the last four-year history of reliability data. A cumulative frequency distribution of the number of locations requiring service restoration work per day is calculated for the four-year period. When the frequency of the restoration work exceeds the 98.5 percentile, by company or region the major storm criterion work be met for the all interruptions for that day. 43) Named storms, tornadoes, ice, events with >10% of customers out. 44) An interruption of electric service resulting from conditions beyond the control of the electric distribution company which affects at least 10% of the customers in an operating area during the course of event for a duration of 5 min each or greater. 45) An interruption of electric service resulting from conditions beyond the control of the electric distribution company which affects at least 10% of the customers in an operating area. SCHEDULE 2 SL 11 of 2012 Annex B (informative) Major events definition development B.1 Justification and process for development of the 2.5 beta methodology The statistical approach to identifying major event days was chosen over the previous definitions (as shown in A.2) because of the difficulties experienced in creating a uniform list of types of major events, and because the measure of impact criterion (i.e., percent of customers affected) required when using event types resulted in non-uniform identification. The new methodology should fairly identify major events for all utilities. Some key issues had to be addressed in order to consider this work successful. They were as follows: \u2014 Definition must be understandable and easy to apply. \u2014 Definition must be specific and calculated using the same process for all utilities. \u2014 Must be fair to all utilities regardless of size, geography, or design. \u2014 Entities that adopt the methodology will calculate indices on a normalized basis for trending and reporting. They will further classify the major event days separately and report on those days through a separate process. Daily SAIDI values are preferred to daily customer minutes interrupted (CMI) values for major event day identification because the former permits comparison and computation among years with different numbers of customers served. Consider the merger of two utilities with the same reliability and the same number of customers. CMI after the merger would double, with no change in reliability, while SAIDI would stay constant. Daily SAIDI values are preferred to daily SAIFI values because the former are a better measure of the total cost of reliability events, including utility repair costs and customer losses, than the latter. The total cost of unreliability would be a better measure of the size of a major event, but collection of this data is not practical. The selected approach for setting the major event day identification threshold, known  as  the  \u2015Two  Point  Five  Beta\u2016  method  (since  it  is  using  the  lognormal SAIDI values rather than the raw SAIDI values), is preferred to using fixed multiples  of  standard  deviation  (e.g.  \u2015Three  Sigma\u2016)  to  set  the SCHEDULE 2 SL 11 of 2012 identification threshold because the latter results in non-uniform MED identification among utilities with different sizes and average reliabilities. The b multiplier of 2.5 was chosen because, in theory, it would classify 2.3 days per year as major events. If significantly more days than this are identified, they represent events that have occurred outside the random process that is assumed to control distribution system reliability. The process and the multiplier value were evaluated by a number of utilities with different sized systems from different parts of the United States and found to correlate reasonably well to current major event identification results for those utilities. A number of alternative approaches were considered. None was found to be clearly superior to Two Point Five Beta. When a major event occurs which lasts through midnight (for example, a six hour hurricane which starts at 9:00 PM), the reliability impact of the event may be split between two days, neither of which would exceed the TMED and therefore be classified as a major event day. This is a known inaccuracy in the method that is accepted in exchange for the simplicity and ease of calculation of the method. The preferred number of years of data (five) used to calculate the major event day identification threshold was set by trading off between the desire to reduce statistical variation in the threshold (for which more data is better) and the desire to see B.1.1 Remarks To generate the example data, values of a and b were taken from an actual utility data set, and then daily SAIDI\/day values were artificially generated using a log normal distribution wi then adjusted to illustrate all aspects of the calculation, e.g. a day in Table 2 was assigned a SAIDI value of zero, and a day in Table 3 was assigned a SAIDI value higher than the computed threshold. This annex provides a technical description and analysis of the 2.5\uf0e2 method of identifying MEDs in di method based on the theory of probability and statistics. Fundamental concepts such as probability distribution and expected value are highlighted in italics when they are first used, and provided with a short definition. An undergraduate probability and statistics textbook can be consulted for more complete definitions. SCHEDULE 2 SL 11 of 2012 B.1.2 Beta (\uf062) method description A threshold on daily SAIDI is computed once a year (see 4.5). The short version is as follows: a) Assemble the five most recent years of historical values of SAIDI\/day. If less than five years of data is available, use as much as is available. b) Discard any day in the data set that has a SAIDI\/Day of zero. c) Find the natural logarithm of each value in the data set. d) Compute the average (\uf061, or Alpha) and standard deviation (\uf062\uf02c or Beta) of the natural logarithms computed in step 3. e) Compute the threshold TMED = exp (Alpha + 2.5 * Beta). f) Any day in the next year with SAIDI > TMED is a major event day. B.2 Random nature of distribution reliability The reliability of electric power distribution systems is a random process, that is, a process that produces random values of a specific random variable. A simple example of a random process is rolling a die. The random variable is the value on the top face of the die after a roll, which can have integer values between 1 and 6. In electric power distribution system reliability, the random variables are the reliability indices defined in the guide. These are evaluated on a daily or yearly basis, and take on values from zero to infinity. B.3 Choice of SAIDI to identify major event days Four commonly used reliability indices are: \u2014 System Average Interruption Duration Index (SAIDI) \u2014 System Average Interruption Frequency Index (SAIFI) \u2014 Customer Average Interruption Duration Index (CAIDI) \u2014 Average Service Availability Index (ASAI) These indices are actually measures of unreliability, as they increase when reliability becomes worse. SCHEDULE 2 SL 11 of 2012 An ideal measure of unreliability would be customer cost of unreliability, the dollar cost of power outages to a utility\u2019s customers. This cost is a combination of the initial cost of an outage and accumulated costs during the outage. Unfortunately, the customer cost of unreliability has so far proven impossible to estimate accurately. In contrast, the reliability indices above are routinely and accurately computed from historical reliability data. However, the ability of an index to reflect customer cost of unreliability indicates the best one to use for major event day identification. Duration-related costs of outages are higher than initial costs, especially for major events, which typically have long duration outages. Thus a duration-related index will be a better indicator of total costs than a frequency-related index like SAIFI or MAIFI. Because CAIDI is a value per customer, it does not reflect the size of outage events. Therefore SAIDI best reflects the customer cost of unreliability, and is the index used to identify major event days. SAIDI in minutes\/day is the random variable used for major event day identification. The use of Customer Minutes Interrupted per day was also considered. Like SAIDI, CMI is a good representation of customer cost of unreliability. In fact, SAIDI is just CMI divided by the number of customers in the utility. The number of customers can vary from year to year, especially in the case of mergers, and multiple years of data are used to find major event days. Use of SAIDI accounts for the variation in customer count, while use of CMI does not. Therefore SAIDI is preferred. B.4 Probability distribution of distribution system reliability B.4.1 Probability density functions and probability of exceeding a threshold value MEDs will be days with larger SAIDI values. This suggests the use of a threshold value for daily SAIDI. The threshold value is called TMED. Days with SAIDI greater than TMED are major event days. As the threshold increases, there will be fewer days with SAIDI values above the threshold. The relationship between the threshold and the number of days with SAIDI above the threshold is given by the probability density function of SAIDI\/day. The probability density function gives the probability that a specific value of a random variable will appear. For example, for a six sided die, the probability that SCHEDULE 2 SL 11 of 2012 a one will appear in a given roll is 1\/6th, and the value of the probability density function of one is 1\/6th for this random process. The probability that a value greater than one will occur is just the sum of the probability densities for all values greater than one. Since each value has a probability density of 1\/6th for the example, this sum is just 5\/6ths. As the threshold increases, the probability decreases. For example, for a threshold of 4, there are only two values greater than 4, and the probability of rolling one of them is 2\/6ths or 1\/3rd. In the die rolling example, the random variable can only have discrete integer values. SAIDI\/day is a continuous variable. In this case, the sum is replaced by an integral. The probability p that any given day will have a SAIDI\/day value greater than a threshold value T is the integral of the probability density function from the threshold to infinity as shown below in Equation (B.1). (B.1) Graphically, the probability is the area under the probability density function above the threshold, as shown in Figure B.1. If any given day has a probability p of being a major event day, then the expected value [see Equation (B.2)] of the number of major event days in a year is the probability times the number of days in a year. (B.2) For example, if p = 0.1, then the expected number of major event days in a year is 36.5. This does not mean that exactly 36.5 MEDs will occur. The actual number will vary due to the randomness of the process. SCHEDULE 2 SL 11 of 2012 Using the die rolling example, the probability of getting a six in any roll is 1\/6th. Therefore the expected number of sixes in six rolls is 1. However, if the die is rolled six times, there could be six sixes, or zero sixes, or any number in between. As the number of trials goes up, the number of sixes will approach 1\/6th of the number of rolls, but for small numbers of rolls there will be some variation from the expected value. B.4.2 Gaussian, or normal distribution The expected number of MEDs per year can be computed for any given threshold if the shape of the probability density function is known. The shape of the probability density function is called the probability distribution. Specific types of shapes have specific names. The most well known is the Gaussian distribution, also called the normal distribution or bell curve, shown in Figure B.2. The Gaussian distribution is completely described by its mean, or average value, (\u03bc or Mu) and its stan alue is at the center of the distribution (at 0 on the x axis in Figure B.2) and the standard deviation is a measure of the spread of the distribution. An important property of the Gaussian distribution is that the probability of exceeding a given threshold is a function of the number of standard deviations the threshold is from the mean. Equation (B.3) provides mathematical terms. (B.3) If the threshold is n standard deviations greater than the mean, and the probability of exceeding the threshold, p(SAIDI > TMED), is a function only of n, and not of SCHEDULE 2 SL 11 of 2012 the mean and standard deviation. Values for this function are found in tables in the backs of probability textbooks and in, for example, standard spreadsheet functions. Table B.1 gives the probability of exceeding the threshold for different number of standard deviations k. B.4.3 Three sigma The term \u2015Three Sigma\u2016 is often used loosely to designate a rare event. It comes from the Gaussian probability distribution. As Table B.1 shows, the probability of exceeding a threshold that is three standard deviations more than the mean is 0.00135, or one and a half tenths of a percent. If daily SAIDI had a Gaussian probability distribution, it would be relatively easy to agree on a Three Sigma definition for the major event day threshold, TMED. Unfortunately, SAIDI does NOT have a Gaussian distribution. It has a log-normal distribution. B.5 Log-normal distribution The random variable in the Gaussian distribution has a range from \u2013\uf0a5 to \uf0a5. In real life, many quantities, including distribution reliability, can only be zero or positive. This causes the probability distribution to skew, bunching up near the zero axis and having a long tail to the right. The degree of skewness depends on the ratio of mean to standard deviation. When the standard deviation is small compared to the mean, the log normal distribution looks like the Gaussian distribution, as shown in Figure B.3(b). When it is large compared to the mean, it does not, as shown in Figure B.3(a). Daily reliability data usually has standard deviation values far larger than the mean. SCHEDULE 2 SL 11 of 2012 A consequence of the log-normality of daily reliability data is that the three sigma conditions no longer hold. In particular, the probability of exceeding a given threshold is no longer independent of the values of the average and standard deviation of the distribution. This means that using a method such as Three Sigma would result in different numbers of MEDs for utilities with different average values of reliability, or with different standard deviation values. This seems inequitable. Fortunately, the logarithms of log-normal data have a Gaussian distribution. If the average of the logarithms of the data is called \uf061, or Alpha, and the standard deviation of the logari mean and standard deviation of a Gaussian distribution and a threshold on the log of the data can be set which is independent of the values of \uf0e1 and \u00df. Equations (B.4) and (B.5) show these concepts mathematically. (B.4) and (B.5) The probability of exceeding TMED is a function of k, just as in the Gaussian example. Table B.2 gives these probabilities as well as the expected number of Major Event Days (MEDs) for various values of k. SCHEDULE 2 SL 11 of 2012 B.5.1 Why 2.5? Given an allowed number of MEDs per year, a value for k is easily computed. However, there is no analytical method of choosing an allowed number of MEDs\/year. The chosen value of k = 2.5 is based on consensus reached among Distribution Design Working Group members on the appropriate number of days that should be classified as Major Event Days. As Table B.2 shows, the expected number of days for k = 2.5 is 2.3 MEDs\/year. In practice, the experience of the committee members, representing a wide range of distribution utilities, was that more than 2.3 days were usually classified as MEDs, but that the days that were classified as MEDS were generally those that would have been chosen on qualitative grounds. The performance of different values of k were examined, and consensus was reached on k = 2.5. B.6 Fairness of the 2.5\u00df method It is likely that reliability data from different utilities will be compared by utility management, public utilities commissions and other interested parties. A fair MED classification method would classify, on average, the same number of MEDs per year for different utilities. The two basic ways that utilities can differ in reliability terms are in the mean and standard deviation of their reliability data. Differences in means are attributable to differences in the environment between utilities, and to differences in operating and maintenance practices. Differences in standard deviation are mostly attributable to size. Larger utilities have inherently smaller standard deviations. As discussed above, using the mean and standard deviation of the logs of the data MEDs depend only on the multiplier, and thus should classify the same number of MEDs for large and small utilities, and for utilities with low and high average reliability. This is not the case for using the mean and standard deviation of the data without taking logarithms first. The expected number of MEDs varies the average and standard deviation. This variation occurs because of the log-normal nature of the reliability probability distribution. B.7 Five years of data From a statistical point of view, the more data used to calculate a threshold, the SCHEDULE 2 SL 11 of 2012 better. However, the random process producing the data changes over time as the distribution system is expanded and operating procedures are varied. Using too much historical data would suppress the effects of these changes. The addition of another year of data should have a low probability of changing the MED classification of previous years. A result from order statistics gives the probability that the kth largest value in m samples will be exceeded f times in n future samples [B10]. It is given in Equation (B.5). (B.5) For example, if M = 3 years of data then m = 1095 samples. If f = 3 MEDs\/year then the largest non-MED is the k = 1095 \u20139 = 1086th ordered sample. The probability of f = 3 days in the next year of n = 365 samples exceeding the size of the largest non-MED is found from the equation to be 0.194 (19.4%). In Figure B.5 p is plotted against M for several values of f. The consensus of the Design Working Group members was that 5 years was the appropriate amount of data to collect. They felt that the distribution system would change enough to invalidate any extra accuracy from more than 5 years of data. Annex C (informative) Internal data subset C.1 Calculation of reliability indices for subsets of data for internal company use Reliability performance can be assessed for different purposes. It may be advantageous to calculate reliability indices without planned interruptions in order to review performance during unplanned events. In another case, it may be SCHEDULE 2 SL 11 of 2012 advantageous to review only sustained interruptions. Assessment of performance trends and goal setting should be based on normal event days (neglecting the impact of MEDs). Utilities and regulators determine the most appropriate data to use for reliability performance monitoring. When indices are calculated using partial data sets, the basis should be clearly defined for the users of the indices. At a minimum, reliability indices based on all collected data for a reporting period and analyzed as to normal versus major event day classifications should be provided. Indices based on subsets of collected data may be provided as specific needs dictate. SCHEDULE 2 SL 11 of 2012 Annex D (informative) Bibliography [B1] \u2015A Nationwide Survey of Distribution Reliability Measurement Practices,\u2016 IEEE\/PES Working Group on System Design, Paper No. 98 WM 218. [B2] Balijapelli N., Venkata S. S., Christie R. D., \u2015Predicting Distribution System Performance Against Regulatory Reliability Standards,\u2016 to appear in IEEE Transactions on Power Delivery. [B3]  Blinton,  R.  and  Allan  R.  