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

Yanmin Wu, Jiaqi Liu (), Lu Wang, Yanjun An and Xiaofeng Zhang
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Yanmin Wu: College of Electric Engineering, Naval University of Engineering, Wuhan 430033, 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

Energies, 2023, vol. 16, issue 20, 1-17

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.

Keywords: distribution network reconfiguration; chaos optimization; CPSCSFO algorithm; optimization algorithm; distributed generation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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