Identification and Detection of Low-Frequency Oscillation Sources Based on Synchronized Phasor Measurements
Keywords:
current and voltage synchrophasors, phasor measurement units, Wide Area Monitoring System, low-frequency oscillations
Abstract
Monitoring the oscillatory stability of power systems is among the most promising applications of the synchronized phasor measurement (SPM) technology. The presence of high-amplitude low-frequency oscillations (LFOs) and the associated synchronous swings adversely affect the operation of power plant generators and can lead to an emergency operating mode of the power system. The article provides a brief overview of existing methods for identifying oscillatory phenomena in power systems and examines the most common methods for locating LFO sources. The reasons for the insufficient sensitivity of these methods are analyzed, and several improvements are proposed, including enhanced identification of LFOs, the use of data array on retrospective SPM to reveal the dynamics of oscillatory processes, and the inclusion of additional parameters in recognizing the oscillation sources. This, in turn, requires further development of the SPM theory in regard of analyzing synchronized phasors (synchrophasors) of electromechanical transients. In the study of electromechanical transients using the proposed analysis methods, additional parameters for recognizing LFO sources are identified. The advantages of using a data array on low-frequency current mode phasors for obtaining information about the propagation of oscillations in the power system are substantiated. Methods for visualizing the raw data and LFO analysis results are proposed. The architecture of a computerized system being developed for analyzing SPM data streams is presented. Tools for testing LFO analysis software have been developed, including those from the viewpoint of synthesizing data on large-scale oscillatory processes. This article summarizes and expands the previous studies of the authors related to identifying and locating LFO sources in the power system.
References
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#
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2. Zhukov A.V. et al. Methods for Determination of Parameters Variation of the Electrical Mode of the Power System and Their Use for the Power System Control Objectives. – CIGRE Session, 2018, Paris.
3. ПК PhasorPoint [Electron. resource], URL: https://www.rtsoft.ru/catalog/programmnoe-obespechenie/prikladnoe-po-i-prilozheniya/phasor-point/ (Date of appeal 31.05.2024).
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2. Zhukov A.V. et al. Methods for Determination of Parameters Variation of the Electrical Mode of the Power System and Their Use for the Power System Control Objectives. – CIGRE Session, 2018, Paris.
3. ПК PhasorPoint [Электрон. ресурс], URL: https://www.rtsoft.ru/catalog/programmnoe-obespechenie/prikladnoe-po-i-prilozheniya/phasor-point/ (дата обращения 31.05.2024).
4. Сенюк М.Д. и др. Методы оценки низкочастотных колебаний в энергосистеме. – Электричество, 2024, № 8, с. 4–14.
5. Wang B., Maslennikov S. IEEE-NASPI Oscillation Source Location Contest-Case Development and Results. – Tech. rep. National Renewable Energy Lab. (NREL), Golden, CO (United States), 2021.
6. Popov A.I. et al. Examples of Processing Low-Frequency Oscillations in Russia and Ways to Improve the Analysis. – 2022 International Conference on Smart Grid Synchronized Measurements and Analytics, 2022, DOI:10.1109/SGSMA51733.2022.9805996.
7. Wang B., Maslennikov S. Synchrophasor Data for Oscillation Source Location. – Synchrophasor Technology: Real-time Operation of Power Networks, 2023, 190(1), DOI:10.1049/PBPO190E_ch1.
8. Chen L., Min Y., Hu W. An Energy-Based Method for Location of Power System Oscillation Source. – IEEE Transactions on Power Systems, 2012, 28(2), pp. 828–836, DOI: 10.1109/TPWRS.2012.2211627.
9. Maslennikov S., Wang B., Litvinov E. Dissipating Energy Flow Method for Locating the Source of Sustained Oscillations. – International Journal of Electrical Power & Energy Systems, 2017, pp. 55–62, DOI:10.1016/j.ijepes.2016.12.010.
10. Haugdal H., Uhlen K. Mode Shape Estimation Using Complex Principal Component Analysis and K-Means Clustering. – International Conference on Smart Grid Synchronized Measurements and Analytics, 2019, DOI:10.1109/SGSMA.2019.8784556.
11. Rahul S., Sunitha R. Nonlinear Nonstationary Analysis Techniques for Mode Shape Estimation in Power Systems. – Innovations in Power and Advanced Computing Technologies, 2019, vol. 1, DOI:10.1109/i-PACT44901.2019.8960158.
12. Wang W. et al. Model-Less Source Location for Forced Oscillation Based on Synchrophasor and Moving Fast Fourier Transformation. – IEEE PES Innovative Smart Grid Technologies Europe, 2020, pp. 404–408, DOI:10.1109/ISGT-Europe47291.2020.9248914.
13. Banna H.Ul., Solanki S.K., Solanki J. Data-Driven Disturbance Source Identification for Power System Oscillations Using Credibility Search Ensemble Learning. – IET Smart Grid, 2019, 2(2), pp. 293–300, DOI:10.1049/iet-stg.2018.0092.
14. Meng Y. et al. Forced Oscillation Source Location Via Multivariate Time Series Classification. – IEEE/PES Transmission and Distribution Conference and Exposition (T&D), 2018, DOI:10.1109/TDC.2018.8440420.
