Active Distribution Network Fault Location Based on Petri Nets and Improved Particle Swarm Optimization Algorithm

Abstract To address issues such as inadequate fault tolerance, long computation time, and limited universality in fault location for active distribution networks, this paper proposes a fault location method that combines Petri nets with an improved particle swarm optimization (PSO) algorithm. This method enhances the efficiency of fault location in distribution networks with distributed power sources, demonstrating good applicability and convergence, especially in complex network scenarios. The results from two test functions and simulation analyses of two types of node distribution networks show that (1) in the single-point fault simulation, the improved algorithm successfully located the fault in the ninth iteration, outperforming the 14th iteration result of the standard PSO algorithm. (2) In networks with randomly interconnected distributed power sources, the algorithm accurately located both single and multiple faults. (3) Experimental verification further supports the simulation results, proving the effectiveness of this method in practical applications. Cite this article as: Y. Xia, J. Yang, J. Chen, Y. Lai and S. Ye, "Active distribution network fault location based on petri nets and improved particle swarm optimization algorithm," Electrica, 24(3), 789-798, 2024.

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Publication Details

Journal
Istanbul University - Journal of Electrical & Electronics Engineering
Published
2024-11-08
DOI
https://doi.org/10.5152/electrica.2024.24047
Citations
1
Primary Topic
Smart Grid and Power Systems
Type
article
Field-Weighted Citation Impact
0.21
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Active Distribution Network Fault Location Based on Petri Nets and Improved Particle Swarm Optimization Algorithm

Jie Yang, Yeming Lai, Yunfeng Xia, Sheng Ye et al.
1 citations
Istanbul University - Journal of Electrical & Electronics Engineering
Smart Grid and Power Systems
0.21
article

Active Distribution Network Fault Location Based on Petri Nets and Improved Particle Swarm Optimization Algorithm

Jie Yang, Yeming Lai, Yunfeng Xia, Sheng Ye, Junan Chen
article en
1 citations

Abstract

Abstract To address issues such as inadequate fault tolerance, long computation time, and limited universality in fault location for active distribution networks, this paper proposes a fault location method that combines Petri nets with an improved particle swarm optimization (PSO) algorithm. This method enhances the efficiency of fault location in distribution networks with distributed power sources, demonstrating good applicability and convergence, especially in complex network scenarios. The results from two test functions and simulation analyses of two types of node distribution networks show that (1) in the single-point fault simulation, the improved algorithm successfully located the fault in the ninth iteration, outperforming the 14th iteration result of the standard PSO algorithm. (2) In networks with randomly interconnected distributed power sources, the algorithm accurately located both single and multiple faults. (3) Experimental verification further supports the simulation results, proving the effectiveness of this method in practical applications. Cite this article as: Y. Xia, J. Yang, J. Chen, Y. Lai and S. Ye, "Active distribution network fault location based on petri nets and improved particle swarm optimization algorithm," Electrica, 24(3), 789-798, 2024.

Istanbul University - Journal of Electrical & Electronics EngineeringVol. 24(3)
Openalex Percentile: Top 46%
Smart Grid and Power Systems
0.21
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Active Distribution Network Fault Location Based on Petri Nets and Improved Particle Swarm Optimization Algorithm — Jie Yang, Yeming Lai, et al. · Istanbul University - Journal of Electrical & Electronics Engineering (2024) | TGRS Research Map | TGRS