Algorithm for Automatic Calculation of SAIDI and SAIFI Reliability Indices Based on Metering System Data
Keywords:
power distribution grid, reliability, SAIFI and SAIDI indices, automatic calculation, electricity metering system
Abstract
A 10–35 kV power distribution grid is considered, in which an automated information and measuring electricity metering system operates. It is assumed that the metering system head unit (instrument) contains data on the electrical network feeder’s and on the number of consumers (subscribers) connected to all of its outgoing lines. The head unit communicates with the feeder’s outgoing line meters that record the date, time, and duration of sustained (more than five-minute) interruptions of power supply to consumers. The appropriate meters transmit, on a monthly basis, data on power supply interruptions in the outgoing lines to the head unit, where the power distribution grid’s SAIDI and SAIFI reliability indices are calculated according to the developed algorithm. These reliability indices are automatically calculated according to the method outlined in IEEE Standard 1366™-2012, intended for use in modern information and measurement electricity metering systems. Computational experiments have confirmed the accuracy of calculating the SAIDI and SAIFI indices using the developed algorithm and calculation software. The study results are beneficial for both existing metering systems and those under development with SAIDI and SAIFI reliability indices monitoring functions. Such calculations can be used to determine and maintain the required level of power supply reliability of the power distribution grid consumers.
References
1. Savian F.D.S. et al. Non-Technical Losses: A Systematic Contemporary Article Review. – Renewable and Sustainable Energy Reviews, 2021, 147(8), DOI: 10.1016/j.rser.2021.111205.
2. Данилов М.И. О выявлении и расчёте потерь электроэнергии автоматизированными системами учёта распределительных сетей при несанкционированных потреблениях. – Электричество, 2021, № 6, с. 51–61.
3. Danilov M.I., Romanenko I.G. Identification of Unauthorized Electric-Power Consumption in the Phases of Distribution Networks with Automated Metering Systems. – Power Technology and Engineering, 2022, 56(3), pp. 414–422, DOI: 10.1007/s10749-023-01530-y.
4. Paul Sh. et al. Resilience Assessment and Planning in Power Distribution Systems: Past and Future Considerations. – Renewable and Sustainable Energy Review, 2024, 189, DOI: 10.1016/j.rser.2023.113991.
5. IEEE 1366-2012. IEEE Guide for Electric Power Distribution Reliability Indices, 2012, DOI: 10.1109/IEEESTD.2012.6209381.
6. IEEE 100-2000. The Authoritative Dictionary of IEEE Standards Terms, 7th Ed., 2000, DOI: 10.1109/IEEESTD.2000.322230.
7. Billinton R.R., Acharya J.R. Major Event Day Segmentation. – IEEE Transactions on Power Systems, 2006, 21(3), pp. 1463–1464, DOI: 10.1109/TPWRS.2006.876644.
8. Hann N. et al. 2.5 Beta Methodology—Impact of “Zero SAIDI” Days. – IEEE Transactions on Power Systems, 2013, 28(3), pp. 3517–3518, DOI: 10.1109/TPWRS.2013.2244077.
9. Eto J.H. et al. Evaluating the Performance of the IEEE Standard 1366 Method for Identifying Major Event Days. – IEEE Transactions on Power Systems, 2017, 32(2), pp. 1327–1333, DOI: 10.1109/TPWRS.2016.2585978.
10. Сазыкин В.Г., Багметов А.А. Оптимизация электрической сети по показателям надежности SAIDI, SAIFI с использованием платформы PSS®SINCAL. – Промышленная энергетика, 2019, № 11, c. 2–9.
11. Абдурахманов А.М. и др. Анализ условии секционирования воздушных электрических сетей напряжением 6–20 кВ. – Электричество, 2020, № 8, с. 17–22.
12. Голуб И.И. и др. Алгоритм реконфигурации городской распределительной сети. – Известия РАН. Энергетика, 2020, № 5, с. 3–12.
