Optimization of electric distribution network configuration for power loss reduction based on enhanced binary cuckoo search algorithm

•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'...

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Vydáno v:Computers & electrical engineering Ročník 90; s. 106893
Hlavní autoři: Nguyen, Thuan Thanh, Nguyen, Thang Trung, Le, Bac
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier Ltd 01.03.2021
Elsevier BV
Témata:
Algorithms
Configurations
Continuity (mathematics)
Domains
Electric distribution network
Electric power distribution
Electric power loss
Enhanced binary cuckoo search
Genetic algorithms
Loss reduction
Network reconfiguration
Optimization
Particle swarm optimization
Power loss
Reconfiguration
Search algorithms
Transfer function
Transfer functions
Power loss
Network reconfiguration
Transfer function
Enhanced binary cuckoo search
Electric distribution network
ISSN:0045-7906, 1879-0755
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Shrnutí:•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. 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. [Display omitted]
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ISSN:0045-7906
1879-0755
DOI:10.1016/j.compeleceng.2020.106893