On Identifying and Calculating Electricity Losses with Automated Metering Systems in Distribution Networks in Case of Unauthorized Consumption
Keywords:
distribution network, unauthorized electricity tap, three-phase circuit, network parameters, section impedances, parameter identification, calculation method
Abstract
A 0.4 kV distribution network equipped with an automated information and measurement electricity metering system is considered. It is assumed that the metering system receives data on active and reactive power, and on the effective voltage values that correspond to the same time interval and are received at the distribution network beginning and from all subscribers. It is also assumed that the impedances of the phase wires are the same for each inter-subscriber section of the network, but differ from the impedance of the neutral one and are considered to be unknown during the initial calculation. The problem is formulated as follows: arrange, by means of the metering system, online calculation and monitoring of non-technical losses of electric energy in the network that contains several simultaneously operating subscribers connected to the network phases, from which incorrect energy consumption data are received. It is also necessary to identify such subscribers and evaluate the amounts of their unauthorized taps of electricity. The known approach to solving the formulated problem is analyzed, and its shortcomings are revealed. A new method is proposed, which is based on taking into account the phasor relationships for the operating parameters that determine the three-phase network electrical state and calculating the impedances of the distribution network inter-subscriber sections when there are no unauthorized taps of electricity and the currents through these sections when there are unauthorized taps of electricity. By using the proposed method, it becomes possible to determine non-technical losses of electricity in the distribution network for the reporting period and to identify subscribers with incorrect electricity consumption data. It is shown that the unaccounted consumption of electricity in each individual subscriber can be calculated if there are several subscribers with unauthorized taps of electricity connected to one phase of the network, whereas there are no more than one of such taps in the other phases. The obtained results can find application both in existing automated electricity metering systems and in the development of new ones.
References
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23. Ni F., Nguyen P.H., Cobben J.F.G. et al. Three-phase state estimation in the medium-voltage network with aggregated smart meter data. – International Journal of Electrical Power & Energy Systems, 2018, vol. 98, pp. 463–473.
24. Кононов Ю.Г., Рыбасова О.С., Михайленко В.С. Уточнение параметров участков линий сети среднего напряжения по данным синхронных измерений. – Известия вузов. Электромеханика, 2018, т. 61, № 1, c. 77–84.
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#
1. Ahmad T., Chen H., Wang J. et al. Review of various mode-ling techniques for the detection of electricity theft in smart grid environment. – Renewable and Sustainable Energy Reviews, 2018, vol. 82, pp. 2916–2933.
2. Messinis G.M., Hatziargyriou N.D. Review of non-technical loss detection methods. – Electric Power Systems Research, 2018, vol. 158, pp. 250–266.
3. Mustafa M., Hamadneh N., Alshammari N. et al. Detection of Non-Technical Losses in Power Utilities – A Comprehensive Systematic Review. – Energies, 2020, vol. 13, No. 18, 4727, doi: 10.3390/en13184727.
4. Yip S.C., Tan W.N., Tan C.K. et al. An anomaly detection framework for identifying energy theft and defective meters in smart grids. – International Journal of Electrical Power & Energy Systems, 2018, vol. 101, pp. 189–203.
5. Leite J.B., Mantovani J.R.S. Detecting and locating non-technical losses in modern distribution networks. – IEEE Transactions on Smart Grid, 2018, vol. 9, No. 2, pp. 1023–1032.
6. Biswas P., Cai H., Zhou B. et al. Electricity Theft Pinpointing through Correlation Analysis of Master and Individual Meter Readings. – IEEE Transactions on Smart Grid, 2019, vol. 11(4), pp. 3031–3042, doi: 10.1109/TSG.2019.2961136.
7. Buzau M., Tejedor-Aguilera J., Cruz-Romero P. et al. Detection of non-technical losses using smart meter data and supervised learning. – IEEE Transactions on Smart Grid, 2019, vol. 10. pp. 2661–2670.
8. Messinis G.M., Rigas A.E., Hatziargyriou N.D. A Hybrid Method for Non-Technical Loss Detection in Smart Distribution Grids. – IEEE Transactions on Smart Grid, 2019, vol. 10, No. 6, pp. 6080–6091, doi: 10.1109/TSG.2019.2896381.
9. Tariq M., Poor H.V. Electricity Theft Detection and Localization in Grid-Tied Microgrids. – IEEE Transactions on Smart Grid, 2018, vol. 9, No.3, pp. 1920–1929, doi: 10.1109/TSG.2016.2602660.
10. Danilov M.I., Romanenko I.G. Izvestija vuzov. Elektromekhanika – in Russ. (Russian Electromechanics), 2019, vol. 61, No. 4, pp. 90–96.
