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Distribution Network Reconfiguration Using Chaotic Particle Swarm Chicken Swarm Fusion Optimization Algorithm

Author

Listed:
  • Yanmin Wu

    (College of Electric Engineering, Naval University of Engineering, Wuhan 430033, China
    College of Building Environment Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Jiaqi Liu

    (College of Building Environment Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Lu Wang

    (College of Building Environment Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Yanjun An

    (College of Building Environment Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Xiaofeng Zhang

    (College of Electric Engineering, Naval University of Engineering, Wuhan 430033, China)

Abstract

Aiming at the problems of traditional optimization algorithms for reconfiguring distribution networks, which easily fall into a local optimum, have difficulty finding a global optimum, and suffer from low computational efficiency, the proposed algorithm named Chaotic Particle Swarm Chicken Swarm Fusion Optimization (CPSCSFO) is used to optimize the reconfiguration of the distribution network with distributed generation (DG). This article works to solve the problems mentioned above from the following three aspects: Firstly, chaotic formula is used to improve the initialization of the particles and optimize the optimal position. This increases individual randomness while avoiding local optimality for inert particles. Secondly, chicken swarm optimization (CSO) and particle swarm optimization (PSO) are combined. The multi-population nature of the CSO algorithm is used to increase the global search capability, and, at the same time, the information exchange between groups is completed to extend the particle search range, which ensures the independence and excellence of each particle group. Thirdly, the node hierarchy method is introduced to calculate the power flow. The branching loop matrix and the node hierarchy strategy are used to detect the network topology. In this way, improper solutions can be reduced, and the efficiency of the algorithm can be improved. This paper has demonstrated better performance by CPSCSFO based on simulation results. The network loss has been reduced and the voltage level of each node in the optimal reconfiguration with distributed power supply has been improved; the network loss in the optimal reconfiguration with DG is 69.59% lower than that reconfiguration before. The voltage level of each node is increased, the minimum node voltage is increased by 3.44% and a better convergence speed is presented. As a result, the quality of network operation and the distribution network is greatly improved and provides guidance for building a safer, more economical and reliable distribution network.

Suggested Citation

  • Yanmin Wu & Jiaqi Liu & Lu Wang & Yanjun An & Xiaofeng Zhang, 2023. "Distribution Network Reconfiguration Using Chaotic Particle Swarm Chicken Swarm Fusion Optimization Algorithm," Energies, MDPI, vol. 16(20), pages 1-17, October.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7185-:d:1264498
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    Citations

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    Cited by:

    1. David W. Puma & Y. P. Molina & Brayan A. Atoccsa & J. E. Luyo & Zocimo Ñaupari, 2024. "Distribution Network Reconfiguration Optimization Using a New Algorithm Hyperbolic Tangent Particle Swarm Optimization (HT-PSO)," Energies, MDPI, vol. 17(15), pages 1-13, August.
    2. Wei-Chen Lin & Chao-Hsien Hsiao & Wei-Tzer Huang & Kai-Chao Yao & Yih-Der Lee & Jheng-Lun Jian & Yuan Hsieh, 2024. "Network Reconfiguration Framework for CO 2 Emission Reduction and Line Loss Minimization in Distribution Networks Using Swarm Optimization Algorithms," Sustainability, MDPI, vol. 16(4), pages 1-19, February.
    3. Hui Jia & Xueling Zhu & Wensi Cao, 2024. "Distribution Network Reconfiguration Based on an Improved Arithmetic Optimization Algorithm," Energies, MDPI, vol. 17(8), pages 1-15, April.

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