13. Петров Д.В. и др. Расчет оптимальной численности штата ЭРП и каналов обслуживания КЛ 6–10 кВ городских электрических сетей. – Вестник Северо-Кавказского федерального университета, 2021, № 6(87), с. 7–13.
14. Karpova E.V., Golub I.I. Post-Emergency Reconfiguration of a Distribution Network as a Method for Restoring Power Supply to Consumers. – iPolytech Journal, 2023, 27(1), pp. 74–82, DOI: 10.21285/1814-3520-2023-1-74-82.
15. Кучерявенков А.А., Горожанкин П.А. Централизованное решение по автоматике распредсетей 6–10 кВ с использованием «умных» разъединителей и выключателей нагрузки. – Электроэнергия. Передача и распределение, 2023, № 4(79), с. 90–93.
16. Тивари А., Тивари С. Оценка клиентоориентированных показателей и исследование надежности системы электроснабжения. – Надежность, 2023, т. 23, № 2, с. 49–56.
17. Wang Ch. et al. Markov Decision Process-Based Resilience Enhancement for Distribution Systems: An Approximate Dynamic Programming Approach. – IEEE Transactions on Smart Grid, 2020, 11(3), pp. 2498–2510, DOI: 10.1109/TSG.2019.2956740.
18. Huang Y. et al. Resilient Distribution Networks by Microgrid Formation Using Deep Reinforcement Learning. – IEEE Transactions on Smart Grid, 2022, 13(6), pp. 4918–4930, DOI: 10.1109/TSG.2022.3179593.
19. Wang Ch. et al. Two-Stage Robust Design of Resilient Active Distribution Networks Considering Random Tie Line Outages and Outage Propagation. – IEEE Transactions on Smart Grid, 2023, 14(4), pp. 2630–2644, DOI: 10.1109/TSG.2022.3224605.
20. Чукреев Ю.Я. и др. Свойства надежности при децентрализации энергетики. – Известия РАН. Энергетика, 2023, № 5, с. 19–39.
21. Обоскалов В.П., Абдель Менаем А.С.Х. Моделирование редких событий при расчете показателей балансовой надежности ЭЭС. – Известия РАН. Энергетика, 2021, № 4, с. 24-41.
22. Danilov M.I., Romanenko I.G. Determination of Power Flows and Temperature of Electrical Network Wires of a Power System Steady State. – Power Technology and Engineering, 2023, 56(5), pp. 739–750, DOI: 10.1007/s10749-023-01583-z.
23. Обоскалов В.П., Герасименко А.А. Определение предела мощности, передаваемой по линии электропередачи, при оценке балансовой надежности электроэнергетических систем. – Электричество, 2023, № 7, c. 6–19.
24. Danilov M.I., Romanenko I.G. On the Determination of the Region Border Prior to the Limit Steady Modes of Electric Power Systems by the Tropical Geometry of the Power Balance Equations Analysis Method. – Automation and Remote Control, 2024, 85(1), pp. 73–84, DOI: 10.31857/S0005117924010066
---
Исследование выполнено при финансовой поддержке Министерства науки и высшего образования Российской Федерации в рамках программы «Приоритет-2030». (грант №122060300035-2)
#
1. Savian F.D.S. et al. Non-Technical Losses: A Systematic Contemporary Article Review. – Renewable and Sustainable Energy Reviews, 2021, 147(8), DOI: 10.1016/j.rser.2021.111205.
2. Danilov M.I. Elektrichestvo – in Russ. (Electricity), 2021, No. 6, pp. 51–61.
3. Danilov M.I., Romanenko I.G. Identification of Unauthorized Electric-Power Consumption in the Phases of Distribution Networks with Automated Metering Systems. – Power Technology and Engineering, 2022, 56(3), pp. 414–422, DOI: 10.1007/s10749-023-01530-y.
4. Paul Sh. et al. Resilience Assessment and Planning in Power Distribution Systems: Past and Future Considerations. – Renewable and Sustainable Energy Review, 2024, 189, DOI: 10.1016/j.rser.2023.113991.
