1. Chaotic Particle Swarm Optimization Algorithm for Fault Location of Distribution Network with DG
- Author
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Governor David Kwabena Amesimenu, Hui-Qiong Deng, Kuo-Chi Chang, Rongsheng Zhang, Hsiao-Chuan Wang, and Fu-Hsiang Chang
- Subjects
Fitness function ,Computer science ,Algorithmic efficiency ,Genetic algorithm ,Convergence (routing) ,Chaotic ,Particle swarm optimization ,Function (mathematics) ,Fault (power engineering) ,Algorithm - Abstract
To achieve accurate and fast fault location in the distribution network, this paper introduces chaos theory into PSO (Particle Swarm Optimization). It proposes a fault location method for distribution networks with distributed generation based on CPSO (Chaotic Particle Swarm Optimization). The IEEE14-node distribution network model with multiple power sources is established. Then, the coding mode, switching function, and fitness function of distribution network fault information is constructed. Finally, the location results of single-point fault, multi-point fault, and information distortion are analyzed, respectively. The results show that the chaotic particle swarm algorithm proposed in this paper can achieve accurate location and outperform the traditional particle swarm algorithm, genetic algorithm, and the recently proposed manta ray foraging algorithm in convergence, accuracy, and algorithm efficiency.
- Published
- 2021
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