Particle Swarm Optimization Support Vector Machine-Based Grounding Fault Detection Method in Distribution Network
Year: 2025
Type: article
Abstract: With the present fault detection method for low-voltage distribution networks, it is difficult to detect single-phase grounding faults under complex working conditions. In this paper, a particle swarm optimization (PSO) support vector machine (SVM)-based grounding fault detection method is proposed for distribution networks. By improving the inertia weight value and introducing a flight-time factor, the PSO algorithm can be improved. The parameters C and g of the SVM can be optimized based on the improved PSO algorithm. Based on the PSO-SVM-based method, a grounding fault detection method can be established. By testing the proposed model in the simulation and experiment, its effectiveness and detection accuracy is validated.
Source: Algorithms
DOI: 10.3390/a18050259
Authors: Zhongqin Xiong, Shichang Huang, Shen Ren, Yutong Lin, Zewen Li, Dongyu Li, Fangming Deng
Institution: East China Jiaotong University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,930
Funder: China Southern Power Grid
Award: G3005999558
OpenAlex ID: W4409904357