5. IEEE 1366-2012. IEEE Guide for Electric Power Distribution Reliability Indices, 2012, DOI: 10.1109/IEEESTD.2012.6209381.
6. IEEE Std 100-2000. The Authoritative Dictionary of IEEE Standards Terms, 7th Ed., 2000, DOI: 10.1109/IEEESTD.2000.322230.
7. Billinton R.R., Acharya J.R. Major Event Day Segmentation. – IEEE Transactions on Power Systems, 2006, 21(3), pp. 1463–1464, DOI: 10.1109/TPWRS.2006.876644.
8. Hann N. et al. 2.5 Beta Methodology—Impact of “Zero SAIDI” Days. – IEEE Transactions on Power Systems, 2013, 28(3), pp. 3517–3518, DOI: 10.1109/TPWRS.2013.2244077.
9. Eto J.H. et al. Evaluating the Performance of the IEEE Standard 1366 Method for Identifying Major Event Days. – IEEE Transactions on Power Systems, 2017, 32(2), pp. 1327–1333, DOI: 10.1109/TPWRS. 2016.2585978.
10. Sazykin V.G., Bagmetov А.А. Promyshlennaya energetika – in Russ. (Industrial Power Engineering), 2019, No. 11, pp. 2–9.
11. Abdurahmanov A.M. et al. Elektrichestvo – in Russ. (Electricity), 2020, No. 8, pp. 17–22.
12. Golub I.I. et al. Izvestiya RAN. Energetika – in Russ. (News of the RAS. Power Engineering), 2020, No. 5, pp. 3–12.
13. Petrov D.V. et al. Vestnik Severo-Kavkazskogo Federal'nogo Universiteta – in Russ. (Bulletin of the North Caucasus Federal University), 2021, No. 6(87), pp. 7–13.
14. Karpova E.V., Golub I.I. Post-Emergency Reconfiguration of a Distribution Network as a Method for Restoring Power Supply to Consumers. – iPolytech Journal, 2023, 27(1), pp. 74–82, DOI: 10.21285/1814-3520-2023-1-74-82.
15. Kucheryavenkov A.A., Gorozhankin P.А. Elektroenergiya. Peredacha i raspredelenie – in Russ. (Electricity. Transmission and Distribution), 2023, No. 4(79), pp. 90–93.
16. Tivari A., Tivari S. Nadezhnost' – in Russ. (Reliability), 2023, vol. 23, No. 2, pp. 49–56.
17. Wang Ch. et al. Markov Decision Process-Based Resilience Enhancement for Distribution Systems: An Approximate Dynamic Programming Approach. – IEEE Transactions on Smart Grid, 2020, 11(3), pp. 2498–2510, DOI: 10.1109/TSG.2019.2956740.
18. Huang Y. et al. Resilient Distribution Networks by Microgrid Formation Using Deep Reinforcement Learning. – IEEE Transactions on Smart Grid, 2022, 13(6), pp. 4918–4930, DOI: 10.1109/TSG.2022. 3179593.
19. Wang Ch. et al. Two-Stage Robust Design of Resilient Active Distribution Networks Considering Random Tie Line Outages and Outage Propagation. – IEEE Transactions on Smart Grid, 2023, 14(4), pp. 2630–2644, DOI: 10.1109/TSG.2022.3224605.
20. Chukreev Yu.Ya. et al. Izvestiya RAN. Energetika – in Russ. (News of the RAS. Power Engineering), 2023, No. 5, pp. 19–39.
21. Oboskalov V.P., Abdel’ Menaem А.S.H. Izvestiya RAN. Energetika – in Russ. (News of the RAS. Power Engineering), 2021, No. 4, pp. 24-41.
22. Danilov M.I., Romanenko I.G. Determination of Power Flows and Temperature of Electrical Network Wires of a Power System Steady State. – Power Technology and Engineering, 2023, 56(5), pp. 739–750, DOI: 10.1007/s10749-023-01583-z.
