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 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.03.2021
Elsevier BV |
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| ISSN: | 0045-7906, 1879-0755 |
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| Abstract | •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.
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| AbstractList | •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] 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. |
| ArticleNumber | 106893 |
| Author | Nguyen, Thang Trung Le, Bac Nguyen, Thuan Thanh |
| Author_xml | – sequence: 1 givenname: Thuan Thanh surname: Nguyen fullname: Nguyen, Thuan Thanh email: nguyenthanhthuan@iuh.edu.vn organization: Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam – sequence: 2 givenname: Thang Trung surname: Nguyen fullname: Nguyen, Thang Trung email: nguyentrungthang@tdtu.edu.vn organization: Power System Optimization Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam – sequence: 3 givenname: Bac surname: Le fullname: Le, Bac email: lhbac@fit.hcmus.edu.vn organization: Faculty of Information Technology, University of Science, Ho Chi Minh City, Vietnam |
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| Keywords | Power loss Network reconfiguration Transfer function Enhanced binary cuckoo search Electric distribution network |
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| Snippet | •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... This paper presents a new network reconfiguration (NR) method using enhanced binary cuckoo search algorithm (EBCSA) to reduce power loss in the distribution... |
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| SubjectTerms | 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 |
| Title | Optimization of electric distribution network configuration for power loss reduction based on enhanced binary cuckoo search algorithm |
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