An improved binary gaining-sharing knowledge-based algorithm for solving the analytic model of power grid fault diagnosis

被引:0
作者
Yuan Q. [1 ,2 ]
Zhou H. [1 ,2 ]
Huang J. [3 ]
Song F. [4 ]
机构
[1] School of Marine Engineering, Jimei University, Xiamen
[2] Fujian Province Key Laboratory of Naval Architecture and Marine Engineering, Xiamen
[3] Xiamen Anmaixin Automation Technology Co., Ltd., Xiamen
[4] Ganzhou Cyclewell Technology Co., Ltd., Ganzhou
来源
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2023年 / 51卷 / 24期
基金
中国国家自然科学基金;
关键词
adaptive crossover operator; binary; discrete working mechanism; evolutionary population dynamics; fault diagnosis; gaining-sharing knowledge-based algorithm;
D O I
10.19783/j.cnki.pspc.230761
中图分类号
学科分类号
摘要
There is a problem that existing intelligent optimization algorithms tend to fall into local optima and low population quality when solving power grid fault diagnosis analytical models. Thus an improved binary gain-sharing knowledge-based algorithm (IBGSK) is proposed. First, a complete analytical model considering complete fault information is constructed from the fault diagnosis rules. Second, a discrete working mechanism is integrated into the population replacement of the improved algorithm to avoid spatial disconnection. Then, combined with the idea of evolutionary population dynamics (EPD), an adaptive crossover operator is proposed to improve the population quality, thereby enhancing the global optimization ability of the improved algorithm. Finally, the performance of algorithms is evaluated by feature selection and fault diagnosis simulation experiments. The results show that the IBGSK algorithm has higher computational efficiency, stronger global optimization ability, and generalizability in feature selection problems than other optimization algorithms. It has better diagnostic reliability, timeliness, and convergence in solving the analytic model of power grid fault diagnosis. © 2023 Power System Protection and Control Press. All rights reserved.
引用
收藏
页码:175 / 187
页数:12
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