23. Oboskalov V.P., Gerasimenko А.А. Elektrichestvo – in Russ. (Electricity), 2023, No. 7, pp. 6–19.
24. Danilov M.I., Romanenko I.G. On the Determination of the Region Border Prior to the Limit Steady Modes of Electric Power Systems by the Tropical Geometry of the Power Balance Equations Analysis Method. – Automation and Remote Control, 2024, 85(1), pp. 73–84, DOI: 10.31857/S0005117924010066
---
The study was performed with the financial support of the Ministry of Science and Higher Education of the Russian Federation as part of the Priority-2030 program (grant no. 122060300035-2)
2. Данилов М.И. О выявлении и расчёте потерь электроэнергии автоматизированными системами учёта распределительных сетей при несанкционированных потреблениях. – Электричество, 2021, № 6, с. 51–61.
3. Danilov M.I., Romanenko I.G. Identification of Unauthorized Electric-Power Consumption in the Phases of Distribution Networks with Automated Metering Systems. – Power Technology and Engineering, 2022, 56(3), pp. 414–422, DOI: 10.1007/s10749-023-01530-y.
4. Paul Sh. et al. Resilience Assessment and Planning in Power Distribution Systems: Past and Future Considerations. – Renewable and Sustainable Energy Review, 2024, 189, DOI: 10.1016/j.rser.2023.113991.
5. IEEE 1366-2012. IEEE Guide for Electric Power Distribution Reliability Indices, 2012, DOI: 10.1109/IEEESTD.2012.6209381.
6. IEEE 100-2000. The Authoritative Dictionary of IEEE Standards Terms, 7th Ed., 2000, DOI: 10.1109/IEEESTD.2000.322230.
7. Billinton R.R., Acharya J.R. Major Event Day Segmentation. – IEEE Transactions on Power Systems, 2006, 21(3), pp. 1463–1464, DOI: 10.1109/TPWRS.2006.876644.
8. Hann N. et al. 2.5 Beta Methodology—Impact of “Zero SAIDI” Days. – IEEE Transactions on Power Systems, 2013, 28(3), pp. 3517–3518, DOI: 10.1109/TPWRS.2013.2244077.
9. Eto J.H. et al. Evaluating the Performance of the IEEE Standard 1366 Method for Identifying Major Event Days. – IEEE Transactions on Power Systems, 2017, 32(2), pp. 1327–1333, DOI: 10.1109/TPWRS.2016.2585978.
10. Сазыкин В.Г., Багметов А.А. Оптимизация электрической сети по показателям надежности SAIDI, SAIFI с использованием платформы PSS®SINCAL. – Промышленная энергетика, 2019, № 11, c. 2–9.
11. Абдурахманов А.М. и др. Анализ условии секционирования воздушных электрических сетей напряжением 6–20 кВ. – Электричество, 2020, № 8, с. 17–22.
12. Голуб И.И. и др. Алгоритм реконфигурации городской распределительной сети. – Известия РАН. Энергетика, 2020, № 5, с. 3–12.
13. Петров Д.В. и др. Расчет оптимальной численности штата ЭРП и каналов обслуживания КЛ 6–10 кВ городских электрических сетей. – Вестник Северо-Кавказского федерального университета, 2021, № 6(87), с. 7–13.
14. Karpova E.V., Golub I.I. Post-Emergency Reconfiguration of a Distribution Network as a Method for Restoring Power Supply to Consumers. – iPolytech Journal, 2023, 27(1), pp. 74–82, DOI: 10.21285/1814-3520-2023-1-74-82.
15. Кучерявенков А.А., Горожанкин П.А. Централизованное решение по автоматике распредсетей 6–10 кВ с использованием «умных» разъединителей и выключателей нагрузки. – Электроэнергия. Передача и распределение, 2023, № 4(79), с. 90–93.
