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Research on Fault Location in Integrated Energy Systems Based on Improved Binary Particle Swarm Optimization Algorithm

Year: 2025

Type: article

Abstract: ObjectivesThe coverage of power systems continues to expand, and the structure of integrated energy systems is becoming increasingly complex. This trend leads to a significant decline in the accuracy of fault location in the distribution network that is a critical component of the energy system. To address this, a fault location method for distribution network based on an improved binary particle swarm optimization (BPSO) algorithm is proposed.MethodsDuring each iteration of the binary particles, an adaptive mutation operation is first performed on the position of the particle. Furthermore, an adaptive method is introduced into the setting of inertia weight, establishing a BPSO algorithm with dual adaptive characteristics.ResultsIn the standard radial distribution networks and those incorporating distributed generation, the improved BPSO algorithm can accurately pinpoint fault sections.ConclusionsCompared with the traditional BPSO algorithm and genetic algorithm, the improved algorithm demonstrates stronger robustness in convergence ability. It remains unaffected by differences in fault types and has greater reliability. Therefore, it is more suitable for fault location tasks in complex and dynamic distribution network environments.

Source: DOAJ (DOAJ: Directory of Open Access Journals)

DOI: 10.12096/j.2096-4528.pgt.24242

Authors: ZHAO Ruizhi, LIAN Xiaolin, YING Kaiwen, LIU Jie, LI Siyu, GAO Yang

Institutions: State Grid Shanghai Municipal Electric Power Company (China), Shanghai Jiao Tong University

Language: English

Topic: Power Systems Fault Detection

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7084135458

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