Dynamic Harmonic State Estimation of Power System Based on Sage-Husa Square-Root Unscented Kalman Filter

被引：2
|
作者：
Li, Yunshuo [1 ]
Liu, Jun [1 ]
Yang, Ting [2 ]
机构：
[1] China Elect Power Res Inst Co Ltd, Distribut Res Inst, Beijing, Peoples R China
[2] Nanjing Inst Technol, Coll Power Elect Engn, Nanjing, Peoples R China
来源：
PROCEEDINGS OF 2019 IEEE 3RD INTERNATIONAL ELECTRICAL AND ENERGY CONFERENCE (CIEEC) | 2019年
关键词：
dynamic HSE; Sage-Husa filter; SRUKF; IEEE14 test system;
D O I：
10.1109/CIEEC47146.2019.CIEEC-2019206
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
The limitations and shortcomings of traditional Kalman filter (KF) and its derivative algorithms with the application of harmonic state estimation (HSE) are analyzed. With the consideration that the power system is nonlinear and the measurement noise is an unknown random noise which is difficult to estimate by experience or hypothesis, an improved Sage-Husa square-root unscented KF (SH-SRUKF) algorithm based on SRUKF is introduced and derived, the method and flowchart for dynamic HSE under SH-SRUKF algorithm is proposed in this paper. Taking an IEEE14 test system as an example, the results of dynamic HSE in three scenarios are discussed, including the measurement noise is uncertain random noise, it might contain bad data and feasible fluctuations in load power. The simulation results indicate that SH-SRUKF performs better than SRUKF in the robustness and accuracy for dynamic HSE.
引用
收藏
页码：478 / 483
页数：6
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