11. Omorov T.T. Elektrichestvo – in Russ. (Electricity), 2017, No. 9, pp. 17–23.
12. Gao Y., Foggo B., Yu N. A Physically Inspired Data-Driven Model for Electricity Theft Detection with Smart Meter Data. – IEEE Transactions on Industrial Informatics, 2019, vol.14, No. 8, pp. 5076–5088, doi: 10.1109/TII.2019.2898171.
13. Ferreira T.S.D, Trindade F.C.L., Vieira J.C.M. Load Flow-Based Method for Nontechnical Electrical Loss Detection and Location in Distribution Systems Using Smart Meters. – IEEE Transactions on Power Systems, 2020, vol. 35, pp. 3671–3681.
14. Omorov T.T., Takyrbashev B.K., Osmonova R.Ch., Koiba-garov T.Zh. Vestnik YUUrGU. Seriya «Energetika» – in Russ. (Bulletin of the South Ural State University. Ser. Power Engineering), 2018, vol. 18, No. 2, pp. 48–54, doi: 10.14529/power180206.
15. Omorov T.T., Tatyrbashev B.K., Koibagarov T.Zh., Osmonova R.Ch. Elektricheskie stantsii – in Russ. (Power Station), 2019, No. 2, pp. 37–41.
16. Danilov M.I., Romanenko I.G. Elektroenergiya. Peredacha i raspredelenie – in Russ. (Electricity. Transmission and Distribution), 2019, vol. 61, No. 4, pp. 90–96.
17. Pappu S.J., Bhatt N., Pasumarthy R. et.al. Identifying Topology of Low Voltage Distribution Networks Based on Smart Meter Data. – IEEE Transactions on Smart Grid, 2018, vol. 9, pp. 5113–5122.
18. Zhdaneev O.V., Zuev S.S., Kostromin I.S., Khafizov R.Z. Energetik – in Russ. (Energy specialist), 2020, No.11, pp.9–19.
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20. Danilov M.I., Romanenko I.G. Vestnik YUUrGU. Seriya «Energetika» – in Russ. (Bulletin of the South Ural State University. Ser. Power Engineering), 2019, vol. 19, No. 4, pp. 87–94, doi: 10.14529/power190410.
21. Danilov M.I., Romanenko I.G. Vestnik YUUrGU. Seriya «Energetika» – in Russ. (Bulletin of the South Ural State University. Ser. Power Engineering), 2020, vol. 20, No. 2, pp. 5–14, doi: 10.14529/power200201.
22. Danilov M.I., Romanenko I.G. Energetik – in Russ. (Energy specialist), 2021, No.5, pp.17–21.
23. Ni F., Nguyen P.H., Cobben J.F.G. et al. Three-phase state estimation in the medium-voltage network with aggregated smart meter data. – International Journal of Electrical Power & Energy Systems, 2018, vol. 98, pp. 463–473.
24. Kononov Yu.G., Rybasova O.S., Mikhailenko V.S. Izvestija vuzov. Elektromekhanika – in Russ. (Russian Electromechanics), 2018, vol. 61, No. 1, pp. 77–84, doi: 10.17213/0136-3360-2018-1-77-84.
25. Pegoraro P.A., Brady K., Castello P. et al. Compensation of Systematic Measurement Errors in a PMU-Based Monitoring System for Electric Distribution Grids. – IEEE Transactions on Instrumentation and Measurement, 2019, vol. 68, pp. 3871–3882.
26. Kurganov S.A., Filaretov V.V. Elektrichestvo – in Russ. (Electricity), 2021, No. 1, pp. 61–67.
2. Messinis G.M., Hatziargyriou N.D. Review of non-technical loss detection methods. – Electric Power Systems Research, 2018, vol. 158, pp. 250–266.
3. Mustafa M., Hamadneh N., Alshammari N. et al. Detection of Non-Technical Losses in Power Utilities – A Comprehensive Systematic Review. – Energies, 2020, vol. 13, No. 18, 4727, doi: 10.3390/en13184727.
4. Yip S.C., Tan W.N., Tan C.K. et al. An anomaly detection framework for identifying energy theft and defective meters in smart grids. – International Journal of Electrical Power & Energy Systems, 2018, vol. 101, pp. 189–203.
5. Leite J.B., Mantovani J.R.S. Detecting and locating non-technical losses in modern distribution networks. – IEEE Transactions on Smart Grid, 2018, vol. 9, No. 2, pp. 1023–1032.
6. Biswas P., Cai H., Zhou B. et al. Electricity Theft Pinpointing through Correlation Analysis of Master and Individual Meter Readings. – IEEE Transactions on Smart Grid, 2019, vol. 11(4), pp. 3031–3042, doi: 10.1109/TSG.2019.2961136.
7. Buzau M., Tejedor-Aguilera J., Cruz-Romero P. et al. Detection of non-technical losses using smart meter data and supervised learning. – IEEE Transactions on Smart Grid, 2019, vol. 10. pp. 2661–2670.