N.,  \u2015Reliability  Evaluation  of  Power  Systems,\u2016 Plenum Press, 1984. [B4] Billinton R., Allan R., Salvaderi L., Applied Reliability Assessment in Electric Power Systems, IEEE Press, New York, 1991. [B5] Brown R.E., Electric Power Distribution Reliability, Marcel Dekker, New York, 2002. [B6]  Capra,  R.  A.,  Gangel,  M.  W.,  and  Lyon,  S.V.  \u2015Underground  Distribution System Design for Reliability,\u2016IEEE Transactions on Power Apparatus and Systems, Vol. PAS-88, No. 6, June 1969, pp. 834-42. [B7] Christie R.D., \u2015Statistical Classification of Major Event Days in Distribution System Reliability,\u2016accepted to IEEE Transactions on Power Delivery.4 [B8] EPRI EL-2018, RP-1356-1, Development of Distribution System Reliability and Risk Analysis Models,\\\" Vol. 2, August 1981. [B9] IEEE 100, The Authoritative Dictionary of IEEE Standard Terms, 7th Edition.5 [B10] Kottegoda N. T., and Rosso R., Statistics, Probability, and Reliability for Civil and Environmental Engineers, McGraw-Hill, New York, 1997. [B11]   Marinello,   C.   A.,   \u2015A   Nationwide   Survey   of   Reliability Practices,\u2016 presented at EEI Transaction and Distribution Committee Meeting, Hershey, PA, October 20, 1993. SCHEDULE 2 SL 11 of 2012 Made by the Authority, after consultation with the Governor and the licensee, the 8th day of March, 2012. S.B. Cowan Chairman. D.B.R. Rankine Member. Mike Herland Member. D.L. Tibbetts Member. 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\"FRBRManifestation\": {\"FRBRuri\": \"\/akn\/ky\/act\/sl\/2012\/11\/eng@2012-01-01.xml\", \"FRBRdate\": [{\"date\": \"2026-06-22\", \"name\": \"generation\"}], \"FRBRthis\": \"\/akn\/ky\/act\/sl\/2012\/11\/eng@2012-01-01.xml\", \"FRBRauthor\": [{\"as\": \"#editor\", \"href\": \"\/akn\/ontology\/canary\/organization\/editor\/cilegis\"}], \"FRBRformat\": \"application\/xml\"}}}, \"name\": \"act\", \"header\": {\"title\": \"Electricity Regulatory Authority (Standard of Performance) Rules\", \"actNumber\": \"11 of 2012\", \"longTitle\": null}}, \"doc\": null, \"bill\": null, \"judgment\": null}}","akn_full_text":"CAYMAN ISLANDS\n\nElectricity Regulatory Authority Law\nELECTRICITY REGULATORY AUTHORITY\n(STANDARD OF PERFORMANCE) RULES,\n2012\n\n(SL 11 of 2012)\nSupplement No. 1 published with Gazette No. 7 dated 26th March, 2012.\n\nPage 2\nSL 11 of 2012\nc\n\nPUBLISHING DETAILS\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nArrangement of Rules\n\nc\nSL 11 of 2012\nPage 3\n\nCAYMAN ISLANDS\n\nElectricity Regulatory Authority Law\nELECTRICITY REGULATORY AUTHORITY\n(STANDARD OF PERFORMANCE) RULES,\n2012\n(SL 11 of 2012)\nArrangement of Rules\nRule\nPage\n1.\nCitation ......................................................................................................................................5\n2.\nDefinitions ..................................................................................................................................5\n3.\nInitial Period ...............................................................................................................................6\n4.\nRewards and penalties ..............................................................................................................7\n5.\nT&D standards and requirements ..............................................................................................7\n6.\nCustomer service standards ......................................................................................................9\n7.\nGeneration performance standards and requirements ............................................................. 10\nSCHEDULE 1\n13\nIEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability,\nAvailability, and Productivity\n13\nSCHEDULE 2\n45\nIEEE Guide for Electric Power Distribution Reliability Indices\n45\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nRule 1\n\nc\nSL 11 of 2012\nPage 5\n\nCAYMAN ISLANDS\n\nElectricity Regulatory Authority Law\nELECTRICITY REGULATORY AUTHORITY\n(STANDARD OF PERFORMANCE) RULES,\n2012\n(SL 11 of 2012)\nIn exercise of the powers conferred by sections 66 and 89(3) of the Electricity Regulatory\nAuthority Law (2010 Revision), the Authority, after consultation with the Governor and\nthe licensee, makes the following Rules \u2014\n1.\nCitation\n1.\nThese Rules may be cited as the Electricity Regulatory Authority (Standard of\nPerformance) Rules, 2012.\n2.\nDefinitions\n2.\nIn these Rules \u2014\n\u201cEAF\u201d means the Equivalent Availability Factor as defined by ANSI\/IEEE\nStandard 762-1987(R2002) (set out in Schedule 1) which is the fraction of the\nmaximum generation that could be provided if limited only by outages and\nderatings (per unit or plant basis) and is calculated as available generation\ndivided by maximum generation multiplied by 100% (unit or total plant basis);\n\u201cIG\u201d means Imperial Gallon, corrected to ISO standard conditions;\n\u201cInitial Period\u201d  means the period commencing on 1st January, 2011, and\nterminating on 31st December, 2012;\n\nRule 3\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 6\nSL 11 of 2012\nc\n\n\u201cNet Fuel Efficiency\u201d means the annual total plant net actual generation\ndivided by the annual total plant fuel consumption for electrical generation\nduring the year;\n\u201cplanned outage\u201d means the state in which a unit is unavailable due to\ninspection, testing or overhaul and that outage is scheduled in advance of its\noccurrence;\n\u201cPlanned Outage Factor\u201d means planned outage hours divided by the period\nhours and multiplied by 100% when measured on a per unit basis or the sum\nof the planned outage hours multiplied by the gross maximum generation per\nunit for all of the units in the active state and then divided by the gross\nmaximum generation for the plant on a total plant basis;\n\u201cSAIDI\u201d means the System Average Interruption Duration Index which is the\ntotal hours, on average, that a customer could expect to be without electricity\nover a year, calculated as the sum of the duration of each customer interruption\n(in hours), divided by the total number of connected customers averaged over\nthe year;\n\u201cSAIFI\u201d means the System Average Interruption Frequency Index which is\nthe number of occasions per year when each customer could, on average,\nexpect to experience an unplanned interruption, calculated as the total number\nof customer interruptions, divided by the total number of connected customers\naveraged over the year and unless otherwise stated, SAIFI excludes\nmomentary interruptions;\n\u201cService Territory\u201d means the entire area of the island of Grand Cayman;\n\u201cT&D Licensee\u201d means Caribbean Utilities Company Ltd. as the exclusive\nholder of the T&D licence for the Service Territory under the Law;\n\u201cTarget\u201d means the quantity or figure that shall provide the benchmark for\nCaribbean Utilities Company Ltd.\u2019s performance;\n\u201cThe Generator\u201d means Caribbean Utilities Company Ltd. as the holder of a\ngeneration licence for the Service Territory under the Law; and\n\u201cZone of Acceptability\u201d means the range above and below the Target that is\nexempt from any reward or penalty, intended to allow for the normal variation\nof the performance measures.\n3.\nInitial Period\n3.\nThe T&D Licensee shall, during the Initial Period, meet with the Technical\nCommittee of the Authority on a quarterly or semi-annual basis, as requested by the\nTechnical Committee, to discuss its performance during the prior period in all areas\nrelated to these standards.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nRule 4\n\nc\nSL 11 of 2012\nPage 7\n\n4.\nRewards and penalties\n4.\n(1) Rewards and penalties shall be excluded from the calculation of changes to the\nbase rate.\n(2) The effect of any rewards or penalties recognized in the applicable financial\nbalances of the T&D Licensee shall be removed before calculating Return on\nRate Base in determining the RCAM annual base rate adjustment.\n5.\nT&D standards and requirements\n5.\n(1) The T&D Licensee shall, for SAIDI and SAIFI during the Initial Period, adopt\nits average historical performance over the past ten years, excluding the\ncalendar years 2005 and 2006, as the Targets.\n(2) The T&D Licensee shall, as it has in the past, measure SAIDI and SAIFI in the\nfuture according to the methodology prescribed in the IEEE Standard No.\n1366 set out in Schedule 2.\n(3) The annual Target for SAIDI and SAIFI shall exclude any year substantially\naffected by an event of force majeure, as defined in the T&D licence and\ngeneration licence, for up to two years, unless otherwise approved by the\nAuthority.\n(4) In paragraph (3), \u2015substantially affected\u2016 means an event which causes\nSAIDI and SAIFI to vary by more than 10% from the Target figure.\n(5) The T&D Licensee shall request and receive the Authority\u2019s approval for such\nexclusions.\n(6) Using this metric during 2011, the SAIDI shall be 5.5 hours per year, and the\nSAIFI Target shall be 4.2 interruptions per year.\n(7) The Zone of Acceptability shall be a range 10% above and below the\nforegoing Targets, rounded to the nearest tenth, on an annual basis.\n(8) During 2011, the ranges shall be \u2014\n(a)\n5.0 to 6.1 hours per year for SAIDI, using the 5.5 hour Target, plus and\nminus 10%, and\n(b) 8 to 4.6 interruptions per year for SAIFI, using the 4.2 Target, plus and\nminus 10%.\n(9) The increments for potential rewards and penalties shall be tenths of an hour\n(six minute increments) for SAIDI, and 0.1 interruptions per year for SAIFI,\neach valued at five thousand dollars per increment, subject to a maximum of\none hundred thousand dollars during the Initial Period.\n(10) There shall be, during the Initial Period, no reward or penalty for better or\nworse performance outside this range.\n(11) The T&D Licensee shall report, with monthly detail, its SAIDI and SAIFI\nperformance on or before 15th January, 15th April, 15th July and 15th October\n\nRule 6\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 8\nSL 11 of 2012\nc\n\nof each year, in conjunction with the quarterly management reports that the\nT&D Licensee shall provide to the Authority.\n(12) The reports shall enable the Authority and the T&D Licensee to determine\nduring the year whether performance is likely to be within or outside the Zone\nof Acceptability for that year and, if it is likely that performance shall be\noutside the Zone of Acceptability, the Authority and the T&D Licensee shall\ndiscuss the reasons for such performance, and if it is expected to be worse than\nthe relevant limit of the Zone of Acceptability, the T&D Licensee shall\npropose and implement corrective actions, which in its judgment will correct\nthe likely deficiency.\n(13) The T&D Licensee shall, in January of each year, immediately following the\nsubmission of its report to the Authority of its prior year\u2019s performance on\nSAIDI and SAIFI, file a report with the Authority indicating whether a reward\nor penalty is due, based on the prior year\u2019s performance.\n(14) Where a reward or penalty is due, the T&D Licensee shall recommend\nchanges to modify monthly consumer billings to reflect any applicable reward\nor penalty, using the T&D Licensee\u2019s forecast of sales to spread those amounts\nevenly over the balance of the year so that the balance of any reward due to or\npenalty imposed on, the T&D Licensee shall be zero at the end of that year.\n(15) A recommendation made under paragraph (14) shall be approved by the\nAuthority prior to its implementation and the T&D Licensee shall, upon\nimplementation, establish a tracking account to monitor the balance in this\naccount.\n(16) Rewards and penalties shall be reflected as a \u2015z factor\u2016 on a consumer\u2019s bill.\n(17) The T&D Licensee shall, in January, in the report to the Authority on its\nannual performance for the prior year, provide information to the Authority on\nthe means by which it intends to meet the T&D standards for the coming year.\n(18) The T&D Licensee shall, within six weeks of the date of commencement of\nthese Rules, provide a recommendation for the Authority\u2019s consideration for a\nperformance standard for T&D losses.\n(19) The T&D Licensee shall, together with the recommendation, provide the\nAuthority with the data for the performance standard for at least the preceding\ntwo years.\n(20) The T&D Licensee shall include this figure in its quarterly performance\nreports to the Authority, with monthly detail, and by 1st November of each\nyear, the T&D Licensee shall justify the level of anticipated T&D losses for\nthe coming year, and provide notice of the dates of any planned T&D outages.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nRule 6\n\nc\nSL 11 of 2012\nPage 9\n\n6.\nCustomer service standards\n6.\n(1) The T&D Licensee shall measure the customer service standards specified\nusing the following figures specified as indicative Targets \u2014\n(a)\nthe time it takes for the T&D Licensee to reconnect customers after an\noutage - a maximum of twenty-four hours;\n(b) connection of new accounts - a maximum of seven calendar days;\n(c)\nreconnection after shutoff for non-payment, once payment is made - a\nmaximum of twenty-four hours; and\n(d) response time to billing complaints - a maximum of ten business days.\n(2) The reconnection standards in paragraphs (a) and (c) shall be measured in\nterms of hours, and the connection and response time standards in\nparagraphs \u2014\n(b) and (d) shall be measured in parts of days.\n(3) The T&D Licensee shall collect comprehensive data to document its\nperformance on these measures of customer service during the Initial Period.\n(4) The Authority shall, upon the compilation and submission of the data to\ndocument performance pursuant to paragraph (3), review the performance to\ndetermine Target, Zone of Acceptability and the level of reward or penalty for\nfuture performance standards.\n(5) There shall be no rewards or penalties until the Authority has determined the\nTarget, Zone of Acceptability, and an appropriate level of reward or penalty.\n(6) The T&D Licensee shall, during the Initial Period, provide quarterly reports\nwith monthly detail on the performance for each of the customer service\nstandards.\n(7) The T&D Licensee shall, within one month of the coming into force of these\nRules, provide the Authority with any data that it has in relation to its\nperformance to date of the measures set out in paragraph (1) for the\nAuthority\u2019s consideration in setting performance standards for these measures.\n(8) The Authority shall, following a review of the performance of the T&D\nLicensee, set standards, including rewards and penalties, for the measures set\nout in paragraph (1) and may, in addition, request the T&D Licensee to\npropose \u2014\n(a)\nTargets, Zones of Acceptability and rewards or penalties for these\nmeasures; and\n(b) additional appropriate performance standards applicable to customer\nservice for the Authority\u2019s consideration and approval.\n(9) The Authority may provide requests for modification to the T&D Licensee on\nits most recent customer satisfaction survey for regulatory purposes, and\n\nRule 7\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 10\nSL 11 of 2012\nc\n\nwithin four weeks of receiving the requests, the T&D Licensee shall submit an\nup-to-date customer satisfaction survey to the Authority for approval, which\nshall be utilized for its 2012 survey.\n(10) The T&D Licensee shall conduct a customer satisfaction survey and provide a\nreport to the Authority on the results every six months, including actions that\nthe Licensee intends to take to maintain and increase satisfaction with its\nservice and to mitigate dissatisfaction revealed by the survey.\n(11) The Authority shall, in addition to the determination of the customer service\nstandards, use the customer satisfaction survey to help determine whether the\nT&D Licensee is taking appropriate actions to provide, maintain and improve\nupon historical levels of customer service.\n7.\nGeneration performance standards and requirements\n7.\n(1) There shall be an annual fuel efficiency standard which shall take into\nconsideration any units that are planned to be added or retired during the year,\nand if the unit is not added or retired as planned or an event involving a unit\noccurs that was not planned, The Generator shall notify the Authority as soon\nas it becomes aware of this change, and shall file with the Authority a revised\nfuel efficiency standard for the overall generation fleet within fifteen business\ndays of such notification.\n(2) The Generator\u2019s Net Fuel Efficiency performance target for 2011 shall be set\nat 18.54 kWh\/IG and The Generator shall \u2014\n(a)\nfor 2011, use a range Zone of Acceptability of 18.03 to 19.14 kWh per\nIG, which is plus-or-minus 3.0% from the 18.58 kWh\/IG target; and\n(b) report its fuel efficiency performance quarterly, and monthly within\nfifteen days of each month\u2019s end, with monthly detail on the performance\nof each generating unit in the fleet.\n(3) The Authority and The Generator shall use the reports required under\nparagraph (2)(b) to determine during the year whether performance is expected\nto be within or outside the Zone of Acceptability for the year.\n(4) The Generator shall indicate in its quarterly reports whether the annual\nperformance for Net Fuel Efficiency is likely to be outside of the Zone of\nAcceptability for the year and if any quarterly report indicates that the yearend target will not likely be met, or upon the Authority\u2019s request, the\nAuthority and The Generator shall discuss the reasons for such anticipated\nperformance.\n(5) Where The Generator is outside of the Zone of Acceptability, The Generator\nshall propose and implement corrective actions, which in its judgment will\ncorrect the likely deficiency, and the Authority and The Generator shall agree\nupon the nature and timing of the corrective actions.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nRule 7\n\nc\nSL 11 of 2012\nPage 11\n\n(6) The T&D Licensee shall, if The Generator\u2019s prior year performance on fuel\nefficiency as shown in the report submitted pursuant to these Rules is outside\nof the applicable Zone of Acceptability, implement any necessary changes in\nconsumer billings to reflect any applicable reward or penalty.\n(7) The T&D Licensee shall, using its forecast of sales figures, determine the\namount of any reward or penalty and subject to Authority approval, spread that\namount evenly over the balance of the year so that the balance of any reward\ndue to or penalty imposed on the T&D Licensee shall be zero at the end of\nthat year.\n(8) A penalty shall only apply if The Generator has failed to implement the agreed\nupon corrective actions.\n(9) Rewards and penalties shall be reflected as a \u2015z factor\u2016 on a consumers\u2019 bill.\n(10) The T&D Licensee shall, upon implementation, establish a tracking account to\nmonitor the balance in an account.