16. Тивари А., Тивари С. Оценка клиентоориентированных показателей и исследование надежности системы электроснабжения. – Надежность, 2023, т. 23, № 2, с. 49–56.
17. Wang Ch. et al. Markov Decision Process-Based Resilience Enhancement for Distribution Systems: An Approximate Dynamic Programming Approach. – IEEE Transactions on Smart Grid, 2020, 11(3), pp. 2498–2510, DOI: 10.1109/TSG.2019.2956740.
18. Huang Y. et al. Resilient Distribution Networks by Microgrid Formation Using Deep Reinforcement Learning. – IEEE Transactions on Smart Grid, 2022, 13(6), pp. 4918–4930, DOI: 10.1109/TSG.2022.3179593.
19. Wang Ch. et al. Two-Stage Robust Design of Resilient Active Distribution Networks Considering Random Tie Line Outages and Outage Propagation. – IEEE Transactions on Smart Grid, 2023, 14(4), pp. 2630–2644, DOI: 10.1109/TSG.2022.3224605.
20. Чукреев Ю.Я. и др. Свойства надежности при децентрализации энергетики. – Известия РАН. Энергетика, 2023, № 5, с. 19–39.
21. Обоскалов В.П., Абдель Менаем А.С.Х. Моделирование редких событий при расчете показателей балансовой надежности ЭЭС. – Известия РАН. Энергетика, 2021, № 4, с. 24-41.
22. Danilov M.I., Romanenko I.G. Determination of Power Flows and Temperature of Electrical Network Wires of a Power System Steady State. – Power Technology and Engineering, 2023, 56(5), pp. 739–750, DOI: 10.1007/s10749-023-01583-z.
23. Обоскалов В.П., Герасименко А.А. Определение предела мощности, передаваемой по линии электропередачи, при оценке балансовой надежности электроэнергетических систем. – Электричество, 2023, № 7, c. 6–19.
24. Danilov M.I., Romanenko I.G. On the Determination of the Region Border Prior to the Limit Steady Modes of Electric Power Systems by the Tropical Geometry of the Power Balance Equations Analysis Method. – Automation and Remote Control, 2024, 85(1), pp. 73–84, DOI: 10.31857/S0005117924010066
---
Исследование выполнено при финансовой поддержке Министерства науки и высшего образования Российской Федерации в рамках программы «Приоритет-2030». (грант №122060300035-2)
#
1. Savian F.D.S. et al. Non-Technical Losses: A Systematic Contemporary Article Review. – Renewable and Sustainable Energy Reviews, 2021, 147(8), DOI: 10.1016/j.rser.2021.111205.
2. Danilov M.I. Elektrichestvo – in Russ. (Electricity), 2021, No. 6, pp. 51–61.
3. Danilov M.I., Romanenko I.G. Identification of Unauthorized Electric-Power Consumption in the Phases of Distribution Networks with Automated Metering Systems. – Power Technology and Engineering, 2022, 56(3), pp. 414–422, DOI: 10.1007/s10749-023-01530-y.
4. Paul Sh. et al. Resilience Assessment and Planning in Power Distribution Systems: Past and Future Considerations. – Renewable and Sustainable Energy Review, 2024, 189, DOI: 10.1016/j.rser.2023.113991.
5. IEEE 1366-2012. IEEE Guide for Electric Power Distribution Reliability Indices, 2012, DOI: 10.1109/IEEESTD.2012.6209381.
6. IEEE Std 100-2000. The Authoritative Dictionary of IEEE Standards Terms, 7th Ed., 2000, DOI: 10.1109/IEEESTD.2000.322230.
7. Billinton R.R., Acharya J.R. Major Event Day Segmentation. – IEEE Transactions on Power Systems, 2006, 21(3), pp. 1463–1464, DOI: 10.1109/TPWRS.2006.876644.
