Optimization of electric distribution network configuration for power loss reduction based on enhanced binary cuckoo search algorithm. (March 2021)

• Record Type: Journal Article
• Authors: Nguyen, Thuan Thanh; Nguyen, Thang Trung; Le, Bac
• Is Part Of: Computers & electrical engineering. Volume 90(2021)
• Publication Date: 2021-03
• Subjects: Network reconfiguration -- Enhanced binary cuckoo search -- Electric distribution network -- Transfer function -- Power loss; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106893
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: An enhanced binary cuckoo search (EBCSA) is proposed for solving the NR problem. A local search mechanism is added EBCSA to exploit around the best so far solution. The EBCSA has better performance in comparison to BCSA, BCOA, BGA and BPSO. The effect of types of the transfer function to EBCSA's efficiency is evaluated. The effect of the control parameters of EBCSA to the NR problem is analyzed. Abstract: This paper presents a new network reconfiguration (NR) method using enhanced binary cuckoo search algorithm (EBCSA) to reduce power loss in the distribution system. Enhanced binary cuckoo search algorithm (EBCSA) is developed by transferring the continuous cuckoo search algorithm (CSA) to the binary domain and adding a new local search mechanism. Calculation results on different test systems demonstrate that EBCSA has capability for searching the optimal network configuration with greater success rate, better optimal solution quality and smaller number of average convergence iterations than those of binary CSA, binary coyote optimization algorithm, binary genetic algorithm and binary particle swarm optimization. Furthermore, the effect of the transfer function transferring from continuous domain to binary domain and the value of the parameters of EBCSA for the NR problem are also evaluated to choose the suitable values. The results show that EBCSA is a tool worth considering for the NR problem. Graphical abstract: Image, graphical abstract