\n(11) The Generator shall provide the Authority with a report of the projection of the\nnext year\u2019s expected Net Fuel Efficiency by 15th November of each year.\n(12) The report required under paragraph (11) shall separate the amount required\nfor station usage from station export.\n(13) A reward or penalty shall be calculated annually at one thousand dollars for\nevery 0.01 kWh\/IG of total annual Net Plant Fuel Efficiency outside the Zone\nof Acceptability up to a maximum reward or penalty of one hundred thousand\ndollars per year during the Initial Period.\n(14) The EAF Target shall be 81.9 % and the Zone of Acceptability shall be plus or\nminus 7.5%, or 75.8% to 88.0% in 2011.\n(15) The EAF Target for 2011 shall be calculated based on the average of the actual\nannual total plant EAF for the four years ended 31st December, 2007, 2008,\n2009 and 2010.\n(16) The Target for calendar years 2012 and 2013 shall be based on the rolling\naverage of the actual performance for the previous five years, respectively,\nunless revised by the Authority after the Initial Period.\n(17) The Generator shall, during the Initial Period, include planned outages in the\nmeasure of EAF and in its quarterly reports to the Authority it shall separately\nprovide monthly figures for the elements of the EAF, being planned outages,\nforced outages and unit seasonal derating outages, as defined by ANSI\/IEEE\nStandard 762-1987(R2002) set out in Schedule 1.\n(18) The Generator shall provide the Authority with a projection of its forecasted\nEAF for the coming year by 15th November of each year and shall divide this\nprojection into the elements of the EAF, being planned outages, forced outages\n\nRule 7\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 12\nSL 11 of 2012\nc\n\nand unit seasonal derating outages, as defined by ANSI\/IEEE Standard 7621987(R2002), and justify the level of planned outages to the Authority.\n(19) A penalty or reward amount of five thousand dollars shall be applied for every\n0.2% EAF outside the Zone of Acceptability and for the Initial Period, the\nreward or penalty shall be limited to one hundred thousand dollars and the\nmaximum reward is achieved at 92.0%, or greater, while a maximum penalty\nwill occur at 71.8% or lower being 20 increments of 0.2% outside the Zone of\nAcceptability.\n(20) The Authority shall monitor The Generator\u2019s EAF performance during the\nyear and The Generator shall report to the Authority at the end of each quarter\non whether it expects that The Generator will be within the Zone of\nAcceptability for the entire year.\n(21) The Authority and The Generator shall, if any quarterly report indicates a\ndeficiency in EAF for the year or upon the Authority\u2019s request, discuss the\nreasons for such anticipated performance and The Generator shall propose and\nimplement corrective actions, which in its judgment will correct the likely\ndeficiency, and the Authority and The Generator shall agree upon the nature\nand timing of such corrective actions.\n(22) The Generator shall, when EAF for the prior year is known but no later than\nthe end of January in any year, file a report with the Authority indicating\nwhether any reward or penalty is due to The Generator based on the prior\nyear\u2019s EAF.\n(23) The T&D Licensee shall, subject to Authority approval, in the event that a\nreward or penalty applies, using it\u2019s forecast of sales spread the amount of that\nreward or penalty evenly over the balance of the year, so that the balance of\nany reward due to or penalty imposed on the T&D Licensee shall be zero at\nthe end of that calendar year.\n(24) A penalty shall only apply if The Generator has failed to implement the agreed\nupon corrective actions.\n(25) Rewards and penalties shall be reflected as a \u2015z factor\u2016 on a consumers\u2019 bill.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 13\n\n SCHEDULE 1\n(Regulations 2 and 7(17))\nANSI\/IEEE Std 762-1987(R2002)\n(Revision of ANSI\/IEEE Std 762, originally issued for trial use in 1980)\nIEEE Standard Definitions for Use in Reporting Electric Generating\nUnit Reliability, Availability, and Productivity\n\nSponsor\nPower Systems Engineering Committee of the IEEE Power Engineering Society\n\nReaffirmed March 20, 2002\nIEEE-SA Standards Board\n\nApproved September 19, 1985\nIEEE Standards Board\n\nApproved August 1, 2002\nAmerican National Standards Institute\n\nIEEE-SA Standards Board Approved September 19, 1985 Recognized as an\nAmerican National Standard (ANSI)\n\nIEEE Standards documents are developed within the Technical Committees of\nthe IEEE Societies and the Standards Coordinating Committees of the IEEE\nStandards Board. Members of the committees serve voluntarily and without\ncompensation. They are not necessarily members of the Institute. The standards\ndeveloped within IEEE represent a consensus of the broad expertise on the\nsubject within the Institute as well as those activities outside of IEEE which have\nexpressed an interest in participating in the development of the standard.\n\nUse of an IEEE Standard is wholly voluntary. The existence of an IEEE Standard\ndoes not imply that there are no other ways to produce, test, measure, purchase,\nmarket, or provide other goods and services related to the scope of the IEEE\nStandard. Furthermore, the viewpoint expressed at the time a standard is\napproved and issued is subject to change brought about through developments in\nthe state of the art and comments received from users of the standard. Every\nIEEE Standard is subjected to review at least once every five years for revision or\nreaffirmation. When a document is more than five years old, and has not been\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 14\nSL 11 of 2012\nc\n\nreaffirmed, it is reasonable to conclude that its contents, although still of some\nvalue, do not wholly reflect the present state of the art. Users are cautioned to\ncheck to determine that they have the latest edition of any IEEE Standard.\n\nComments for revision of IEEE Standards are welcome from any interested\nparty, regardless of membership affiliation with IEEE. Suggestions for changes\nin documents should be in the form of a proposed change of text, together with\nappropriate supporting comments.\n\nInterpretations: Occasionally questions may arise regarding the meaning of\nportions of standards as they relate to specific applications. When the need for\ninterpretations is brought to the attention of IEEE, the Institute will initiate action\nto prepare appropriate responses. Since IEEE Standards represent a consensus of\nall concerned interests, it is important to ensure that any interpretation has also\nreceived the concurrence of a balance of interests. For this reason IEEE and the\nmembers of its technical committees are not able to provide an instant response\nto interpretation requests except in those cases where the matter has previously\nreceived formal consideration. Comments on standards and requests for\ninterpretations should be addressed to:\n\nSecretary, IEEE Standards Board 345 East 47th Street\nNew York, NY 10017 USA\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 15\n\nForeword\n\n(This Foreword is not a part of ANSI\/IEEE Std 762-1987, IEEE Standard Definitions for Use in\nReporting Electric Generating Unit Reliability, Availability, and Productivity.)\n\nMeasures of generating unit performance have been defined, recorded, and\nutilized by the electric power industry for over 40 years. Initially, only a few\nterms, such as forced outage rate and scheduled outage rate, were needed. The\nincreased focus on generating unit performance in recent years has caused\nregulatory agencies and the industry to place a greater emphasis on performance\nmeasures.\n\nThese contemporary constraints have amplified the difficulties that evolved from\nhaving generating unit statistics compiled by different organizations to meet their\nown specific needs. In the past these difficulties have included the interpretation\nof data within a given system by an outside agency and the correlation of data\namong the various systems.\n\nThe current problems have made clear the need for a standard to overcome these\ndifficulties by providing terminology and indexes for use in existing data systems\nor in future systems. This standard is directed toward allowing for a meaningful\nexchange of electric generating unit performance data while attempting to retain\nas much of existing systems as possible.\n\nNo attempt is made here to standardize or to recommend methodologies or\nprocedures for the collection of unit performance data. Furthermore, no attempt\nis made here to address the special requirements of electric generating units\nlimited by fuel supplies, resources such as water (hydro), or environmental\nrestrictions. It is expected that the methods used will continue to vary from\nsystem to system according to individual needs. What is attempted is to specify\ncertain common terms and indexes that must be obtainable from each data base\nto provide for a basis of information exchange.\n\nThe task force has attempted to keep the list of terms and indexes as brief as\npossible. Performance cannot be measured by a single parameter, and several\nindexes are required to indicate the ability of a generating unit to produce power\nwhen called upon. The use of any single index to measure the performance of a\nunit or a class of units is misleading. This requirement has necessitated the\ninclusion of all of the terms and indexes as given here.\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 16\nSL 11 of 2012\nc\n\nSome indexes are based on period hours. By use of such a common base, simple\nadditive relationships between various indexes result, and the use of period hours\ngives sets of indexes that sum to 100%, as described in Appendix C. Other\n\nindexes are not based on period hours. For example, in the statistic forced outage\nrate (see 7.16), (service hours forced outage hours) is used as a base because\nforced outage rate is intended to estimate the probability of forced outage during\nthe times when there is no planned or maintenance outage. For other than base\nload service, further modifications are needed to estimate this probability\ncorrectly. It is the intent of the task force to define sufficient data categories\n(states, times, capacity levels) so that suitable indexes for all types of units can be\ncalculated.\n\nIt should be noted that even the use of all the indexes and terms cannot identify\nthe underlying and sometimes compelling reasons for lost performance.\n\nThis standard was prepared by the Power Plant Productivity Definitions Task\nForce of the Applications of Probability Methods Subcommittee of the Power\nSystems Engineering Committee, whose members were as follows:\n\nThe following persons were on the balloting committee that approved this\ndocument for submission to the IEEE Standards Board:\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 17\n\nWhen the IEEE Standards Board approved this standard on September 19, 1985,\nit had the following membership:\n\nThe task force wishes to dedicate this work to the memory of Veazey M.Cook, a\npioneer in the application of generating unit outage data in system planning\nstudies. The format and many of the terms used in this standard can be traced to\nVeazey Cook's work.\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 18\nSL 11 of 2012\nc\n\nCLAUSE\nPAGE\n1.\nPurpose. .................................................................................................... 1\n2.\nScope. ....................................................................................................... 1\n3.\nUnit States. ................................................................................................ 1\n3.1\nActive ........................................................................................................ 2\n3.2\nDeactivated Shutdown .............................................................................. 5\n4.\nCapacity Terms ......................................................................................... 5\n4.1\nMaximum Capacity (MC). ........................................................................ 5\n4.2\nDependable Capacity ................................................................................ 5\n4.3\nAvailable Capacity .................................................................................... 6\n4.4\nSeasonal Derating ..................................................................................... 6\n4.5\nUnit Derating ............................................................................................ 6\n4.6\nPlanned Derating ...................................................................................... 6\n4.7\nUnplanned Derating .................................................................................. 6\n4.8\nInstalled Nameplate Capacity ................................................................... 6\n5.\nTime Designations and Dates ................................................................... 7\n5.1\nAvailable Hours (AH) ............................................................................... 7\n5.2\nService Hours (SH) ................................................................................... 7\n5.3\nReserve Shutdown Hours (RSH) .............................................................. 7\n5.4\nUnavailable Hours (UH) ........................................................................... 7\n5.5\nPlanned Outage Hours (POH) .................................................................. 7\n5.6\nUnplanned Outage Hours (UOH) ............................................................. 8\n5.7\nForced Outage Hours (FOH) .................................................................... 8\n5.8\nMaintenance Outage Hours (MOH) ......................................................... 8\n5.9\nDeactivated Shutdown Hours (DSH) ........................................................ 8\n5.10\nPeriod Hours (PH) .................................................................................... 8\n5.11\nUnit Derated Hours (UNDH) .................................................................... 8\n5.12\nPlanned Derated Hours (PDH) ................................................................. 8\n5.13\nUnplanned Derated Hours (UDH) ............................................................ 8\n5.14\nForced Derated Hours (FDH) ................................................................... 9\n5.15\nMaintenance Derated Hours (MDH) ........................................................ 9\n5.16\nSeasonal Derated Hours (SDH) ................................................................ 9\n5.17\nEquivalent Hours (E) ................................................................................ 9\n5.18\nDeactivation Date ................................................................................... 10\n5.19\nReactivation Date .................................................................................... 10\n6.\nEnergy Terms.......................................................................................... 10\n6.1\nActual Generation (AAG) ....................................................................... 10\n6.2\nMaximum Generation (MG) ................................................................... 10\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 19\n\n6.3\nAvailable Generation (AG) ..................................................................... 10\n6.4\nUnavailable Generation (UG) ................................................................. 10\n6.5\nSeasonal Unavailable Generation (SUG) ................................................ 11\n\nCLAUSE ....................................................................................................... PAGE\n6.6\nReserve Generation (RG) ........................................................................ 11\n6.7\nDerated Generation (DG) ........................................................................ 11\n7.\nPerformance Indexes. .............................................................................. 11\n7.1\nPlanned Outage Factor (POF) ................................................................. 11\n7.2\nUnplanned Outage Factor (UOF) ............................................................ 11\n7.3\nForced Outage Factor (FOF). .................................................................. 11\n7.4\nMaintenance Outage Factor (MOF). ....................................................... 12\n7.5\nUnavailability Factor (UF) ...................................................................... 12\n7.6\nAvailability Factor (AF). ......................................................................... 12\n7.7\nService Factor (SF) ................................................................................. 12\n7.8\nSeasonal Derating Factor (SDF) ............................................................. 12\n7.9\nUnit Derating Factor (UDF) .................................................................... 12\n7.10\nEquivalent Unavailability Factor (EUF) ................................................. 13\n7.11\nEquivalent Availability Factor (EAF). .................................................... 13\n7.12\nGross Capacity Factor (GCF) ................................................................. 13\n7.13\nNet Capacity Factor (NCF) ..................................................................... 13\n7.14\nGross Output Factor (GOF) .................................................................... 14\n7.15\nNet Output Factor (NOF) ........................................................................ 14\n7.16\nForced Outage Rate (FOR) ..................................................................... 14\n7.17\nEquivalent Forced Outage Rate (EFOR) ................................................. 14\n7.18\nMean Service Time to Outage................................................................. 14\n7.19\nMean Outage Duration ............................................................................ 15\n7.20\nStarting Reliability (SR) .......................................................................... 15\n7.21\nCycling Rate (CR) ................................................................................... 15\nAnnex A Correlation Between Unit State and Capacity Derating Definitions\nin This Standard and Those Formerly Used by the Industry (Informative).16\nAnnex B  Transitions Between States (Informative) ........................................... 17\nAnnex C Relationships Between Period-Hour-Based Performance Indexes\n(Informative) ........................................................................................................ 19\nAnnex D Glossary of Terms and Abbreviations (Informative) ............................ 23\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 20\nSL 11 of 2012\nc\n\nAn American National Standard\n\nIEEE Standard Definitions for Use in Reporting Electric Generating Unit\nReliability, Availability, and Productivity\n\n1.\nPurpose\nThis standard is intended to aid the electric power industry in reporting and\nevaluating electric generating unit reliability, availability, and productivity. It\nwas developed to overcome present difficulties in the interpretation of electric\ngenerating unit performance data from various systems and to facilitate\ncomparisons among different systems. The standard should also make possible\nthe future exchange o meaningful data among systems in North America and\nthroughout the world.\n\n2.