8. Hann N. et al. 2.5 Beta Methodology—Impact of “Zero SAIDI” Days. – IEEE Transactions on Power Systems, 2013, 28(3), pp. 3517–3518, DOI: 10.1109/TPWRS.2013.2244077.
9. Eto J.H. et al. Evaluating the Performance of the IEEE Standard 1366 Method for Identifying Major Event Days. – IEEE Transactions on Power Systems, 2017, 32(2), pp. 1327–1333, DOI: 10.1109/TPWRS. 2016.2585978.
10. Sazykin V.G., Bagmetov А.А. Promyshlennaya energetika – in Russ. (Industrial Power Engineering), 2019, No. 11, pp. 2–9.
11. Abdurahmanov A.M. et al. Elektrichestvo – in Russ. (Electricity), 2020, No. 8, pp. 17–22.
12. Golub I.I. et al. Izvestiya RAN. Energetika – in Russ. (News of the RAS. Power Engineering), 2020, No. 5, pp. 3–12.
13. Petrov D.V. et al. Vestnik Severo-Kavkazskogo Federal'nogo Universiteta – in Russ. (Bulletin of the North Caucasus Federal University), 2021, No. 6(87), pp. 7–13.
14. Karpova E.V., Golub I.I. Post-Emergency Reconfiguration of a Distribution Network as a Method for Restoring Power Supply to Consumers. – iPolytech Journal, 2023, 27(1), pp. 74–82, DOI: 10.21285/1814-3520-2023-1-74-82.
15. Kucheryavenkov A.A., Gorozhankin P.А. Elektroenergiya. Peredacha i raspredelenie – in Russ. (Electricity. Transmission and Distribution), 2023, No. 4(79), pp. 90–93.
16. Tivari A., Tivari S. Nadezhnost' – in Russ. (Reliability), 2023, vol. 23, No. 2, pp. 49–56.
17. Wang Ch. et al. Markov Decision Process-Based Resilience Enhancement for Distribution Systems: An Approximate Dynamic Programming Approach. – IEEE Transactions on Smart Grid, 2020, 11(3), pp. 2498–2510, DOI: 10.1109/TSG.2019.2956740.
18. Huang Y. et al. Resilient Distribution Networks by Microgrid Formation Using Deep Reinforcement Learning. – IEEE Transactions on Smart Grid, 2022, 13(6), pp. 4918–4930, DOI: 10.1109/TSG.2022. 3179593.
19. Wang Ch. et al. Two-Stage Robust Design of Resilient Active Distribution Networks Considering Random Tie Line Outages and Outage Propagation. – IEEE Transactions on Smart Grid, 2023, 14(4), pp. 2630–2644, DOI: 10.1109/TSG.2022.3224605.
20. Chukreev Yu.Ya. et al. Izvestiya RAN. Energetika – in Russ. (News of the RAS. Power Engineering), 2023, No. 5, pp. 19–39.
21. Oboskalov V.P., Abdel’ Menaem А.S.H. Izvestiya RAN. Energetika – in Russ. (News of the RAS. Power Engineering), 2021, No. 4, pp. 24-41.
22. Danilov M.I., Romanenko I.G. Determination of Power Flows and Temperature of Electrical Network Wires of a Power System Steady State. – Power Technology and Engineering, 2023, 56(5), pp. 739–750, DOI: 10.1007/s10749-023-01583-z.
23. Oboskalov V.P., Gerasimenko А.А. Elektrichestvo – in Russ. (Electricity), 2023, No. 7, pp. 6–19.
24. Danilov M.I., Romanenko I.G. On the Determination of the Region Border Prior to the Limit Steady Modes of Electric Power Systems by the Tropical Geometry of the Power Balance Equations Analysis Method. – Automation and Remote Control, 2024, 85(1), pp. 73–84, DOI: 10.31857/S0005117924010066
---
The study was performed with the financial support of the Ministry of Science and Higher Education of the Russian Federation as part of the Priority-2030 program (grant no. 122060300035-2)
Published
2024-07-31
Issue
Section
Article
