A fault segment location method for distribution networks based on spiking neural P systems and Bayesian estimation

作     者：Yi Wang Tao Wang Liyuan Liu 

作者机构：School of Electrical Engineering and Electronic InformationXihua UniversityChengdu 610039China Key Laboratory of Fluid and Power MachineryMinistry of EducationXihua UniversityChengdu 610039China 

出 版 物：《Protection and Control of Modern Power Systems》 (现代电力系统保护与控制（英文）)

年 卷 期：2023年第8卷第3期

页      面：184-195页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0701[理学-数学] 

基　　金：funded by grants from the National Natural Science Foundation of China(61703345) the Chunhui Project Foundation of the Education Department of China(Z201980) the Open Research Subject of Key Laboratory of Fluid and Power Machinery(Xihua University),Ministry of Education(szjj2019-27) 

主　　题：Distribution network Fault location Spiking neural P system Bayesian estimation Contradiction principle 

摘      要：With the increasing scale of distribution networks and the mass access of distributed generation,traditional central-ized fault location methods can no longer meet the performance requirements of speed and high ***-fore,this paper proposes a fault segment location method based on spiking neural P systems and Bayesian estimation for distribution networks with distributed ***,the distribution network system topology is decoupled into single-branch networks.A spiking neural P system with excitatory and inhibitory synapses is then proposed to model the suspected faulty segment,and its matrix reasoning algorithm is executed to obtain a preliminary set of location ***,the Bayesian estimation and contradiction principle are applied to verify and correct the ini-tial results to obtain the final location *** results based on the IEEE 33-node system validate the feasi-bility and effectiveness of the proposed method.