State prediction method of line relay protection device based on the Markov chain with dynamic optimization

被引：0
|
作者：
Li T. [1 ]
Liu Q. [1 ]
Ren J. [2 ]
Zeng S. [1 ]
Zhou D. [3 ]
Wang Z. [3 ]
机构：
[1] State Grid Hebei Electric Power Co., Ltd. Research Institute, Shijiazhuang
[2] State Grid Hebei Electric Power Co., Ltd., Shijiazhuang
[3] Wuhan Kemov Electric Co., Ltd, Wuhan
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2022年 / 50卷 / 13期
基金：
中国国家自然科学基金;
关键词：
line relay protection; Markov chain; state prediction; support vector machine; Weibull distribution;
D O I：
10.19783/j.cnki.pspc.210915
中图分类号：
学科分类号：
摘要：
At present, the relay protection states monitoring models use the static fault probability value to predict the equipment failure rate, which fails to consider the dynamic impact of equipment aging and maintenance, and the prediction results are unreliable. Therefore, a Markov chain state prediction method based on three parameters Weibull distribution dynamic optimization is proposed in this paper. First, the grey model-particle swarm support vector machine algorithm is used to calculate the more accurate failure rate function of relay protection equipment, and then it is used to dynamically modify the transition probability between each operation state in the Markov chain, and finally deduce the future operation state of the line protection. The simulation result shows that, the failure rate function solved in this paper has higher calculation accuracy than the function solved by the traditional method, and the dynamic optimization Markov chain model realizes the dynamic quantitative treatment of equipment aging and maintenance. The calculation results of states transition probabilities accord with the equipment operation conditions, and can effectively predict the operation state at any time within the specified operation life of the equipment. It has certain guiding significance for the optimization of protection maintenance strategy. © 2022 Power System Protection and Control Press. All rights reserved.
引用
收藏
页码：97 / 106
页数：9
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