\nScope\nThis document standardizes terminology and indexes for reporting electric\ngenerating unit reliability, availability, and productivity performance measures.\nA generating unit includes all equipment up to the high-voltage terminal of the\ngenerator step-up transformer. Reliability in this standard encompasses measures\nof the ability of generating units to perform their intended function. Availability\nmeasures are concerned with the fraction of time a unit is capable of providing\nservice, and account for outage frequency and duration. Productivity measures\nare concerned with the total power produced by a plant with respect to its\npotential power production. Therefore, productivity measures consider\nmagnitude of outage as well as frequency and duration of outage.\n\nNOTE \u2014 This standard was developed for application at the unit level; the definitions are\napplicable below the unit level in most cases. There are some exceptions, however, such as the\ndefinition of in service, which applies only at the unit level. Because of these exceptions, care\nshould be taken when using this standard below the unit level.\n\n3.\nUnit States\nA unit state is a particular unit condition that is important for purposes of\ncollecting data on performance.\n\nNOTE \u2014 The state definitions are related as shown in Fig 1. The transitions between states are\ndescribed in Appendix B. The correlation between these definitions and those in use by the industry\nis shown in Appendix A.\n\n3.1 Active\nThe state in which a unit is in the population of units being reported on.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 21\n\nNOTE \u2014 A unit generally enters the active state on its service date.\n\n3.1.1 Available\nThe state in which a unit is capable of providing service, whether or not it is\nactually in service and regardless of the capacity level that can be provided.\n\n3.1.1.1 In Service\nThe state in which a unit is electrically connected to the system.\n\n3.1.1.2 Reserve Shutdown\nThe state in which a unit is available but not in service.\n\nNOTE \u2014 This is sometimes referred to as economy shutdown.\n\n3.1.2 Unavailable\nThe state in which a unit is not capable of operation because of operational or\nequipment failures, external restrictions, testing, work being performed, or some\nadverse condition. The unavailable state persists until the unit is made available\nfor operation, either by being synchronized to the system (in-service state) or by\nbeing placed in the reserve shutdown state.\n\n3.1.2.1 Planned Outage\nThe state in which a unit is unavailable due to inspection, testing, nuclear\nrefueling, or overhaul. A planned outage is scheduled well in advance.\n\n3.1.2.1.1 Basic Planned Outage\nThe planned outage state that is originally scheduled and of a predetermined\nduration.\n\n3.1.2.1.2 Extended Planned Outage\nThe planned outage state that is the extension of the basic planned outage beyond\nits predetermined duration.\n\nNOTE \u2014 Extended planned outage applies only when planned work exceeds predetermined\nduration. The extension, due to a condition discovered during the planned outage that has forced\nthe extension of the planned outage, is to be classified as Class 1 unplanned outage (see 3.1.2.2.2).\nStartup failure would result in Class 0 unplanned outage (see 3.1.2.2.1).\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 22\nSL 11 of 2012\nc\n\nFigure 1\u2014Relation Between Unit States\n\n3.1.2.2 Unplanned Outage\nThe state in which a unit is unavailable but is not in the planned outage state.\nNOTES:\n1 \u2014 When an unplanned outage is initiated, the outage is to be classified according to one\nof five classes, as defined in 3.1.2.2.1 through 3.1.2.2.5. Unplanned outage Class 0 applies to a\nstart-up failure and Class 1 applies to a condition requiring immediate outage. Also, unplanned\noutage starts when planned outage ends but is extended due to unplanned work. Classes 2, 3, and 4\napply to outages where some delay is possible in time of removal of the unit from service. The\nclass (2, 3, or 4) of outage is to be determined by the amount of delay that can be exercised in the\ntime of removal of the unit. The class of outageis not made more urgent if the time of removal is\nadvanced due to favorable conditions of system reserves or availability of replacement capacity for\nthe predicted duration of the outage. However, outage starts when the unit is removed from service\nor is declared unavailable when it is not in service.\n\n2 \u2014 During the time the unit is in the unplanned outage state, the outage class is determined by the\noutage class that initiates the state.\n\n3 \u2014 In some cases, the opportunity exists during unplanned outages to perform some of the repairs\nor maintenance that would have been performed during the next planned outage. If the additional\nwork extends the outage beyond that required for the unplanned outage, the remaining outage\nshould be reported as a planned outage.\n\n4 \u2014 Unlike planned outages, unplanned outages do not have a fixed duration that can be estimated\neach year.\n\n3.1.2.2.1 Class 0 Unplanned Outage (Starting Failure)\nAn outage that results from the unsuccessful attempt to place the unit in service\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 23\n\n(see 3.1.3.1).\n\n3.1.2.2.2 Class 1 Unplanned Outage (Immediate)\nAn outage that requires immediate removal from the existing state.\n\nNOTE \u2014 A Class 1 unplanned outage can be initiated from either the in-service or reserve\nshutdown states. A Class 1 unplanned outage can also be initiated from the planned outage state.\nSee Note in 3.1.2.1.2.\n\n3.1.2.2.3 Class 2 Unplanned Outage (Delayed)\nAn outage that does not require immediate removal from the in-service state but\nrequires removal within 6 h.\n\n3.1.2.2.4 Class 3 Unplanned Outage (Postponed)\nAn outage that can be postponed beyond 6 h but requires that a unit be removed\nfrom the in-service state before the end of the next weekend.\n\nNOTE \u2014 Classes 2 and 3 can only be initiated from the inservice state.\n\n3.1.2.2.5 Class 4 Unplanned Outage (Deferred)\nAn outage that will allow a unit outage to be deferred beyond the end of the next\nweekend but requires that a unit be removed from the available state before the\nnext planned outage.\n\n3.1.2.3 Repair Urgency\nWhen a planned or unplanned outage is initiated, the urgency with which repair\nactivities are carried out is classified according to one of three classes as defined\nin 3.1.2.3.1 through 3.1.2.3.3.\n\n3.1.2.3.1 Maximum Effort\nRepairs were accomplished in the shortest possible time.\n\n3.1.2.3.2 Normal Effort\nRepairs were carried out with normal repair crews working normal shifts.\n\n3.1.2.3.3 Low-Priority Effort\nRepairs were carried out with less than a normal effort.\n\n3.1.3 Starting Attempt\nThe action to bring a unit from shutdown to the in-service state. Repeated\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 24\nSL 11 of 2012\nc\n\ninitiations of the starting sequence without accomplishing corrective repairs are\ncounted as a single attempt.\n\n3.1.3.1 Starting Failure\nThe inability to bring a unit from some unavailable state or reserve shutdown\nstate to the in-service state within a specified period. The specified period may be\ndifferent for individual units. Repeated failures within the specified starting\nperiod are to be counted as a single starting failure.\n\n3.1.3.2 Starting Success\nThe occurrence of bringing a unit from some unavailable state or the reserve\nshutdown state to the in-service state within a specified period. The specified\nperiod may be different for individual units.\n\n3.2 Deactivated Shutdown\nThe state in which a unit is unavailable for service for an extended period of time\nbecause of its removal for economy or reasons not related to the equipment.\nUnder this condition, a unit generally requires weeks of preparation to make it\navailable.\n\n4.\nCapacity Terms\nTerms that involve capacity can be expressed as gross or net quantities.\n\nNOTE \u2014 The capacity definitions are related as shown in Fig 2. The correlation between the\ncapacity-derating definitions in this section and partial-outage definitions in use by industry is\nshown in Appendix A.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 25\n\nFigure 2\u2014Unit Capacity Levels\n\n4.1 Maximum Capacity (MC)\nThe maximum capacity that a unit can sustain over a specified period of time.\nThe maximum capacity can be expressed as gross maximum capacity (GMC) or\nnet maximum capacity (NMC). To establish this capacity, formal demonstration\nis required. The test should be repeated periodically. This demonstrated capacity\nlevel shall be corrected to generating conditions for which there should be\nminimum ambient restriction. When a demonstration test has not been conducted,\nthe estimated maximum capacity of the unit shall be used.\n\n4.2 Dependable Capacity\nThe maximum capacity, modified for ambient limitations for a specified period\nof time, such as a month or a season.\n\n4.3 Available Capacity\nThe dependable capacity, modified for equipment limitation at any time.\n\n4.4 Seasonal Derating\nThe difference between maximum capacity and dependable capacity.\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 26\nSL 11 of 2012\nc\n\n4.5 Unit Derating\nThe difference between dependable capacity and available capacity.\n\n4.6 Planned Derating\nThat portion of the unit derating that is scheduled well in advance.\n\n4.6.1 Basic Planned Derating\nThe planned derating that is originally scheduled and of predetermined duration.\n\n4.6.2 Extended Planned Derating\nThe planned derating that is the extension of the basic planned derating beyond\nits predetermined duration.\n\n4.7 Unplanned Derating\nThat portion of the unit derating that is not a planned derating. Unplanned\nderating events are classified according to the urgency with which the derating\nneeds to be initiated, as defined in 4.7.1 through 4.7.4.\n\n4.7.1 Unplanned Derating, Class 1 (Immediate)\nA derating that requires an immediate action for the reduction of capacity.\n\n4.7.2 Unplanned Derating, Class 2 (Delayed)\nA derating that does not require an immediate reduction of capacity, but requires\na reduction of capacity within 6 h.\n\n4.7.3 Unplanned Derating, Class 3 (Postponed)\nA derating that can be postponed beyond 6 h, but requires a reduction of capacity\nbefore the end of the next weekend.\n\n4.7.4 Unplanned Derating, Class 4 (Deferred)\nA derating that can be deferred beyond the end of the next weekend, but requires\na reduction of capacity before the next planned outage.\n\n4.8 Installed Nameplate Capacity\nThe full-load continuous gross capacity of a unit under specified conditions, as\ncalculated from the electric generator nameplate based on the rated power factor.\nNOTE \u2014 The nameplate rating of the electric generator may not be indicative of the unit maximum\nor dependable capacity, since some other item or equipment (such as the turbine) may limit unit\noutput.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 27\n\n5.\nTime Designations and Dates\n\nNOTE \u2014 The time spent in the various unit states defined in Section 3 is defined in 5.1 through\n5.10. See Fig 3. In 5.11 through 5.16, the time a unit was subject to the various categories of unit\nderating defined in Section 4. is defined. Derated time is accumulated only during the available,\ninservice, and reserve shutdown states.\n\nFigure 3\u2014Time Spent in Various Unit States\n\n5.1 Available Hours (AH)\nThe number of hours a unit was in the available state.\n\nNOTE \u2014 Available hours is the sum of service hours and reserve shutdown hours, or may be\ncomputed from period hours minus unavailable hours (see 5.4).\n\n5.2 Service Hours (SH)\nThe number of hours a unit was in the in-service state.\n\n5.3 Reserve Shutdown Hours (RSH)\nThe number of hours a unit was in the reserve shutdown state.\n\n5.4 Unavailable Hours (UH)\nThe number of hours a unit was in the unavailable state.\n\nNOTE \u2014 Unavailable hours are the sum of planned outage hours and unplanned outage hours, or\nthe sum of planned outage hours, forced outage hours, and maintenance outage hours.\n\n5.5 Planned Outage Hours (POH)\nThe number of hours a unit was in the basic or extended planned outage state.\n\n5.6 Unplanned Outage Hours (UOH)\nThe number of hours a unit was in a Class 0, 1, 2, 3, or 4 unplanned outage state.\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 28\nSL 11 of 2012\nc\n\n5.7 Forced Outage Hours (FOH)\nThe number of hours a unit was in a Class 0, 1, 2, or 3 unplanned outage state.\n\n5.8 Maintenance Outage Hours (MOH)\nThe number of hours a unit was in a Class 4 unplanned outage state.\n\n5.9 Deactivated Shutdown Hours (DSH)\nThe number of hours a unit was in the deactivated shutdown state.\n\n5.10 Period Hours (PH)\nThe number of hours a unit was in the active state.\n\n5.11 Unit Derated Hours (UNDH)\nThe available hours during which a unit derating was in effect.\n\n5.11.1 In-Service Unit Derated Hours (IUNDH)\nThe in-service hours during which a unit derating was in effect.\n\n5.11.2 Reserve Shutdown Unit Derated Hours (RSUNDH)\nThe reserve shutdown hours during which a unit derating was in effect.\n\n5.12 Planned Derated Hours (PDH)\nThe available hours during which a basic or extended planned derating was in\neffect.\n\n5.12.1 In Service PlAnned Derated Hours (IPDH)\nThe in-service hours during which a basic or extended planned derating was in\neffect.\n\n5.12.2 Reserve Shutdown Planned Derated Hours (RSPDH)\nThe reserve shutdown hours during which a basic or extended planned derating\nwas in effect.\n\n5.13 Unplanned Derated Hours (UDH)\nThe available hours during which an unplanned derating was in effect.\n\n5.13.1 In-Service Unplanned Derated Hours (IUDH)\nThe in-service hours during which an unplanned derating was in effect.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 29\n\n5.13.2 Reserve Shutdown Unplanned Derated Hours (RSUDH)\nThe reserve shutdown hours during which an unplanned derating was in effect.\n\n5.14 Forced Derated Hours (FDH)\nThe available hours during which a Class 1, 2, or 3 unplanned derating was in\neffect.\n\n5.14.1 In-Service Forced Derated Hours (IFDH)\nThe in-service hours during which a Class 1, 2, or 3 unplanned derating was in\neffect.\n\n5.14.2 Reserve Shutdown Forced Derated Hours (RSFDH)\nThe reserve shutdown hours during which a Class 1, 2, or 3 unplanned derating\nwas in effect.\n\n5.15 Maintenance Derated Hours (MDH)\nThe available hours during which a Class 4 unplanned derating was in effect.\n\n5.15.1 In-Service Maintenance Derated Hours (IMDH)\nThe in-service hours during which a Class 4 unplanned derating was in effect.\n\n5.15.2 Reserve Shutdown Maintenance Derated Hours (RSMDH)\nThe reserve shutdown hours during which a Class 4 unplanned derating was in\neffect.\n\n5.16 Seasonal Derated Hours (SDH)\nThe available hours during which a seasonal derating was in effect.\n\n5.17 Equivalent Hours (E)\nThe number of hours a unit was in a time category involving unit derating,\nexpressed as equivalent hours of full outage at maximum capacity. Both unit\nderating and maximum capacity shall be expressed on a consistent basis, gross or\nnet. Equivalent hours can be calculated for each of the time categories in\n5.11through 5.16. The symbol designation for the equivalent hours is formed by\nadding an E in front of the symbol for the corresponding time designation (for\nexample, equivalent unit derated hours is designated EUNDH). Equivalent hours\ncan be calculated from the following equation:\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 30\nSL 11 of 2012\nc\n\nwhere\n\nE( ) = equivalent hours in the time category represented by parentheses, which\ncan be any one of the time categories in 5.11 through 5.16\nD( )i = the derating for the time category shown in parentheses, after the ith\nchange in either available capacity (unit deratings) or dependable capacity\n(seasonal deratings)\n\nNOTE \u2014 In order to apportion equivalent hours among the various time categories, appropriate\nground rules shall be established in the reporting system so that after each change in either\navailable capacity or dependable capacity, the sum of all subcategories of unit derating is equal to\nthe unit derating.\n\nTi = the number of hours accumulated in the time category of interest between\nthe ith and the (i + 1)th change in either available capacity (unit deratings) or\ndependable capacity (seasonal deratings)\n\nMC = maximum capacity\n\n5.18 Deactivation Date\nThe date a unit was placed into the deactivated shutdown state.\n\n5.19 Reactivation Date\nThe date a unit was returned to the active state from the deactivated shutdown\nstate.\n\n6.\nEnergy Terms\nSimilar to capacity terms, energy terms can be expressed as gross or net\nquantities.\n\n6.1 Actual Generation (AAG)\nThe energy that was generated by a unit in a given period. Actual generation can\nbe expressed as gross actual generation (GAAG) or net actual generation\n(NAAG).\n\n6.2 Maximum Generation (MG)\nThe energy that could have been produced by a unit in a given period of time if\noperated continuously at maximum capacity. Maximum generation can be\nexpressed as gross maximum generation (GMG) or net maximum generation\n(NMG).\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 31\n\nMG = period hours \u00b7 maximum capacity = PH \u00b7 MC GMG = PH \u00b7 GMC\nNMG = PH \u00b7 NMC\n\n6.3 Available Generation (AG)\nThe energy that could have been generated by a unit in a given period if operated\ncontinuously at its available capacity.\n\n6.4 Unavailable Generation (UG)\nThe difference between the energy that would have been generated if operating\ncontinuously at dependable capacity and the energy that would have been\ngenerated if operating continuously at available capacity. This is the energy that\ncould not be generated by a unit due to planned and unplanned outages and unit\nderatings.\n\nUG = (planned outage hours + unplanned outage hours + equivalent unit derated\nhours) \u00b7 maximum capacity = (POH + UOH + EUNDH) \u00b7 MC\n\n6.5 Seasonal Unavailable Generation (SUG)\nThe difference between the energy that would have been generated if operating\ncontinuously at maximum capacity and the energy that would have been\ngenerated if operating continuously at dependable capacity, calculated only\nduring the time the unit was in the available state.\n\nSUG = equivalent seasonal derated hours \u00b7 maximum capacity = ESDH \u00b7 MC\n\n6.6 Reserve Generation (RG)\nThe energy that a unit could have produced in a given period but did not, because\nit was not required by the system. This is the difference between available\ngeneration and actual generation.\n\n6.7 Derated Generation (DG)\nThe generation that was not available due to unit deratings.\n\nDG = equivalent unit derated hours \u00b7 maximum capacity = EUNDH \u00b7 MC\n\n7.\nPerformance Indexes\nAppendix C discusses the relationships among the performance indexes that are\nbased on period hours.\n\nNOTE \u2014 All per unit performance indexes are expressed in percentage.