Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources

作     者：Ye Guo Yifei Xu Hongbin Sun Boming Zhang 

作者机构：Tsinghua-Berkeley Shenzhen Institute(TBSI)Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Department of Electrical EngineeringState Key Laboratory of Power SystemsTsinghua UniversityBeijing100084China 

出 版 物：《CSEE Journal of Power and Energy Systems》 (中国电机工程学会电力与能源系统学报(英文))

年 卷 期：2025年第11卷第1期

页      面：115-123页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the National Natural Science Foundation of China(No.51977115) 

主　　题：Forecasting-aided state estimation phasor measurement renewable energy sources state estimation time interval 

摘      要：To achieve more precise monitoring of state fluctuations in the power network close to renewable energy sources, it is necessary to utilize phasor measurements and shorten the time interval between state estimations. For large-scale power systems, however, estimating all of their states with shorter time intervals means a drastic increase in computational burden. As a tradeoff between accuracy and computational efficiency, a multi-time interval forecasting-aided state estimation approach is proposed in this paper, where states with various degrees of fluctuations are estimated asynchronously with different time intervals. Based on the newest state estimate, forecasting-aided state estimators are employed to predict states at time moments prior to the next round of measurement update and state estimation. Extensive numerical tests have demonstrated the effectiveness of the proposed approach.