An Improved Prony Prediction Compensation-Based Wide-Area Damping Control Approach for Power System Low-Frequency Oscillation Suppression

被引:1
|
作者
Chang, Shujun [1 ]
Peng, Chao [2 ,3 ]
Hu, Yuyang [2 ]
Mou, Yaxue [2 ]
机构
[1] Univ Elect Sci & Technol China, Zhongshan Inst Zhongshan, Zhongshan 528400, Guangdong, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 610054, Sichuan, Peoples R China
[3] Intelligent Terminal Key Lab Sichuan Prov, Yibin 644000, Sichuan, Peoples R China
关键词
FACTS DEVICES; UNIFIED MODEL; DESIGN;
D O I
10.1155/2021/5580847
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
Currently, wide-area damping control has been considered one of the most effective and promising methods to solve the problem of interval low-frequency oscillation in power systems. In order to reduce adverse affection caused by time delay in acquisition and transmission of wide-area signals, an improved Prony prediction compensation-based wide-area damping control approach for power system low-frequency oscillation suppression is proposed in this paper. Firstly, the influence of communication time delay on power system stability is analyzed by a small disturbance stability analysis method. An algorithm based on the improved Prony prediction algorithm is designed to predict the acquired signals with time delay. A second derivative-based order determination algorithm is used to obtain the best effective order of the prediction model, and the parameter prediction step size of the prediction model is determined by the actual situation of time delay change. Finally, design of a wide-area damping controller based on the improved Prony prediction compensation is presented in detail. The proposed control approach is conducted in a four-machine and two-zone power system, and the experiment results show that the proposed approach can effectively compensate for the signal under the conditions of fixed time delay and variable time delay and has better adaptability advantages than the traditional Prony prediction compensation method.
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收藏
页数:10
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