\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 32\nSL 11 of 2012\nc\n\n7.1 Planned Outage Factor (POF)\n\n7.2 Unplanned Outage Factor (UOF)\n\n7.3 Forced Outage Factor (FOF)\n\n7.4 Maintenance Outage Factor (MOF)\n\n7.5 Unavailability Factor (UF)\n\n7.6 Availability Factor (AF)\n\n7.7 Service Factor (SF)\n\n7.8 Seasonal Derating Factor (SDF)\nThe fraction of maximum generation that could not be produced due to seasonal\nderatings:\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 33\n\n7.9 Unit Derating Factor (UDF)\nThe fraction of maximum generation that could not be produced due to unit\nderatings:\n\n7.10 Equivalent Unavailability Factor (EUF)\nThe fraction of maximum generation that could not be produced due to unit\nderatings and planned and unplanned outages:\n\n7.11 Equivalent Availability Factor (EAF)\nThe fraction of maximum generation that could be provided if limited only by\noutages and deratings:\n\n7.12 Gross Capacity Factor (GCF)\n\n7.13 Net Capacity Factor (NCF)\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 34\nSL 11 of 2012\nc\n\nNOTE \u2014 Net capacity factor calculated using this equation can be negative during a period when\nthe unit is shutdown. For meaningful pooling of data on several units, net capacity factor can be\ndefined to be zero when the unit is shutdown.\n\n7.14 Gross Output Factor (GOF)\n\n7.15 Net Output Factor (NOF)\n\n7.16 Forced Outage Rate (FOR)\n\n7.17 Equivalent Forced Outage Rate (EFOR)\n\n7.18 Mean Service Time to Outage\n\n7.18.1 Mean Service Time to Forced Outage (MSTFO)\n\n7.18.2 Mean Service Time to Maintenance Outage (MSTMO)\n\n7.18.3 Mean Service Time to Planned Outage (MSTPO)\n\nNOTE \u2014 In 7.18.1, only forced outages occurring from in-service state are considered. The  name\nfor  the  index  could  be  \u2015mean  service  time  to  in-service  forced  outage.\u2016 However, for\nsimplicity in-service is not included in the name. This note is also applicable to 7.18.2 and 7.18.3.\n\nIndexes similar to 7.18.1, 7.18.2, and 7.18.3 can also be calculated for outages that occur during\nreserve shutdown state.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 35\n\n7.19 Mean Outage Duration\n\n7.19.1 Mean Forced Outage Duration (MFOD)\n\n7.19.2 Mean Maintenance Outage Duration (MMOD)\n\n7.19.3 Mean Planned Outage Duration (MPOD)\n\nNOTE \u2014 Similar to 7.18, outage hours and number of outages in 7.19 include outages  that occur\nfrom in-service state only.\n\n7.20 Starting Reliability (SR)\n\n7.21 Cycling Rate (CR)\n\nAnnex A\n\nCorrelation Between Unit State and Capacity Derating Definitions in This Standard\nand Those Formerly Used by the Industry\n\n(Informative)\n\n(These Appendixes are not a part of ANSI\/IEEE Std 762-1987, EEE Standard Definitions for Use\nin Reporting Electric Generating Unit Reliability, Availability, and Productivity.)\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 36\nSL 11 of 2012\nc\n\nAnnex B\n\nTransitions Between States (Informative)\nSection 3 defines three primary unit states:\n1) Available\n2) Unavailable\n3) Deactivated shutdown\n\nThese three states are mutually exclusive and exhaustive. A unit will be in\nexactly one of these states at all times. Thus, these states divide calendar time\ninto nonoverlapping segments. The available and unavailable states are each\ndivided into additional, mutually exclusive states. The available state is divided\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 37\n\ninto in- service and reserve shutdown states, and the unavailable state is divided\ninto planned and unplanned outage states. These four secondary states, together\nwith the deactivated shutdown state, also form a mutually exclusive and\nexhaustive set. Finally, the planned outage state is divided into basic and\nextended planned outage states. Also, the unplanned outage state is divided into\nfive outage classes, according to the urgency with which the outage is initiated.\nLike the other states, the unplanned outage classes are defined to be mutually\nexclusive. The unit state structure can also be described by starting with the\nlowest level states. Thus, there are ten basic states:\n\n1) In service\n2) Reserve shutdown\n3) Basic planned outage\n4) Extended planned outage\n5) Class 0 unplanned outage\n6) Class 1 unplanned outage\n7) Class 2 unplanned outage\n8) Class 3 unplanned outage\n9) Class 4 unplanned outage\n10) Deactivated shutdown\n\nThese basic states are defined to be mutually exclusive and exhaustive. By\ngrouping various subsets of the basic states together, each of the secondary and\nprimary states can be formed.\n\nOnce a unit is in a state, it remains in that state until a transition event occurs that\ncauses the unit to move to another state. The possible transition events can be\nshown by use of a state transition matrix. Figure B.1 shows a state transition\nmatrix for the ten basic states. The left side of the matrix shows the possible unit\nstates before a transition event. The top row of the matrix shows the (same)\npossible unit states after a transition event. Thus, each (nondiagonal) element of\nthe matrix can be used to describe a transition event from the state on the left to\nthe top state. Figure B.1 shows the transition events that are possible according to\nthe definitions in Section 3. The elements denoted by \"x\" are not possible.\n\nBy looking on a particular row of Fig B.1, the possible transition events that can\nterminate a state can be seen. By looking at a particular column of Fig the\npossible transition events that can initiate a state can be seen.\n\nDetailed definitions for the transition events in Fig have not been included in this\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 38\nSL 11 of 2012\nc\n\nstandard. However, in actual reporting generating unit performance, it is the\ntransition event occurrence times that are in fact reported, from which the state\nduration times are then calculated. Therefore, the reporting instructions that\nimplement the collection of unit performance data should give careful\n\nconsideration to defining precisely and clearly the exact point in time at which\nthe various transitions take place.\n\nFigure B.1\u2014State Transition Matrix\n\nAnnex C\n\nRelationships Between Period-Hour-Based Performance Indexes (Informative)\nFor purposes of measuring and improving the performance of individual\ngenerating units, it is common to emphasize measures that are based on period\nhours. The performance indexes in Section 7 provide a unified set of period-\nhourbased indexes (called factors), as follows:\n\nAF = availability factor UF = unavailability factor\nEAF = equivalent availability factor EUF = equivalent unavailability factor FOF\n= forced outage factor\nMOF = maintenance outage factor\nUOF = unplanned outage factor = FOF + MOF\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 39\n\nPOF = planned outage factor SDF = seasonal derating factor UDF = unit derating\nfactor\n\nThese indexes are unified in the sense that they are related in the following ways:\n\nEquation C1 shows that equivalent availability can be obtained by subtracting the\nunit derating factor and the seasonal derating factor from the availability factor.\n\nEquation C2 shows that equivalent unavailability can be obtained by adding the\nunit derating factor, but not the seasonal derating factor, to the unavailability\nfactor.\n\nEquation C3 shows that the availability and unavailability factors add to 100%.\n\nEquation C4 shows that the equivalent availability, equivalent unavailability, and\nseasonal derating factor also add to 100%. However, equivalent availability and\nequivalent unavailability alone do not, in general, add to 100%, because this sum\ndoes not include the effect of seasonal deratings.\n\nEquation C5 shows that the unavailability factor is the sum of the planned and\nunplanned outage factors (unplanned outage factor is the sum of maintenance\noutage factor and forced outage factor).\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 40\nSL 11 of 2012\nc\n\nSubstituting Eq C5 into Eq C2 produces Eq C6, which shows that equivalent\nunavailability is the sum of the planned and unplanned outage factors and the\nunit derating factor.\n\nSubstituting Eq C6 into Eq C4 produces Eq C7. This last equation shows that\nthere are four recognized sources of energy loss: planned outages (full),\nunplanned outages (full), unit deratings, and seasonal deratings. Each energy loss\nis represented by a separate index: POF, UOF, UDF, and SDF, respectively.\nThese indexes are defined in such a way as to be additive. Therefore, the total per\nunit energy loss is the sum of the four indexes, and the remaining per unit energy\nnot lost is called equivalent availability factor (EAF).\n\nIn order for the four energy loss indexes to be additive, as in Eq C7, it is\nnecessary that the capacity loss due to each source be separated. This means, for\nexample, that a unit cannot simultaneously be subject to full outage and unit\nderating.\n\nSimilarly, a unit cannot simultaneously be subject to both seasonal derating and\nfull outage. In order to achieve nonoverlapping energy definitions, the task force\nagreed to assign full (maximum) unit capacity to the full outage state. This means\nthat both unit deratings and seasonal deratings are considered to end when a full\noutage starts, as far as the calculation of the unit derating factor (UDF) and the\nseasonal derating factor (SDF) are concerned.\n\nIn order to further illustrate the relationship between the period-hour-based\nperformance indexes, Fig C1 shows capacity versus time diagram (all capacity\nvalues must be either gross or net). The total height of the diagram is maximum\ncapacity (MC), and the total width of the diagram is period hours (PH). Thus, the\ntotal area Y of the diagram is\n\nY = MC \u00b7 PH\n\nThis is the total megawatthour (MWh) of energy that could have been generated\nduring the period if operating continuously at MC.\n\nThe area Y is divided into several vertical segments by the various time\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 41\n\ndesignations in Section 5. The vertical segments involving available hours are\nfurther divided into sections to show the energy associated with seasonal\nderating, unit derating, discretionary reduction, and actual generation. All of the\nperformance factors in Section 7 that are based on period hours can be expressed\nas simple ratios of the areas in Fig C.1 as follows:\n\nFigure C.1\u2014Relation Between Time and Energy Terms\n\nTime Indexes\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 42\nSL 11 of 2012\nc\n\nEnergy Indexes\n\nNOTE \u2014 Capacity factor is GCF or NCF depending on gross or net basis used for capacity.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 1\n\nc\nSL 11 of 2012\nPage 43\n\nAnnex D\n\nGlossary of Terms and Abbreviations (Informative)\n\nSCHEDULE 1\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 44\nSL 11 of 2012\nc\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 45\n\nSCHEDULE 2\n(Regulation 5(2))\n1366TM\nIEEE Guide for Electric Power Distribution Reliability Indices\n\nIEEE Power Engineering Society\n\nSponsored by the Transmission and Distribution Committee\n\nIEEE Guide for Electric Power Distribution Reliability Indices\n\nSponsor\nTransmission and Distribution Committee\nof the\nIEEE Power Engineering Society\n\nApproved 26 April 2004\nAmerican National Standards Institute\n\nApproved 10 December 2003\nIEEE-SA Standards Board\n\nGrateful acknowledgment is made to the Edison Electric Institute for the\npermission to use the following source material:\n\nPages 28\u201330 of the June 2001, Edison Electric Institute 2000 Reliability Report.\n\nAbstract: Distribution reliability indices and factors that affect their calculations\nare defined in this guide. The indices are intended to apply to distribution\nsystems, substations, circuits, and defined regions.\nKeywords: circuits, distribution reliability indices, distribution systems, electric\npower, reliability indices\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 46\nSL 11 of 2012\nc\n\nIntroduction\n\n(This introduction is not part of IEEE Std 1366-2003, IEEE Guide for Electric Power Distribution\nReliability Indices.)\n\nThis Guide has been updated to clarify existing definitions and to introduce a\nstatistically based definition for classification of major event days. The working\ngroup created a methodology, 2.5 Beta Method, for determination of major event\ndays. Once days are classified as normal or major event days, appropriate\nanalysis and reporting can be conducted. After this document is balloted, the\nworking group will continue to investigate the major event definition by\nreviewing catastrophic events and days with zero events to determine if\nenhancements are warranted.\n\nPatents\nAttention is called to the possibility that implementation of this standard may\nrequire use of subject matter covered by patent rights. By publication of this\nstandard, no position is taken with respect to the existence or validity of any\npatent rights in connection therewith. The IEEE shall not be responsible for\nidentifying patents for which license may be required by an IEEE standard or for\nconducting inquiries into the legal validity or scope of those patents that are\nbrought to its attention.\n\nNotice to users Errata\nErrata, if any, for this and all other standards can be accessed at the following\nURL: http:\/\/standards.ieee.org\/reading\/ieee\/updates\/errata\/index.html. Users are\nencouraged to check this URL for errata periodically.\n\nInterpretations\n\nCurrent interpretations can be accessed at the following URL:\nhttp:\/\/standards.ieee.org\/reading\/ieee\/interp\/index.html.\n\nParticipants\nAt the time this standard was completed, the Working Group on System Design\nhad the following membership:\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 47\n\nThe following members of the balloting committee voted on this standard.\nBalloters may have voted for approval, disapproval, or abstention.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 48\nSL 11 of 2012\nc\n\nWhen the IEEE-SA Standards Board approved this standard on 10 December\n2003, it had the following membership:\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 49\n\nCONTENTS\n1. Overview ......................................................................................................................... 1\n1.1 Scope.\n1\n1.2 Purpose. 1\n2. References ....................................................................................................................... 1\n3. Definitions....................................................................................................................... 2\n4. Reliability indices............................................................................................................ 4\n4.1 Basic factors .................................................................................................................... 4\n4.2 Sustained interruption indices. ........................................................................................ 5\n4.3 Load based indices .......................................................................................................... 7\n4.4 Other indices (momentary) ............................................................................................. 7\n4.5 Major event day classification ......................................................................................... 8\n5. Application of the indices ............................................................................................. 11\n5.1 Sample system .............................................................................................................. 12\n5.2 Calculation of indices for a system with no major event days....................................... 13\n5.3 Examples. ...................................................................................................................... 14\n6. Information about the factors which affect the calculation of reliability\nindices 17\n6.1 Rationale behind selecting the indices provided in this guide. ...................................... 17\n6.2 Factors that cause variation in reported indices ............................................................ 17\nAnnex A (informative) Survey of reliability index usage 18\nAnnex B (informative) Major events definition development. 27\nAnnex C (informative) Internal data subset.\n35\nAnnex D (informative) Bibliography 36\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 50\nSL 11 of 2012\nc\n\nIEEE Guide for Electric Power Distribution Reliability Indices\n\n1.\nOverview\n\n1.1 Scope\nThis guide identifies distribution reliability indices and factors that affect their\ncalculation. It includes indices, which are useful today, as well as ones that may\nbe useful in the future. The indices are intended to apply to distribution systems,\nsubstations, circuits, and defined regions.\n\n1.2 Purpose\nThe purpose of this guide is twofold. First, it is to present a set of terms and\ndefinitions which can be used to foster uniformity in the development of\ndistribution service reliability indices, to identify factors which affect the indices,\nand to aid in consistent reporting practices among utilities. Secondly, it is to\nprovide guidance for new personnel in the reliability area and to provide tools for\ninternal as well as external comparisons. In the past, other groups have defined\nreliability indices for transmission, generation, and distribution but some of the\ndefinitions already in use are not specific enough to be wholly adopted for\ndistribution. Users of this guide should recognize that not all utilities would have\nthe data available to calculate all the indices.\n\n2.\nReferences\nThe following standards shall be used, when applicable, in preparing\nmanuscripts. When the following standard is superseded by an approved revision,\nthe revision shall apply.\n\nIEEE Std. 859\u2122-1987(R2002), IEEE Standard Terms for Reporting and\nAnalyzing Outage Occurrences and Outage States of Electrical Transmission\nFacilities.1, 2\n\nIEEE Std 493\u2122-1997(R2002), Recommended Practice for Design of Reliable\nIndustrial and Commercial Power Systems.\n\n1IEEE Publications are available from the Institute of Electrical and Electronics Engineers, 445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 088551331, USA (http:\/\/standards.ieee.org\/).\n2The IEEE standards or products referred to in this clause are trademarks of the Institute of Electrical and Electronics Engineers, Inc.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 51\n\n3.\nDefinitions\nDefinitions are given here to aid the user in understanding the factors that affect\nindex calculation. Many of these definitions were taken directly from The\nAuthoritative Dictionary of IEEE Standards Terms, 7th Edition [B9]3. If there is\na conflict between the definitions in this document and the dictionary, the\ndefinitions in this document take precedence. Others are given because they have\na new interpretation within this document or have not been previously defined.\n\n3.1\nconnected load: Connected transformer kVA, peak load, or metered demand\n(to be clearly specified when reporting) on the circuit or portion of circuit that is\ninterrupted. When reporting, the report should state whether it is based on an annual peak\nor on a reporting period peak.\n\n3.2\ncustomer: A metered electrical service point for which an active bill account is\nestablished at a specific location (e.g., premise).\n\n3.3\ncustomer count: The number of customers either served or interrupted\ndepending on usage.\n\n3.4\ndistribution system: That portion of an electric system that delivers electric\nenergy from transformation points on the transmission system to the customer.\n\nNOTE\u2014The distribution system is generally considered to be anything from the distribution\nsubstation fence to the customer meter. Often the initial overcurrent protection and voltage\nregulators are within the substation fence and are considered to be part of the distribution system.