8. Messinis G.M., Rigas A.E., Hatziargyriou N.D. A Hybrid Method for Non-Technical Loss Detection in Smart Distribution Grids. – IEEE Transactions on Smart Grid, 2019, vol. 10, No. 6, pp. 6080–6091, doi: 10.1109/TSG.2019.2896381.
9. Tariq M., Poor H.V. Electricity Theft Detection and Localization in Grid-Tied Microgrids. – IEEE Transactions on Smart Grid, 2018, vol. 9, No.3, pp. 1920–1929, doi: 10.1109/TSG.2016.2602660.
10. Данилов М.И, Романенко И.Г. Метод выявления мест неконтролируемого потребления электроэнергии в электрических сетях 0,4 кВ. – Известия вузов. Электромеханика, 2019, т. 62, № 4. c. 90–96.
11. Оморов Т.Т. Оценка влияния несимметрии токов и напряжений на потери электроэнергии в распределительной сети c использованием АСКУЭ. – Электричество, 2017, № 9, c. 17–23.
12. Gao Y., Foggo B., Yu N. A Physically Inspired Data-Driven Model for Electricity Theft Detection with Smart Meter Data. – IEEE Transactions on Industrial Informatics, 2019, vol.14, No. 8, pp. 5076–5088, doi: 10.1109/TII.2019.2898171.
13. Ferreira T.S.D, Trindade F.C.L., Vieira J.C.M. Load Flow-Based Method for Nontechnical Electrical Loss Detection and Location in Distribution Systems Using Smart Meters. – IEEE Transactions on Power Systems, 2020, vol. 35, pp. 3671–3681.
14. Оморов Т.Т., Такырбашев Б.К., Осмонова Р.Ч. и др. Идентификация утечек тока в распределительных сетях по данным АСКУЭ. – Вестник ЮУрГУ. Серия «Энергетика», 2018, т. 18, № 2, c. 48–54, doi: 10.14529/power180206.
15. Оморов Т.Т., Такырбашев Б.К., Койбагаров Т.Д. и др. Метод идентификации несанкционированного потребления электроэнергии в распредсети по данным АСКУЭ. – Электрические станции, 2019, № 2 (1051), c. 37–41.
16. Данилов М.И, Романенко И.Г. Метод расчета и мониторинга нетехнических потерь электроэнергии в распределительной сети 380 В, контролируемой системой учета. – Электроэнергия. Передача и распределение, 2020, № 6(63), c. 46–53.
17. Pappu S.J., Bhatt N., Pasumarthy R. et.al. Identifying Topology of Low Voltage Distribution Networks Based on Smart Meter Data. – IEEE Transactions on Smart Grid, 2018, vol. 9, pp. 5113–5122.
18. Жданеев О.В., Зуев С.С., Костромин И.С. и др. К вопросу создания средств интеллектуального учёта на основе отечественной электронной компонентной базы. – Энергетик, 2020, № 11, c. 9–19.
19. Кузькина Я.И., Голуб И.И. Идентификация фаз подключения интеллектуальных счетчиков в низковольтной распределительной сети. – Вестник Иркутского государственного технического университета, 2020, т. 24, № 1, c. 135–144.
20. Данилов М.И, Романенко И.Г. К проблеме определения векторов тока и напряжения в распределительной сети по данным АИИС КУЭ. – Вестник ЮУрГУ. Серия «Энергетика», 2019, т. 19, № 4. c. 87–94, doi: 10.14529/power190410.
21. Данилов М.И, Романенко И.Г. К проблеме определения параметров распределительной сети по данным АИИС КУЭ. – Вестник ЮУрГУ. Серия «Энергетика», 2020, т. 20, № 2, c. 5–14, doi: 10.14529/power200201.
22. Данилов М.И, Романенко И.Г. Метод расчёта и мониторинга параметров распределительной сети, контролируемой автоматизированной информационно-измерительной системой учёта электроэнергии. – Энергетик, 2021, №5, c. 17–21.
23. Ni F., Nguyen P.H., Cobben J.F.G. et al. Three-phase state estimation in the medium-voltage network with aggregated smart meter data. – International Journal of Electrical Power & Energy Systems, 2018, vol. 98, pp. 463–473.
24. Кононов Ю.Г., Рыбасова О.С., Михайленко В.С. Уточнение параметров участков линий сети среднего напряжения по данным синхронных измерений. – Известия вузов. Электромеханика, 2018, т. 61, № 1, c. 77–84.
25. Pegoraro P.A., Brady K., Castello P. et al. Compensation of Systematic Measurement Errors in a PMU-Based Monitoring System for Electric Distribution Grids. – IEEE Transactions on Instrumentation and Measurement, 2019, vol. 68, pp. 3871–3882.