15. Gupta A.K., Verma K., Niazi K.R. Power System Low Frequency Oscillations Monitoring and Generator Coherency Determination in Real Time. – IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 2018, pp. 752–757, DOI:10.1109/ISGT-Asia.2018.8467778.
16. Zong H. et al. Oscillation Propagation Analysis of Hybrid AC/DC Grids with High Penetration Renewables. – IEEE Transactions on Power Systems, 2022, 37(6), pp. 4761–4772, DOI:10.1109/TPWRS.2022.3150413.
17. Ma J. et al. Equipment-Level Locating of Low Frequency Oscillating Source in Power System with DFIG Integration Based on Dynamic Energy Flow. – IEEE Transactions on Power Systems, 2020, 35(5), pp. 3433–3447, DOI:10.1109/TPWRS.2020.2977356.
18. Feng S. et al. A Two-Level Forced Oscillations Source Location Method Based on Phasor and Energy Analysis. – IEEE Access, 2018, pp. 44318–44327, DOI:10.1109/ACCESS.2018.2864261.
19. Butin K., Popov A., Rodionov A. Investigation the Influence of the Parameters of the Computational Scheme on Detecting the Source of Low-Frequency Oscillations. – E3S Web of Conferences, 2023, vol. 384, DOI:10.1051/e3sconf/202338401019.
20. Антонов В.И. и др. Основы релейной защиты и автоматики интеллектуальной электрической сети. Вологда: Инфра-Инженерия, 2023, 324 с.
21. Мокеев А.В. Повышение надежности и эффективности работы энергосистем на основе технологии синхронизированных векторных измерений. – Электричество, 2018, № 3, с. 7–15.
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26. Программное обеспечение мониторинга синхронных качаний активной мощности [Электрон. ресурс]. URL: https://www.ap-soft.ru/mskam, свободный (дата обращения: 31.05.2024).
27. Biswas S. et al. Big Data Analysis of Synchrophasor Data: Outcomes of Research Activities Supported by DOE FOA 1861. Richland, WA: Pacific Northwest National Laboratory, 2022.
28. Попов А.И., Бутин К.П., Родионов А.В. Анализ низкочастотных колебаний и большие данные. – Методические вопросы исследования надежности больших систем энергетики, 2024.
29. ГОСТ Р 59364-2021. Единая энергетическая система и изолированно работающие энергосистемы. Релейная защита и автоматика. Система мониторинга переходных режимов. Устройства синхронизированных векторных измерений. Нормы и требования. М.: Стандартинформ, 2021, 46 с.
30. Климова Т.Г., Расщепляев А.И., Серов Д.М. Программно-аппаратный комплекс RTDS, методы построения схем и управления ими. М.: Изд-во МЭИ, 2017, 52 с.
31. Арцишевский Я.Л., Климова Т.Г. Векторные и гипервекторные измерения в электроэнергетике. М.: Энергопрогресс: Энергетик, 2021, 90 с.
32. Угрюмов И.А. Разработка программного обеспечения для просмотра и воспроизведения архивных данных системы мониторинга переходных режимов. – Энергия Арктики: сб. материалов Всероссийской научно-технической конференции, 2023, с. 69–73.
#
1. Phadke A.G., Thorp J.S. Synchronized Phasor Measurements and Their Applications. Springer, 2017, 218 p. DOI: 10.1007/978-0-387-76537-2_1.
2. Zhukov A.V. et al. Methods for Determination of Parameters Variation of the Electrical Mode of the Power System and Their Use for the Power System Control Objectives. – CIGRE Session, 2018, Paris.
3. ПК PhasorPoint [Electron. resource], URL: https://www.rtsoft.ru/catalog/programmnoe-obespechenie/prikladnoe-po-i-prilozheniya/phasor-point/ (Date of appeal 31.05.2024).
4. Senyuk М.D. et al. Elektrichestvo – in Russ. (Electricity), 2024, No. 8, pp. 4–14.
5. Wang B., Maslennikov S. IEEE-NASPI Oscillation Source Location Contest-Case Development and Results. – Tech. rep. National Renewable Energy Lab. (NREL), Golden, CO (United States), 2021.
6. Popov A.I. et al. Examples of Processing Low-Frequency Oscillations in Russia and Ways to Improve the Analysis. – 2022 International Conference on Smart Grid Synchronized Measurements and Analytics, 2022, DOI:10.1109/SGSMA51733.2022.9805996.
7. Wang B., Maslennikov S. Synchrophasor Data for Oscillation Source Location. – Synchrophasor Technology: Real-time Operation of Power Networks, 2023, 190(1), DOI:10.1049/PBPO190E_ch1.
8. Chen L., Min Y., Hu W. An Energy-Based Method for Location of Power System Oscillation Source. – IEEE Transactions on Power Systems, 2012, 28(2), pp. 828–836, DOI: 10.1109/TPWRS.2012.2211627.
9. Maslennikov S., Wang B., Litvinov E. Dissipating Energy Flow Method for Locating the Source of Sustained Oscillations. – International Journal of Electrical Power & Energy Systems, 2017, pp. 55–62, DOI:10.1016/j.ijepes.2016.12.010.
10. Haugdal H., Uhlen K. Mode Shape Estimation Using Complex Principal Component Analysis and K-Means Clustering. – International Conference on Smart Grid Synchronized Measurements and Analytics, 2019, DOI:10.1109/SGSMA.2019.8784556.
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2024-07-31
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