\n\n3.5\nforced outage: The state of a component when it is not available to perform its\nintended function due to an unplanned event directly associated with that component.\n\n3.6\ninterrupting device: An interrupting device is a device whose purpose is to\ninterrupt the flow of power, usually in response to a fault. Restoration of service or\ndisconnection of loads can be accomplished by manual, automatic, or motor- operated\nmethods. Examples include transmission circuit breakers, feeder circuit breakers, line\nreclosers, line fuses, sectionalizers, motor-operated switches or others.\n\n3.7\ninterruption: The loss of service to one or more customers connected to the\ndistribution portion of the system. It is the result of one or more component outages,\ndepending on system configuration. See also: outage.\n\n3 The numbers in brackets correspond to those of the bibliography in Annex D.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 52\nSL 11 of 2012\nc\n\n3.8\ninterruption duration: The time period from the initiation of\nan interruption to a customer until service has been restored to that customer. The process\nof restoration may require restoring service to small sections of the system (see 5.3.2)\nuntil service has been restored to all customers. Each of these individual steps should be\ntracked collecting the start time, end time and number of customers interrupted for each\nstep.\n\n3.9\ninterruptions caused by events outside of the distribution\nsystem: Outages that occur on generation, transmission, substations, or customer\nfacilities that result in the interruption of service to one or more customers. While\ngenerally a small portion of the number of interruption events, these interruptions can\naffect a large number of customers and last for an exceedingly long duration.\n\n3.10\nlockout: Refers to the final operation of a recloser or circuit\nbreaker in an attempt to isolate a persistent fault, or to the state where all automatic\nreclosing has stopped. The current-carrying contacts of the overcurrent protecting device\nare locked open under these conditions.\n\n3.11\nloss of service: A complete loss of voltage on at least one\nnormally energized conductor to one or more customers. This does not include any of the\npower quality issues such as: sags, swells, impulses, or harmonics.\n3.12\nmajor event: Designates an event that exceeds reasonable\ndesign and or operational limits of the electric power system. A Major Event includes at\nleast one Major Event Day (MED).\n\n3.13\nmajor event day: A day in which the daily system SAIDI\nexceeds a threshold value, TMED. For the purposes of calculating daily system SAIDI,\nany interruption that spans multiple calendar days is accrued to the day on which the\ninterruption began. Statistically, days having a daily system SAIDI greater than TMED are\ndays on which the energy delivery system experienced stresses beyond that normally\nexpected (such as severe weather). Activities that occur on major event days should be\nseparately analyzed and reported. (See 4.5.)\n\n3.14\nmomentary interruption: A single operation of an\ninterrupting device that results in a voltage zero. For example, two circuit breaker or\nrecloser operations (each operation being an open followed by a close) that momentarily\ninterrupts service to one or more customers is defined as two momentary interruptions.\n\n3.15\nmomentary interruption event: An interruption of duration\nlimited to the period required to restore service by an interrupting device.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 53\n\nNOTE\u2014Such switching operations must be completed within a specified time of 5 min or less.\nThis definition includes all reclosing operations that occur within five minutes of the first\ninterruption. For example, if a recloser or circuit breaker operates two, three, or four times and then\nholds (within 5 min of the first operation), those momentary interruptions shall be considered one\nmomentary interruption event.\n\n3.16\noutage (electric power systems): The state of a component when it is not\navailable to perform its intended function due to some event directly associated with that\ncomponent.\n\nNOTES:\n\n(1)\nAn outage may or may not cause an interruption of service to customers, depending on\nsystem configuration.\n\n(2)\nThis definition derives from transmission and distribution applications and does not\napply to generation outages.\n\n3.17\nplanned interruption: A loss of electric power that results when a\ncomponent is deliberately taken out of service at a selected time, usually for the purposes\nof construction, preventative maintenance, or repair.\n\nNOTES:\n\n(1)\nThis derives from transmission and distribution applications and does not apply to\ngeneration interruptions.\n\n(2)\nThe key test to determine if an interruption should be classified as a planned or\nunplanned interruption is as follows: if it is possible to defer the interruption, the interruption is a\nplanned interruption; otherwise, the interruption is an unplanned interruption.\n\n3.18\nplanned outage: The state of a component when it is not available to perform\nits intended function due to a planned event directly associated with that component.\n\n3.19\nreporting period: The time period from which interruption data is to be\nincluded in reliability index calculations. The beginning and end dates and times should\nbe clearly indicated. All events that begin within the indicated time period should be\nincluded. A consistent reporting period should be used when comparing the performance\nof different distribution systems (typically one calendar year) or when comparing the\nperformance of a single distribution system over an extended period of time. The\nreporting period is assumed to be one year unless otherwise stated.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 54\nSL 11 of 2012\nc\n\n3.20\nstep restoration: A process of restoring interrupted customers\ndownstream from the interrupting device\/component in stages over time.\n\n3.21\nsustained interruption: Any interruption not classified as a\npart of a momentary event. That is, any interruption that lasts more than 5 minutes.\n\n3.22\ntotal number of customers served: The average number of\ncustomers served during the reporting period. If a different customer total is used, it must\nbe clearly defined within the report.\n\n3.23 unplanned interruption: An interruption caused by an unplanned outage.\n\n4.\nReliability indices\n\n4.1 Basic factors\nThese basic factors specify the data needed to calculate the indices.\n\ni denotes an interruption event\n\nri = Restoration Time for each Interruption Event CI = Customers Interrupted\nCMI = Customer Minutes Interrupted E = Events\nT = Total\n\nIMi = Number of Momentary Interruptions\n\nIME = Number of Momentary Interruption Events\n\nNi = Number of Interrupted Customers for each Sustained Interruption event\nduring theReporting Period\n\nNmi = Number of Interrupted Customers for each Momentary Interruption event\nduring the Reporting Period\n\nNT = Total Number of Customers Served for the Areas\n\nLi = Connected kVA Load Interrupted for each Interruption Event\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 55\n\nLT = Total connected kVA Load Served\n\nCN = Total Number of Customers who have Experienced a Sustained\nInterruption during the Reporting Period\n\nCNT(k>n) = Total Number of Customers who have Experienced more than n\nSustained Interruptions and Momentary Interruption Events during the Reporting\nPeriod.\n\nk = Number of Interruptions Experienced by an Individual Customer in the\nReporting Period\n\nTMED = Major event day identification threshold value.\n\n4.2 Sustained interruption indices\n\n4.2.1 System average interruption frequency index (SAIFI)\nThe system average interruption frequency index indicates how often the average\ncustomer experiences a sustained interruption over a predefined period of time.\nMathematically, this is given in Equation (1).\n\n(1)\n\nTo calculate the index, use Equation (2) below.\n\n(2)\n\n4.2.2 System average interruption duration index (SAIDI)\nThis index indicates the total duration of interruption for the average customer\nduring a predefined period of time. It is commonly measured in customer\nminutes or customer hours of interruption. Mathematically, this is given in\nEquation (3).\n\n(3)\n\nTo calculate the index, use Equation (4).\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 56\nSL 11 of 2012\nc\n\n(4)\n\n4.2.3 Customer average interruption duration index (CAIDI)\nCAIDI represents the average time required to restore service. Mathematically,\nthis is given in Equation (5).\n\n(5)\n\nTo calculate the index, use Equation 6.\n\n(6)\n\n4.2.4 Customer total average interruption duration index (CTAIDI)\nThis index represents the total average time in the reporting period that customers\nwho actually experienced an interruption were without power. This index is a\nhybrid of CAIDI and is similarly calculated except that those customers with\nmultiple interruptions are counted only once. Mathematically, this is given in\nEquation (7).\n\n(7)\n\nTo calculate the index, use Equation (8).\n\n(8)\n\nNOTE\u2014 In tallying Total Number of Customers Interrupted, each individual customer should only\nbe counted once regardless of number of times interrupted during the reporting period. This applies\nto 4.2.4 and 4.2.5.\n\n4.2.5 Customer average interruption frequency index (CAIFI)\nThis index gives the average frequency of sustained interruptions for those\ncustomers experiencing sustained interruptions. The customer is counted once\nregardless of the number of times interrupted for this calculation.\nMathematically, this is given in Equation (9).\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 57\n\n(9)\n\nTo calculate the index, use Equation (10)\n\n(10)\n4.2.6 Average service availability index (ASAI)\nThe average service availability index represents the fraction of time (often in\npercentage) that a customer has received power during the defined reporting\nperiod. Mathematically, this is given in Equation (11).\n\n(11)\n\nTo calculate the index, use Equation (12).\n\n (12)\nNOTE\u2014There are 8760 hours in a non-leap year, 8784 hours in a leap year.\n\n4.2.7 Customers experiencing multiple interruptions (CEMIn)\nThis index indicates the ratio of individual customers experiencing more than n\nsustained interruptions to the total number of customers served. Mathematically,\nthis is given in Equation (13).\n\n(13)\n\nTo calculate the index, use Equation (14).\n\n(14)\n\nNOTE\u2014This index is often used in a series of calculations with n incremented from a value of one\nto the highest value of interest.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 58\nSL 11 of 2012\nc\n\n4.3 Load based indices\n\n4.3.1 Average system interruption frequency index (ASIFI)\nThe calculation of this index is based on load rather than customers affected.\nASIFI is sometimes used to measure distribution performance in areas that serve\nrelatively few customers having relatively large concentrations of load,\n\npredominantly industrial\/commercial customers. Theoretically, in a system with\nhomogeneous load distribution, ASIFI would be the same as SAIFI.\nMathematically, this is given in Equation (15).\n\n(15)\n\nTo calculate the index, use Equation (16).\n\n(16)\n\n4.3.2 Average system interruption duration index (ASIDI)\nThe calculation of this index is based on load rather than customers affected. Its\nuse, limitations, and philosophy are stated in the ASIFI definition in 4.3.1.\nMathematically, this is given in Equation (17).\n\n(17)\n\nTo calculate the index, use Equation (18).\n\n(18)\n\n4.4 Other indices (momentary)\n\n4.4.1 Momentary average interruption frequency index (MAIFI)\nThis index indicates the average frequency of momentary interruptions.\nMathematically, this is given in Equation (19).\n\n(19)\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 59\n\nTo calculate the index, use Equation (20).\n\n(20)\n\n4.4.2 Momentary average interruption event frequency index (MAIFIE)\nThis index indicates the average frequency of momentary interruption events.\nThis index does not include the events immediately preceding a lockout.\nMathematically, this is given in Equation (21).\n\n(21)\n\nTo calculate the index, use Equation (22).\n\n(22)\n\n4.4.3 Customers experiencing multiple sustained interruption and\nmomentary interruption events (CEMSMIn)\nThis index is the ratio of individual customers experiencing more than n of both\nsustained interruptions and momentary interruption events to the total customers\nserved. Its purpose is to help identify customer issues that cannot be observed by\nusing averages. Mathematically, this is given in Equation (23).\n\n(23)\n\nTo calculate the index, use Equation (24).\n\n(24)\n\n4.5 Major event day classification\nThe following process (\u2015Beta Method\u2016) is used to identify MEDs. Its purpose is\nto allow major events to be studied separately from daily operation, and in the\nprocess, to better reveal trends in daily operation that would be hidden by the\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 60\nSL 11 of 2012\nc\n\nlarge statistical effect of major events. This approach supersedes previous major\nevent definitions (see Annex A for sample definitions). For more technical detail\non derivation of the methodology refer to Annex B.\n\nA major event day is a day in which the daily system SAIDI exceeds a threshold\nvalue, TMED. The SAIDI index is used as the basis of this definition since it\nleads to consistent results regardless of utility size and because SAIDI is a good\nindicator of operational and design stress. Even though SAIDI is used to\ndetermine the major event days, all indices should be calculated based on\nremoval of the identified days.\n\nIn calculating daily system SAIDI, any interruption that spans multiple days is\naccrued to the day on which the interruption begins.\n\nThe major event day identification threshold value, TMED, is calculated at the\nend of each reporting period (typically one year) for use during the next reporting\nperiod as follows:\n\na)\nCollect values of daily SAIDI for five sequential years ending on\nthe last day of the last complete reporting period. If fewer than five years of historical\ndata are available, use all available historical data until five years of historical data are\navailable.\nb)\nOnly those days that have a SAIDI\/Day value will be used to\ncalculate the TMED (do not include days that did not have any interruptions).\nc) Take the natural logarithm (ln) of each daily SAIDI value in the data set.\nd)\nFind \uf061 (Alpha), the average of the logarithms (also known as the\nlog-average) of the data set.\ne)\nFind \uf062 (Beta), the standard deviation of the logarithms (also\nknown as the log- standard deviation) of the data set.\nf) Compute the major event day threshold, TMED, using equation (25).\n\n(25)\n\ng)\nAny day with daily SAIDI greater than the threshold value TMED\nthat occurs during the subsequent reporting period is classified as a major event day.\n\nActivities that occur on days classified as major event days should be separately\nanalyzed and reported.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 61\n\n4.5.1 An example of using the major event day definition\nAn example of using the major event day definition to identify major events and\nsubsequently calculate adjusted indices that reflect normal operating performance\nis shown in this subclause. This subclause illustrates the calculation of the daily\nSAIDI, calculation of the major event day threshold TMED, identification of\nmajor event days, and calculation of adjusted indices. Table 1 gives selected data\nfor all outages occurring on a certain day for a utility that serves 2,000 customers.\n\n(26)\n\nOne month of historical daily SAIDI data is used in the following example to\ncalculate the Major Event Day threshold TMED. Five years of historical data is\npreferable for this method, but printing that many values in this standard is\nimpractical, so only one month is used to illustrate the concept. The example data\nis shown in Table 2.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 62\nSL 11 of 2012\nc\n\n The value of \uf061, the log\n-average, is the average of the natural logs, and equals \u2013\n0.555 in this case.\n The value of \uf062, the log\n-standard deviation, is the standard deviation of the\nnatural logs, and equals 1.90 in this example.\n The value of \uf061 + 2.5\uf062 is 4.20.\n\nThe threshold value TMED is calculated by e(4.20) and equals 66.69 SAIDI per\nday. This value is used to evaluate the future time period (e.g., the next year).\n\nTable 3 shows example SAIDI\/day values for the first month of 1994.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 63\n\nThe SAIDI\/day on 1\/28\/94 (237.49) exceeds the example threshold value\n(TMED\n= 66.69), indicating that the distribution system experienced stresses beyond that\nnormally expected on that day. Therefore, 1\/28\/94 is classified as a major event\nday. The SAIDI\/day for all other days was less than TMED, indicating that\nnormal stresses were experienced on those days.\n\nTo complete the example, indices should be calculated for the following two\nconditions:\n\na)\nall events included\n\nb)\nmajor event days removed. In most cases, utilities will calculate\nall of the indices they normally use (e.g., SAIFI, SAIDI and\/or CAIDI). For this\nexample, only SAIDI will be shown. 1994 SAIDI for condition one, all events\nincluded, is given in Equation (27) below.\n\n(27)\n\n1994 SAIDI for condition two, major event days removed for separate reporting\nand analysis, is given in equation 28 below.\n\n(28)\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 64\nSL 11 of 2012\nc\n\n5.\nApplication of the indices\nMost utilities store interruption data in large computer databases. Some databases\nare better organized than others for querying and analyzing reliability data. The\nfollowing section will show one sample partial database and the methodology for\ncalculating indices based on the information provided.\n\n5.1 Sample system\nTable 4 shows an excerpt from one utility\u2019s customer information system (CIS)\ndatabase for feeder 7075, which serves 2,000 customers with a total load of 4\nMW. In this example, Circuit 7075 constitutes the \u2015system\u2016 for which the\nindices are  calculated.  More  typically  the  \u2015system\u2016  combines  all  circuits\ntogether  in  a region or for a whole company.\n\nThe total number of customers who have experienced a sustained interruption is\n3,215. The total number of customers experiencing a momentary interruption is\n2, 400.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 65\n\nFrom Table 6, it can be seen that there were eight circuit breaker operations that\naffected 2000 customers. Each of them experienced 8 momentary interruptions.\nThere were twelve recloser operations that caused 750 customers to experience\n12 momentary interruptions. Some of the operations occurred during one\nreclosing sequence. To calculate the number of momentary interruption events,\nonly count the total number of reclosing sequences. In this case there were five\ncircuit breaker events (records 1, 3, 4, 7, and 9) that affected 2000 customers.\nEach of them experienced 5 momentary interruption events. There were six\nrecloser events (records 2, 5, 6, 8, 10 and 11) that affected 750 customers each of\nthem experienced 6 momentary interruption events.