26. Курганов С.А., Филаретов В.В. Диагностика линейных электрических цепей по узлам с наименьшим числом неизвестных параметров. – Электричество, 2021, № 1, c. 61–67.
#
1. Ahmad T., Chen H., Wang J. et al. Review of various mode-ling techniques for the detection of electricity theft in smart grid environment. – Renewable and Sustainable Energy Reviews, 2018, vol. 82, pp. 2916–2933.
2. Messinis G.M., Hatziargyriou N.D. Review of non-technical loss detection methods. – Electric Power Systems Research, 2018, vol. 158, pp. 250–266.
3. Mustafa M., Hamadneh N., Alshammari N. et al. Detection of Non-Technical Losses in Power Utilities – A Comprehensive Systematic Review. – Energies, 2020, vol. 13, No. 18, 4727, doi: 10.3390/en13184727.
4. Yip S.C., Tan W.N., Tan C.K. et al. An anomaly detection framework for identifying energy theft and defective meters in smart grids. – International Journal of Electrical Power & Energy Systems, 2018, vol. 101, pp. 189–203.
5. Leite J.B., Mantovani J.R.S. Detecting and locating non-technical losses in modern distribution networks. – IEEE Transactions on Smart Grid, 2018, vol. 9, No. 2, pp. 1023–1032.
6. Biswas P., Cai H., Zhou B. et al. Electricity Theft Pinpointing through Correlation Analysis of Master and Individual Meter Readings. – IEEE Transactions on Smart Grid, 2019, vol. 11(4), pp. 3031–3042, doi: 10.1109/TSG.2019.2961136.
7. Buzau M., Tejedor-Aguilera J., Cruz-Romero P. et al. Detection of non-technical losses using smart meter data and supervised learning. – IEEE Transactions on Smart Grid, 2019, vol. 10. pp. 2661–2670.
8. Messinis G.M., Rigas A.E., Hatziargyriou N.D. A Hybrid Method for Non-Technical Loss Detection in Smart Distribution Grids. – IEEE Transactions on Smart Grid, 2019, vol. 10, No. 6, pp. 6080–6091, doi: 10.1109/TSG.2019.2896381.
9. Tariq M., Poor H.V. Electricity Theft Detection and Localization in Grid-Tied Microgrids. – IEEE Transactions on Smart Grid, 2018, vol. 9, No.3, pp. 1920–1929, doi: 10.1109/TSG.2016.2602660.
10. Danilov M.I., Romanenko I.G. Izvestija vuzov. Elektromekhanika – in Russ. (Russian Electromechanics), 2019, vol. 61, No. 4, pp. 90–96.
11. Omorov T.T. Elektrichestvo – in Russ. (Electricity), 2017, No. 9, pp. 17–23.
12. Gao Y., Foggo B., Yu N. A Physically Inspired Data-Driven Model for Electricity Theft Detection with Smart Meter Data. – IEEE Transactions on Industrial Informatics, 2019, vol.14, No. 8, pp. 5076–5088, doi: 10.1109/TII.2019.2898171.
13. Ferreira T.S.D, Trindade F.C.L., Vieira J.C.M. Load Flow-Based Method for Nontechnical Electrical Loss Detection and Location in Distribution Systems Using Smart Meters. – IEEE Transactions on Power Systems, 2020, vol. 35, pp. 3671–3681.
14. Omorov T.T., Takyrbashev B.K., Osmonova R.Ch., Koiba-garov T.Zh. Vestnik YUUrGU. Seriya «Energetika» – in Russ. (Bulletin of the South Ural State University. Ser. Power Engineering), 2018, vol. 18, No. 2, pp. 48–54, doi: 10.14529/power180206.
15. Omorov T.T., Tatyrbashev B.K., Koibagarov T.Zh., Osmonova R.Ch. Elektricheskie stantsii – in Russ. (Power Station), 2019, No. 2, pp. 37–41.
16. Danilov M.I., Romanenko I.G. Elektroenergiya. Peredacha i raspredelenie – in Russ. (Electricity. Transmission and Distribution), 2019, vol. 61, No. 4, pp. 90–96.
17. Pappu S.J., Bhatt N., Pasumarthy R. et.al. Identifying Topology of Low Voltage Distribution Networks Based on Smart Meter Data. – IEEE Transactions on Smart Grid, 2018, vol. 9, pp. 5113–5122.
18. Zhdaneev O.V., Zuev S.S., Kostromin I.S., Khafizov R.Z. Energetik – in Russ. (Energy specialist), 2020, No.11, pp.9–19.
19. Kuzkina Ya.I., Golub I.I. Vestnik Irkutskogo gosudarstvenno-go tehnicheskogo universiteta – in Russ. (Proceedings of Irkutsk State Technical University), 2020, vol. 24(1), pp. 135–144.
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