Multi-Stage Voltage Sag State Estimation Using Event-Deduction Model Corresponding to EF, EG, and EP

被引:26
作者
Wang, Ying [1 ]
He, Hai-Shan [1 ]
Xiao, Xian-Yong [1 ]
Li, Shun-Yi [1 ]
Chen, Yun-Zhu [1 ]
Ma, Hai-Xing [1 ]
机构
[1] Sichuan Univ, Coll Elect Engn, Chengdu 610065, Peoples R China
基金
中国国家自然科学基金;
关键词
Power quality; Circuit faults; Monitoring; Impedance; State estimation; Protective relaying; Power grids; Causes identification; event deduction; multi-stage voltage sag; state estimation; voltage sag; PROTECTION; SYSTEM;
D O I
10.1109/TPWRD.2022.3198854
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Knowledge of the disturbance of the concerned bus is essential to make decisions to mitigate voltage sags. The most commonly used method is to estimate the state of voltage sag in the absence of a monitor. However, the traditional state estimation method, which is designed for rectangular voltage sags, is difficult to apply to multi-stage voltage sags (MSVSs). This study proposes an MSVS state-estimation method based on event-deduction models. First, we propose a method to identify the causes of MSVSs. Second, we present a method to calculate the matrix of relay protection trips (MRPT), which corresponds to the fault clearing time of the relay protection and a method to calculate the fault power line set to reduce the computing workload of the MRPT-based estimation method. Third, we propose a method to calculate the impedance matrix of a power system under different disturbance events, resulting in different stages of the MSVS and an event-deduction model based on this impedance matrix to deduce these events. Furthermore, we present a model to estimate the state of voltage sag for MSVS based on the event deduction result. Finally, we use the IEEE-118 system to validate the proposed method.
引用
收藏
页码:797 / 811
页数:15
相关论文
共 24 条
[1]  
[Anonymous], 2022, INT J ELECT POWER, V134
[2]  
Blanza JF, 2019, 2019 INTERNATIONAL SYMPOSIUM ON MULTIMEDIA AND COMMUNICATION TECHNOLOGY (ISMAC), DOI [10.1109/ismac.2019.8836143, 10.1109/ptc.2019.8810771]
[3]  
Chao Zhang, 2021, 2021 6th Asia Conference on Power and Electrical Engineering (ACPEE), P1572, DOI 10.1109/ACPEE51499.2021.9436825
[4]   An Approach Based on Analytical Expressions for Optimal Location of Voltage Sags Monitors [J].
Espinosa-Juarez, Elisa ;
Hernandez, Araceli ;
Olguin, Gabriel .
IEEE TRANSACTIONS ON POWER DELIVERY, 2009, 24 (04) :2034-2042
[5]   Power Quality State Estimator for Smart Distribution Grids [J].
Farzanehrafat, A. ;
Watson, Neville R. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2013, 28 (03) :2183-2191
[6]   Voltage sag source location estimation based on optimized configuration of monitoring points [J].
Lv G. ;
Chu C. ;
Zang Y. ;
Chen G. .
CPSS Transactions on Power Electronics and Applications, 2021, 6 (03) :242-250
[7]   SVD Applied to Voltage Sag State Estimation [J].
Hernandez, Araceli ;
Espinosa-Juarez, Elisa ;
Maria de Castro, Rosa ;
Izzeddine, Mohamed .
IEEE TRANSACTIONS ON POWER DELIVERY, 2013, 28 (02) :866-874
[8]   Voltage sag/swell waveform analysis method based on multi-dimension characterisation [J].
Hu, Wen-Xi ;
Xiao, Xian-Yong ;
Zheng, Zi-Xuan .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2020, 14 (03) :486-493
[9]   Voltage Sag Estimation in Sparsely Monitored Power Systems Based on Deep Learning and System Area Mapping [J].
Liao, Huilian ;
Milanovic, Jovica V. ;
Rodrigues, Marcos ;
Shenfield, Alex .
IEEE TRANSACTIONS ON POWER DELIVERY, 2018, 33 (06) :3162-3172
[10]   A Sparse-Data-Driven Approach for Fault Location in Transmission Networks [J].
Majidi, Mehrdad ;
Etezadi-Amoli, Mehdi ;
Fadali, Mohammed Sami .
IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (02) :548-556