\n\n5.2 Calculation of indices for a system with no major event days\n\nThe equations in Clause 4.5 and definitions in Clause 3 should be used to\ncalculate the annual indices (see Equations (29) \u2013 (40)). In the example below,\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 66\nSL 11 of 2012\nc\n\nthe indices are calculated by using the equations in 4.2 and 4.4 using the data in\nTable 4 and Table 5, assuming there were no major event days in this data set.\n\nTo calculate CTAIDI and CAIFI, the number of customers experiencing a\nsustained interruption is required. The total number of customers affected (CN)\nfor this example can be no more than 2000. Since only a small portion of the\ncustomer information table is shown it is impossible to know CN; however, it is\nlikely that not all of the 2000 customers on this feeder experienced an\ninterruption during the year. 1800 will be arbitrarily assumed for CN (for your\ncalculations actual information should be used) since the interruption on 9\/3\nshows that at least 1500 customers have been interrupted during the year.\n\nCTAIDI, CAIFI, CEMIn, and CEMSMIn require detailed interruption\ninformation for each customer. The database should be searched for all customers\nwho have experienced more than n interruptions that last longer than five\nminutes. Assume n is chosen to be 5. In Table 5, customer Willis, J. experienced\nseven interruptions in one year and it is plausible that other customers also\nexperienced more than five interruptions, both momentary and sustained.\n\nFor this example, assume arbitrary values of 350 for CN(k > n), and 750 for\nCNT(k > n). The number of interrupting device operations is given in Table 6\nand is used to calculate MAIFI and MAIFIE. Assume the number of customers\ndownstream of the recloser equals 750. These numbers would be known in a real\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 67\n\nsystem.\n\nUsing the above sample system should help define the methodology and\napproach to obtaining data from the information systems and using it to calculate\nthe indices.\n\n5.3 Examples\nThe following subclause illustrates two concepts: momentary interruptions and\nstep restoration through the use of examples.\n\n5.3.1 Momentary interruption example\nTo better illustrate the concepts of momentary interruptions and sustained\ninterruptions and the associated indices, consider Figure 1 and Equation 41,\nEquation 42, and Equation 43. Figure 1 illustrates a circuit composed of a circuit\nbreaker (B), a recloser (R), and a sectionalizer (S).\n\nFor this scenario, 750 customers would experience a momentary interruption and\n250 customers would experience a sustained interruption. Calculations for SAIFI,\nMAIFI, and MAIFIE on a feeder basis are shown in Equations 41\u201343 below.\nNotice that the numerator of MAIFI is multiplied by 2 because the recloser took\ntwo shots, however, MAIFIE is multiplied by 1 because it only counts the fact\nthat a series of momentary events occurred.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 68\nSL 11 of 2012\nc\n\n5.3.2 Step restoration examples\nThe following case illustrates the step restoration process. A feeder serving 1000\ncustomers experiences a sustained interruption. Multiple restoration steps are\nrequired to restore service to all customers. Table 7 shows the times of each step,\na description and associated customers interruptions and minutes they were\naffected in a time line format.\n\nFigure 2 illustrates the example described in Table 7. In this example, all of the\ncustomers supplied by the circuit were interrupted at the beginning of step 1.\nService was restored to a portion of those customers at the end of step 1. Service\nwas restored to another portion of those customers at the end of step 2.\nAdditional customers were interrupted during step 3 (new step 1). Service was\nrestored to additional customers at the end of step 3.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 69\n\nTable 8 shows the information in a format that explains each step and allows the\nreader to see the calculation steps.\n\n6.\nInformation about the factors which affect the calculation of reliability\nindices\n\n6.1 Rationale behind selecting the indices provided in this guide\n\nOne view of distribution system performance can be garnered through the use of\nreliability indices. To adequately measure performance, both duration and\nfrequency of customer interruptions must be examined at various system levels.\nThe most commonly used indices are SAIFI, SAIDI, CAIDI and ASAI. All of\nthese indices provide information about average system performance. Many\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 70\nSL 11 of 2012\nc\n\nutilities also calculate indices on a feeder basis to provide more detailed\ninformation for decision making. Averages give general performance trends for\nthe utility; however, using averages will lead to loss of detail that could be\ncritical to decision making. For example, using system averages alone will not\nprovide information about the interruption duration experienced by any specific\ncustomer. At the time of this writing, it is difficult for most utilities to provide\ninformation on a customer basis. This group envisions that the tracking of\nspecific details surrounding specific interruptions rather than averages will, in the\nfuture, be accomplished by improving tracking capabilities. To this end, the\nworking group has included not only the most commonly used indices, but also\nindices that examine performance at the customer level (e.g., CEMIn).\n\n6.2 Factors that cause variation in reported indices\nMany factors can cause variation in the indices reported by different utilities.\nSome examples of differences in the following:\n\n\u2014 level of automated data collection\n\u2014 geography\n\u2014 system design\n\u2014 data classification (e.g., are major events in the data set?, planned interruptions?)\n\nTo ensure accurate and equitable assessment and comparison of absolute\nperformance and performance trends over time, it is important to classify\nperformance for each day in the data set to be analyzed as either day-to-day or\nmajor event day. Not performing this critical step can lead to false decision\nmaking because major event day performance often overshadows and disguises\ndaily performance. Interruptions that occur as a result of outages on customer\nowned facilities or loss of supply from another utility should not be included in\nthe index calculation.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 71\n\nAnnex A\n(informative)\n\nSurvey of reliability index usage\nThe Working Group on System Design conducted three surveys on distribution\nreliability index usage. The first one was completed in 1990 and the second was\ncompleted in 1995 and the third one was completed in 1997. The purpose of the\nsurveys was to determine index usage and relative index values. In 1990, 100\nUnited States utilities were surveyed, 49 of which responded. In 1995, 209\nutilities were surveyed, 64 of which responded. In 1997, 159 utilities were\nsurveyed and 61 responded. Responding utility locations are shown by state in\nFigure A.1.\n\nNewer surveys are being performed by Edison Electric Institute (EEI). The data\nprovided is not comparable because utilities provided whatever information was\neasily obtainable. All surveys showed that the most commonly used indices are\nSAIFI, SAIDI, CAIDI, and ASAI. Figure A.2 shows the percentage of companies\nusing specific indices in 1990. Figure A.3 shows the same information for 1995\nand 1997. Figures A.4\u2013A.8 show data on the most commonly used indices given\nby quartiles where Q1 is the top quartile. The data shown in the Q1 column\nmeans that 25% of utilities have an index less than the value shown. For further\nclarification:\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 72\nSL 11 of 2012\nc\n\nQ1: 25% of utilities have an index less than the value shown\nQ2: 50% of utilities have an index less than the value shown (the median value)\nQ3: 75% of utilities have an index less the value shown\nQ4:100% of utilities have an index less the value shown\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 73\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 74\nSL 11 of 2012\nc\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 75\n\nA.1 Cause codes\n\nIn the 1997 survey, cause codes were surveyed. The results are shown below in\nFigure A.9.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 76\nSL 11 of 2012\nc\n\nA.2 Results of question # 7 of the 1999 EEI reliability survey\n\nThe following information was provided by the Edison Electric Institute (EEI)\nbased on a survey they performed in 1999. The text is shown exactly as the\nsurvey respondents provided the information to EEI.\n\nWhat definition do you use for major events?\n\n1) Major storm defined as 10% or more of the customer base interrupted in an\noperating region (based on 8 operating regions) or customers interrupted for 24\nhours.\n\n2) Interruptions that result from a catastrophic event that exceeds the design limits\nof the electric power system, such as an earthquake, tornado, or an extreme storm.\n\n3) A major storm is an event that affects 10% or more of the connected customers\nwith 1% not restored within 24 hours.\n\n4) Ten percent or more of our customers are without power and have been without\npower for more than 24 hours.\n5) The major storm exclusion a criterion is based on a statistical analysis of the last\nfour-year history of reliability data. A cumulative frequency distribution of\n\nthe number of locations requiring service restoration work per day is calculated\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 77\n\nfor the four-year period. When the frequency of the restoration work exceeds the\n98.5 percentile, by company or region the major storm criterion work be met for\nthe all interruptions for that day.\n\n6)  Ten percent of customers in a given region affected by an event plus the last customer\nout greater than 24 hours. All three of the following must be true:\n\n\u2014widespread damage\n\u201410 000 or 10% of customers served in area affected\n\u2014National Weather Service declares severe weather watch or warning for the area\n\n7) Ten percent customer base and 1 customer for 24 hours.\n\n8) More than 15 000 customers out (out of a total customer base of 450 000).\n\n9) As defined by our PUC as named storms, tornados, ice storms, etc.\n\n10)\nEvents where 10% of your customers (meters) have\nexperienced an interruption due to the event.\n\n11)\nIEEE Std 1366\u2122-1998; Definition 3.12 major event. Company\n1 defined as, 10% of the customers within a region without electricity and not restored\nwithin a 24 hour period.\n\n12)\nTen percent of the entire electric system\u2019s customers must\nexperience an interruption in service and one percent of the entire electric system\u2019s\ncustomers must experience an interruption in service for more than 24 hours.\n\n13)\nTen percent of customers out of service and restoration time\nexceeding 24 hours.\n\n14)\nNamed storms, i.e. hurricane, tropical storms, or tornadoes\nverified by the National Weather Service. Major forest fires are also included. In\naddition, Company 2 reporting definition does not include planned interruptions. MAIFI\nis reported as momentary events.\n\n15)\n(1) Winds in excess of 90 mph OR (2) 1\/2 inch of ice and winds\nin excess of 40 mph.\n\nNOTE\u2014 The major storm outage minutes in 1999 were minimal for Company 3 and did not impact\nthe reliability measures.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 78\nSL 11 of 2012\nc\n\n16)\n0.8 hours x customers served for a month, if the customer hours lost for any\none day in that month exceed this value it can be removed from our year-end\ncalculations. Interruptions that result from a catastrophic event that exceeds the\ndesign limits of the electric power system, such as an earthquake or an extreme\nstorm. These events shall include situations where there is a loss of power to 10% or\nmore of the customers over a 24-hour period and with all customers not restored\nwithin 24 hours.\n\n17)\nState of Connecticut Department of Public Utility Control \u2013 Major Storm\nExclusion Definition for 1999 \u2013 Any day or 24-hour period, where 31 restoration\nsteps or greater were experienced. For 2000, the UI storm exclusion is based on 35\nrestoration steps or greater. The change in storm exclusion restoration step threshold,\nis based on the previous four-year outage history.\n\n18)\nA period of adverse weather which interrupts 10% or more of the customers\nserved in an operating area, or results in customers being without power for 24 hours\nor longer.\n\n19)\nWeather events that cause more than 100 000 customers to be interrupted, with\nrestoration taking at least 24 hours.\n\n20)\n(1) A Watch or Warning has been issued by the National Weather Service, (2)\nExtensive mechanical damage has been experienced and (3) More than 6% of the\ncustomers served in a region have been affected by outages during a 12-hour period.\n\n21)\nA major storm is defined as the interruption to 110 000 customers or more\nwhich is about 5 percent of our total customers. The 110 000 was arrived at by going\nout six standard deviations from the mean of all daily cases of trouble.\n\n22) Any outage lasting longer than 48 hours is capped at 48 hours.\n\n23)\nAny event outage over 10% of the customers in a region AND requiring over\n24 hours to restore service to all customers. (PUC definition) Outages occurring\nduring qualifying major storms are not entered into our system, therefore we can only\nreport on 8B, 11B, and 13B below.\n\n24) Determination is subjective, not strictly defined at this time.\n\n25) Tropical storms, hurricanes, tornados, and ice storms.\n\n26) Interruptions that result from a catastrophic event that exceeds the design\nlimits of the electric power system, such as an earthquake or an extreme storm.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 79\n\nThese events shall include situations where there is a loss of power to 10% or\nmore customers in a region over a 24-hour period and with all customers not\nrestored within 24 hours.\n\n27) >10% of customers out of service for >24 hours.\n\n28) 15 000 or more customers out of service.\n\n29) Ten percent of customers in an area (region) interrupted.\n\n30)\n(1) 10% or more of customers interrupted in a operating area.\nAnd (2) A storm or other large occurrence where customers experience an\ninterruption for 24 or more hours in an operating area.\n\n31)\nA storm is determined at regional level when in any\nconsecutive 24 hours the cumulative outages reach 15 AND cumulative customer\ninterruption minutes reach 200 000\n\n32)\nA major storm is defined as an interruption of electric service\nresulting from conditions beyond the company\u2019s control, which affects at least 10%\nof the customers in an operating area during the course of an event.\n\n33)\nLevel 3 or above out of 5 according to our emergency plan.\nAbout 5 storms per year excluded.\n\n34)\nAny day during which the number of interruptions are greater\nthan 3 standard deviations above average.\n\n35)\nCAIDI for the storm period must be 2.5 times normal. Outside\ncrews required to restore damage. Restoration of damage must require 24 hours or\nmore.\n\n36) Named Storms (i.e. hurricane).\n\n37)\nExtension mechanical damage to the electric system. Outages\ninvolving more than 10% of the customers served by district. More than 1% of the\ncustomers serviced have not been restored within 24 hours.\n\n38) 15 000 or more customers outages.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 80\nSL 11 of 2012\nc\n\n39)\n(1) > 10% of the customers out of service at any one time,\nreported on a district basis. and (2) Extraordinary storm event such as a tornado,\nsevere winds, etc.\n\n40) A major storm is one which affects 15 000 of our approximately 120 000\ncustomers AND makes an incremental addition of 10 min to company SAIDI.\n\n41) A storm or equipment failure that would cause widespread serious damage\nthroughout the service area in such proportion that available Company 4 forces\nwould be unable to restore service within 48 hours. We designate this as a Level III\nevent \u2013 Company 4 has 3 levels of event classifications There were no Level III\nevents in 1999.\n\n42) The major storm exclusion criterion is based on a statistical analysis of the last\nfour-year history of reliability data. A cumulative frequency distribution of the\nnumber of locations requiring service restoration work per day is calculated for the\nfour-year period. When the frequency of the restoration work exceeds the 98.5\npercentile, by company or region the major storm criterion work be met for\nthe all interruptions for that day.\n\n43) Named storms, tornadoes, ice, events with >10% of customers out.\n\n44) An interruption of electric service resulting from conditions beyond the\ncontrol of the electric distribution company which affects at least 10% of the\ncustomers in an operating area during the course of event for a duration of 5 min\neach or greater.\n\n45) An interruption of electric service resulting from conditions beyond the\ncontrol of the electric distribution company which affects at least 10% of the\ncustomers in an operating area.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 81\n\nAnnex B\n\n(informative)\n\nMajor events definition development\n\nB.1 Justification and process for development of the 2.5 beta methodology\n\nThe statistical approach to identifying major event days was chosen over the\nprevious definitions (as shown in A.2) because of the difficulties experienced in\ncreating a uniform list of types of major events, and because the measure of\nimpact criterion (i.e., percent of customers affected) required when using event\ntypes resulted in non-uniform identification. The new methodology should fairly\nidentify major events for all utilities. Some key issues had to be addressed in\norder to consider this work successful. They were as follows:\n\n\u2014 Definition must be understandable and easy to apply.\n\u2014 Definition must be specific and calculated using the same process for all utilities.\n\u2014 Must be fair to all utilities regardless of size, geography, or design.\n\u2014 Entities that adopt the methodology will calculate indices on a normalized basis for trending\nand reporting. They will further classify the major event days separately and report on those\ndays through a separate process.\n\nDaily SAIDI values are preferred to daily customer minutes interrupted (CMI)\nvalues for major event day identification because the former permits comparison\nand computation among years with different numbers of customers served.\nConsider the merger of two utilities with the same reliability and the same\nnumber of customers. CMI after the merger would double, with no change in\nreliability, while SAIDI would stay constant.\n\nDaily SAIDI values are preferred to daily SAIFI values because the former are a\nbetter measure of the total cost of reliability events, including utility repair costs\nand customer losses, than the latter. The total cost of unreliability would be a\nbetter measure of the size of a major event, but collection of this data is not\npractical.\n\nThe selected approach for setting the major event day identification threshold,\nknown  as  the  \u2015Two  Point  Five  Beta\u2016  method  (since  it  is  using  the  lognormal SAIDI values rather than the raw SAIDI values), is preferred to using\nfixed multiples  of  standard  deviation  (e.g.  \u2015Three  Sigma\u2016)  to  set  the\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 82\nSL 11 of 2012\nc\n\nidentification threshold because the latter results in non-uniform MED\nidentification among utilities with different sizes and average reliabilities. The b\nmultiplier of 2.5 was chosen because, in theory, it would classify 2.3 days per\nyear as major events. If significantly more days than this are identified, they\nrepresent events that have occurred outside the random process that is assumed to\ncontrol distribution system reliability. The process and the multiplier value were\nevaluated by a number of utilities with different sized systems from different\nparts of the United States and found to correlate reasonably well to current major\nevent identification results for those utilities. A number of alternative approaches\nwere considered. None was found to be clearly superior to Two Point Five Beta.\n\nWhen a major event occurs which lasts through midnight (for example, a six hour\nhurricane which starts at 9:00 PM), the reliability impact of the event may be\nsplit between two days, neither of which would exceed the TMED and therefore\nbe classified as a major event day. This is a known inaccuracy in the method that\nis accepted in exchange for the simplicity and ease of calculation of the method.\n\nThe preferred number of years of data (five) used to calculate the major event\nday identification threshold was set by trading off between the desire to reduce\nstatistical variation in the threshold (for which more data is better) and the desire\nto see\n\nB.1.1\nRemarks\n\nTo generate the example data, values of a and b were taken from an actual utility\ndata set, and then daily SAIDI\/day values were artificially generated using a log normal distribution wi\nthen adjusted to illustrate all aspects of the calculation, e.g. a day in Table 2 was\nassigned a SAIDI value of zero, and a day in Table 3 was assigned a SAIDI value\nhigher than the computed threshold.\n This annex provides a technical description and analysis of the 2.5\uf0e2 method of identifying MEDs in di\n\nmethod based on the theory of probability and statistics. Fundamental concepts\nsuch as probability distribution and expected value are highlighted in italics when\nthey are first used, and provided with a short definition. An undergraduate\nprobability and statistics textbook can be consulted for more complete\ndefinitions.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 83\n\nB.1.2 Beta (\uf062) method description\n\nA threshold on daily SAIDI is computed once a year (see 4.5). The short version\nis as follows:\n\na)\nAssemble the five most recent years of historical values of SAIDI\/day. If less\nthan five years of data is available, use as much as is available.\n\nb) Discard any day in the data set that has a SAIDI\/Day of zero.\n\nc) Find the natural logarithm of each value in the data set.\n\nd)\nCompute the average (\uf061, or Alpha) and standard deviation (\uf062\uf02c or Beta) of the\nnatural logarithms computed in step 3.\n\ne) Compute the threshold TMED = exp (Alpha + 2.5 * Beta).\n\nf) Any day in the next year with SAIDI > TMED is a major event day.\n\nB.2 Random nature of distribution reliability\n\nThe reliability of electric power distribution systems is a random process, that is,\na process that produces random values of a specific random variable. A simple\nexample of a random process is rolling a die. The random variable is the value on\nthe top face of the die after a roll, which can have integer values between 1 and 6.\n\nIn electric power distribution system reliability, the random variables are the\nreliability indices defined in the guide. These are evaluated on a daily or yearly\nbasis, and take on values from zero to infinity.\n\nB.3 Choice of SAIDI to identify major event days\n\nFour commonly used reliability indices are:\n\n\u2014 System Average Interruption Duration Index (SAIDI)\n\u2014 System Average Interruption Frequency Index (SAIFI)\n\u2014 Customer Average Interruption Duration Index (CAIDI)\n\u2014 Average Service Availability Index (ASAI)\n\nThese indices are actually measures of unreliability, as they increase when\nreliability becomes worse.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 84\nSL 11 of 2012\nc\n\nAn ideal measure of unreliability would be customer cost of unreliability, the\ndollar cost of power outages to a utility\u2019s customers. This cost is a combination\nof the initial cost of an outage and accumulated costs during the outage.\nUnfortunately, the customer cost of unreliability has so far proven impossible to\nestimate accurately. In contrast, the reliability indices above are routinely and\naccurately computed from historical reliability data. However, the ability of an\nindex to reflect customer cost of unreliability indicates the best one to use for\nmajor event day identification.\n\nDuration-related costs of outages are higher than initial costs, especially for\nmajor events, which typically have long duration outages. Thus a duration-related\nindex will be a better indicator of total costs than a frequency-related index like\nSAIFI or MAIFI. Because CAIDI is a value per customer, it does not reflect the\nsize of outage events. Therefore SAIDI best reflects the customer cost of\nunreliability, and is the index used to identify major event days. SAIDI in\nminutes\/day is the random variable used for major event day identification.\n\nThe use of Customer Minutes Interrupted per day was also considered. Like\nSAIDI, CMI is a good representation of customer cost of unreliability. In fact,\nSAIDI is just CMI divided by the number of customers in the utility. The number\nof customers can vary from year to year, especially in the case of mergers, and\nmultiple years of data are used to find major event days. Use of SAIDI accounts\nfor the variation in customer count, while use of CMI does not. Therefore SAIDI\nis preferred.\n\nB.4 Probability distribution of distribution system reliability\n\nB.4.1\nProbability density functions and probability of exceeding a threshold\nvalue\n\nMEDs will be days with larger SAIDI values. This suggests the use of a\nthreshold value for daily SAIDI. The threshold value is called TMED. Days with\nSAIDI greater than TMED are major event days. As the threshold increases,\nthere will be fewer days with SAIDI values above the threshold. The relationship\nbetween the threshold and the number of days with SAIDI above the threshold is\ngiven by the probability density function of SAIDI\/day.\n\nThe probability density function gives the probability that a specific value of a\nrandom variable will appear. For example, for a six sided die, the probability that\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 85\n\na one will appear in a given roll is 1\/6th, and the value of the probability density\nfunction of one is 1\/6th for this random process.\n\nThe probability that a value greater than one will occur is just the sum of the\nprobability densities for all values greater than one. Since each value has a\nprobability density of 1\/6th for the example, this sum is just 5\/6ths. As the\nthreshold increases, the probability decreases. For example, for a threshold of 4,\nthere are only two values greater than 4, and the probability of rolling one of\nthem is 2\/6ths or 1\/3rd.\n\nIn the die rolling example, the random variable can only have discrete integer\nvalues. SAIDI\/day is a continuous variable. In this case, the sum is replaced by\nan integral. The probability p that any given day will have a SAIDI\/day value\ngreater than a threshold value T is the integral of the probability density function\nfrom the threshold to infinity as shown below in Equation (B.1).\n\n(B.1)\n\nGraphically, the probability is the area under the probability density function\nabove the threshold, as shown in Figure B.1.\n\nIf any given day has a probability p of being a major event day, then the expected\nvalue [see Equation (B.2)] of the number of major event days in a year is the\nprobability times the number of days in a year.\n\n(B.2)\n\nFor example, if p = 0.1, then the expected number of major event days in a year\nis 36.5. This does not mean that exactly 36.5 MEDs will occur. The actual\nnumber will vary due to the randomness of the process.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 86\nSL 11 of 2012\nc\n\nUsing the die rolling example, the probability of getting a six in any roll is 1\/6th.\nTherefore the expected number of sixes in six rolls is 1. However, if the die is\nrolled six times, there could be six sixes, or zero sixes, or any number in\nbetween. As the number of trials goes up, the number of sixes will approach\n1\/6th of the number of rolls, but for small numbers of rolls there will be some\nvariation from the expected value.\n\nB.4.2\nGaussian, or normal distribution\n\nThe expected number of MEDs per year can be computed for any given threshold\nif the shape of the probability density function is known. The shape of the\nprobability density function is called the probability distribution. Specific types\nof shapes have specific names. The most well known is the Gaussian distribution,\nalso called the normal distribution or bell curve, shown in Figure B.2.\n\nThe Gaussian distribution is completely described by its mean, or average value, (\u03bc or Mu) and its stan\nalue is at the\ncenter of the distribution (at 0 on the x axis in Figure B.2) and the standard\ndeviation is a measure of the spread of the distribution.\n\nAn important property of the Gaussian distribution is that the probability of\nexceeding a given threshold is a function of the number of standard deviations\nthe threshold is from the mean. Equation (B.3) provides mathematical terms.\n\n(B.3)\n\nIf the threshold is n standard deviations greater than the mean, and the probability\nof exceeding the threshold, p(SAIDI > TMED), is a function only of n, and not of\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 87\n\nthe mean and standard deviation. Values for this function are found in tables in\nthe backs of probability textbooks and in, for example, standard spreadsheet\nfunctions. Table B.1 gives the probability of exceeding the threshold for different\nnumber of standard deviations k.\n\nB.4.3\nThree sigma\n\nThe term \u2015Three Sigma\u2016 is often used loosely to designate a rare event. It comes\nfrom the Gaussian probability distribution. As Table B.1 shows, the probability\nof exceeding a threshold that is three standard deviations more than the mean is\n0.00135, or one and a half tenths of a percent. If daily SAIDI had a Gaussian\nprobability distribution, it would be relatively easy to agree on a Three Sigma\ndefinition for the major event day threshold, TMED. Unfortunately, SAIDI does\nNOT have a Gaussian distribution. It has a log-normal distribution.\n\nB.5 Log-normal distribution\n\nThe random variable in the Gaussian distribution has a range from \u2013\uf0a5 to \uf0a5. In\nreal life, many quantities, including distribution reliability, can only be zero or\npositive. This causes the probability distribution to skew, bunching up near the\nzero axis and having a long tail to the right. The degree of skewness depends on\nthe ratio of mean to standard deviation. When the standard deviation is small\ncompared to the mean, the log normal distribution looks like the Gaussian\ndistribution, as shown in Figure B.3(b). When it is large compared to the mean, it\ndoes not, as shown in Figure B.3(a). Daily reliability data usually has standard\ndeviation values far larger than the mean.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 88\nSL 11 of 2012\nc\n\nA consequence of the log-normality of daily reliability data is that the three\nsigma conditions no longer hold. In particular, the probability of exceeding a\ngiven threshold is no longer independent of the values of the average and\nstandard deviation of the distribution. This means that using a method such as\nThree Sigma\n\nwould result in different numbers of MEDs for utilities with different average\nvalues of reliability, or with different standard deviation values. This seems\ninequitable.\n\nFortunately, the logarithms of log-normal data have a Gaussian distribution. If\nthe average of the logarithms of the data is called \uf061, or Alpha, and the standard deviation of the logari\nmean and standard deviation of a Gaussian distribution and a threshold on the log\nof the data can be set which is independent of the values of \uf0e1 and \u00df. Equations\n(B.4) and (B.5) show these concepts mathematically.\n\n(B.4)\n\nand\n\n(B.5)\n\nThe probability of exceeding TMED is a function of k, just as in the Gaussian\nexample. Table B.2 gives these probabilities as well as the expected number of\nMajor Event Days (MEDs) for various values of k.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 89\n\nB.5.1 Why 2.5?\n\nGiven an allowed number of MEDs per year, a value for k is easily computed.\nHowever, there is no analytical method of choosing an allowed number of\nMEDs\/year. The chosen value of k = 2.5 is based on consensus reached among\nDistribution Design Working Group members on the appropriate number of days\nthat should be classified as Major Event Days. As Table B.2 shows, the expected\nnumber of days for k = 2.5 is 2.3 MEDs\/year. In practice, the experience of the\ncommittee members, representing a wide range of distribution utilities, was that\nmore than 2.3 days were usually classified as MEDs, but that the days that were\nclassified as MEDS were generally those that would have been chosen on\nqualitative grounds. The performance of different values of k were examined,\nand consensus was reached on k = 2.5.\n\nB.6 Fairness of the 2.5\u00df method\nIt is likely that reliability data from different utilities will be compared by utility\nmanagement, public utilities commissions and other interested parties. A fair\nMED classification method would classify, on average, the same number of\nMEDs per year for different utilities.\n\nThe two basic ways that utilities can differ in reliability terms are in the mean\nand standard deviation of their reliability data. Differences in means are\nattributable to differences in the environment between utilities, and to differences\nin operating and maintenance practices. Differences in standard deviation are\nmostly attributable to size. Larger utilities have inherently smaller standard\ndeviations. As discussed above, using the mean and standard deviation of the logs of the data\nMEDs depend only on the multiplier, and thus should classify the same number\nof MEDs for large and small utilities, and for utilities with low and high average\nreliability.\n\nThis is not the case for using the mean and standard deviation of the data without\ntaking logarithms first. The expected number of MEDs varies the average and\nstandard deviation. This variation occurs because of the log-normal nature of the\nreliability probability distribution.\n\nB.7 Five years of data\nFrom a statistical point of view, the more data used to calculate a threshold, the\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 90\nSL 11 of 2012\nc\n\nbetter. However, the random process producing the data changes over time as the\ndistribution system is expanded and operating procedures are varied. Using too\nmuch historical data would suppress the effects of these changes.\nThe addition of another year of data should have a low probability of changing\nthe MED classification of previous years. A result from order statistics gives the\nprobability that the kth largest value in m samples will be exceeded f times in n\nfuture samples [B10]. It is given in Equation (B.5).\n\n(B.5)\n\nFor example, if M = 3 years of data then m = 1095 samples. If f = 3 MEDs\/year\nthen the largest non-MED is the k = 1095 \u20139 = 1086th ordered sample. The\nprobability of f = 3 days in the next year of n = 365 samples exceeding the size of\nthe largest non-MED is found from the equation to be 0.194 (19.4%). In Figure\nB.5 p is plotted against M for several values of f.\n\nThe consensus of the Design Working Group members was that 5 years was the\nappropriate amount of data to collect. They felt that the distribution system\nwould change enough to invalidate any extra accuracy from more than 5 years of\ndata.\nAnnex C (informative) Internal data subset\nC.1 Calculation of reliability indices for subsets of data for internal company\nuse\n\nReliability performance can be assessed for different purposes. It may be\nadvantageous to calculate reliability indices without planned interruptions in\norder to review performance during unplanned events. In another case, it may be\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 91\n\nadvantageous to review only sustained interruptions. Assessment of performance\ntrends and goal setting should be based on normal event days (neglecting the\nimpact of MEDs). Utilities and regulators determine the most appropriate data to\nuse for reliability performance monitoring. When indices are calculated using\npartial data sets, the basis should be clearly defined for the users of the indices.\nAt a minimum, reliability indices based on all collected data for a reporting\nperiod and analyzed as to normal versus major event day classifications should\nbe provided. Indices based on subsets of collected data may be provided as\nspecific needs dictate.\n\nSCHEDULE 2\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\n\nPage 92\nSL 11 of 2012\nc\n\nAnnex D\n(informative)\nBibliography\n[B1] \u2015A Nationwide Survey of Distribution Reliability Measurement Practices,\u2016\nIEEE\/PES Working Group on System Design, Paper No. 98 WM 218.\n[B2] Balijapelli N., Venkata S. S., Christie R. D., \u2015Predicting Distribution\nSystem Performance Against Regulatory Reliability Standards,\u2016 to appear in\nIEEE Transactions on Power Delivery.\n[B3]  Blinton,  R.  and  Allan  R.  N.,  \u2015Reliability  Evaluation  of  Power  Systems,\u2016\nPlenum Press, 1984.\n[B4] Billinton R., Allan R., Salvaderi L., Applied Reliability Assessment in\nElectric Power Systems, IEEE Press, New York, 1991.\n[B5] Brown R.E., Electric Power Distribution Reliability, Marcel Dekker, New\nYork, 2002.\n[B6]  Capra,  R.  A.,  Gangel,  M.  W.,  and  Lyon,  S.V.  \u2015Underground  Distribution\nSystem Design for Reliability,\u2016IEEE Transactions on Power Apparatus and\nSystems, Vol. PAS-88, No. 6, June 1969, pp. 834-42.\n[B7] Christie R.D., \u2015Statistical Classification of Major Event Days in\nDistribution System Reliability,\u2016accepted to IEEE Transactions on Power\nDelivery.4\n[B8] EPRI EL-2018, RP-1356-1, Development of Distribution System Reliability\nand Risk Analysis Models,\" Vol. 2, August 1981.\n[B9] IEEE 100, The Authoritative Dictionary of IEEE Standard Terms, 7th Edition.5\n[B10] Kottegoda N. T., and Rosso R., Statistics, Probability, and Reliability for\nCivil and Environmental Engineers, McGraw-Hill, New York, 1997.\n[B11]   Marinello,   C.   A.,   \u2015A   Nationwide   Survey   of   Reliability\nPractices,\u2016 presented at EEI Transaction and Distribution Committee Meeting,\nHershey, PA, October 20, 1993.\n\nElectricity Regulatory Authority (Standard of Performance) Rules, 2012\nSCHEDULE 2\n\nc\nSL 11 of 2012\nPage 93\n\nMade by the Authority, after consultation with the Governor and the licensee, the\n8th day of March, 2012.\nS.B. Cowan\nChairman.\nD.B.R. Rankine\nMember.\nMike Herland\nMember.\nD.L. 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