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

Protection and Control of Modern Power Systems

Original Research

Liyuan Liu¹  Yi Wang¹  Tao Wang² 

[1] School of Electrical Engineering and Electronic Information, Xihua University, 610039, Chengdu, China;School of Electrical Engineering and Electronic Information, Xihua University, 610039, Chengdu, China;Key Laboratory of Fluid and Power Machinery, Ministry of Education, Xihua University, 610039, Chengdu, China;

关键词: Distribution network;    Fault location;    Spiking neural P system;    Bayesian estimation;    Contradiction principle;   

DOI  :  10.1186/s41601-023-00321-x

 received in 2022-11-28, accepted in 2023-08-29,  发布年份 2023

来源: Springer

【 摘 要 】

With the increasing scale of distribution networks and the mass access of distributed generation, traditional centralized fault location methods can no longer meet the performance requirements of speed and high accuracy. Therefore, this paper proposes a fault segment location method based on spiking neural P systems and Bayesian estimation for distribution networks with distributed generation. First, 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 results. Finally, the Bayesian estimation and contradiction principle are applied to verify and correct the initial results to obtain the final location results. Simulation results based on the IEEE 33-node system validate the feasibility and effectiveness of the proposed method.

【 授权许可】

CC BY   
© Power System Protection and Control Press 2023

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