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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| Cites_doi | 10.1007/s00202-019-00755-3 10.1016/j.asoc.2019.105720 10.1007/s00521-013-1525-5 10.1016/j.asoc.2016.12.018 10.1007/s11047-009-9175-3 10.1007/s10092-018-0274-3 10.1049/iet-gtd.2017.0338 10.1109/61.25627 10.1016/j.epsr.2009.05.004 10.1109/TPWRD.2005.852335 10.1016/j.engappai.2010.02.005 10.1109/59.207317 10.1016/j.swevo.2012.09.002 10.1016/j.ijepes.2015.11.039 10.1016/j.epsr.2018.12.030 10.1016/j.epsr.2019.105943 10.1109/TPWRS.2011.2174258 10.1016/j.epsr.2016.09.017 10.5539/mas.v3n4p98 10.1109/61.58002 10.1007/s40095-014-0073-9 10.3233/FI-2019-1795 10.3233/FI-2019-1796 |
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| Keywords | Power loss Network reconfiguration Transfer function Enhanced binary cuckoo search Electric distribution network |
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| References | Abu Arqub (bib0023) 2019; 166 Karimianfard, Haghighat (bib0003) 2019; 176 Chiang, Jean-Jumeau (bib0026) 1990; 5 Souifi, Kahouli, Hadj Abdallah (bib0001) 2019 Kennedy, Eberhart (bib0021) 1997; 5 Ahmadi, Martí (bib0028) 2015; 1 Mohd Zin, Ferdavani, Khairuddin A, Naeini (bib0031) 2012; 27 Sedighizadeh, Dakhem, Sarvi, Kordkheili (bib0013) 2014; 5 Bottura, Bernardes, Oleskovicz, Asada (bib0009) 2017; 143 Nguyen, Nguyen, Truong, Nguyen, Phung (bib0004) 2017; 52 Jasthi, Das (bib0030) 2018; 12 Abdelaziz, Mohammed, Mekhamer, Badr (bib0002) 2009; 79 Vadivoo, Slochanal (bib0012) 2009; 3 Niknam, Azad Farsani (bib0006) 2010; 23 Haupt, Haupt (bib0017) 2004 Abu Arqub (bib0022) 2018; 55 Sambaiah, Jayabarathi (bib0005) 2019; 0 Abu Arqub (bib0008) 2019; 166 Nguyen, Nguyen, Duong, Doan (bib0010) 2019 Yang, Deb (bib0015) 2009 Mirjalili, Lewis (bib0020) 2013; 9 Das (bib0027) 2006; 21 Baran, Wu (bib0024) 1989; 4 Pierezan, Dos Santos Coelho (bib0016) 2018 Nguyen, Nguyen (bib0007) 2019; 84 Pegado, Ñaupari, Molina, Castillo (bib0014) 2019; 169 Rashedi, Nezamabadi-Pour, Saryazdi (bib0019) 2010; 9 Mirjalili, Mirjalili, Yang (bib0018) 2014; 25 Nara, Shiose, Kitagawa, Ishihara (bib0011) 1992; 7 Bayat, Bagheri, Noroozian (bib0025) 2016; 77 Mantovani, Casari, Romero (bib0029) 2000; 11 Haupt (10.1016/j.compeleceng.2020.106893_bib0017) 2004 Mohd Zin (10.1016/j.compeleceng.2020.106893_bib0031) 2012; 27 Rashedi (10.1016/j.compeleceng.2020.106893_bib0019) 2010; 9 Pierezan (10.1016/j.compeleceng.2020.106893_bib0016) 2018 Nguyen (10.1016/j.compeleceng.2020.106893_bib0004) 2017; 52 Karimianfard (10.1016/j.compeleceng.2020.106893_bib0003) 2019; 176 Nguyen (10.1016/j.compeleceng.2020.106893_bib0010) 2019 Pegado (10.1016/j.compeleceng.2020.106893_bib0014) 2019; 169 Abdelaziz (10.1016/j.compeleceng.2020.106893_bib0002) 2009; 79 Abu Arqub (10.1016/j.compeleceng.2020.106893_bib0008) 2019; 166 Bayat (10.1016/j.compeleceng.2020.106893_bib0025) 2016; 77 Abu Arqub (10.1016/j.compeleceng.2020.106893_bib0023) 2019; 166 Abu Arqub (10.1016/j.compeleceng.2020.106893_bib0022) 2018; 55 Mirjalili (10.1016/j.compeleceng.2020.106893_bib0020) 2013; 9 Chiang (10.1016/j.compeleceng.2020.106893_bib0026) 1990; 5 Mirjalili (10.1016/j.compeleceng.2020.106893_bib0018) 2014; 25 Nguyen (10.1016/j.compeleceng.2020.106893_bib0007) 2019; 84 Sedighizadeh (10.1016/j.compeleceng.2020.106893_bib0013) 2014; 5 Das (10.1016/j.compeleceng.2020.106893_bib0027) 2006; 21 Sambaiah (10.1016/j.compeleceng.2020.106893_bib0005) 2019; 0 Niknam (10.1016/j.compeleceng.2020.106893_bib0006) 2010; 23 Bottura (10.1016/j.compeleceng.2020.106893_bib0009) 2017; 143 Jasthi (10.1016/j.compeleceng.2020.106893_bib0030) 2018; 12 Ahmadi (10.1016/j.compeleceng.2020.106893_bib0028) 2015; 1 Kennedy (10.1016/j.compeleceng.2020.106893_bib0021) 1997; 5 Vadivoo (10.1016/j.compeleceng.2020.106893_bib0012) 2009; 3 Nara (10.1016/j.compeleceng.2020.106893_bib0011) 1992; 7 Souifi (10.1016/j.compeleceng.2020.106893_bib0001) 2019 Mantovani (10.1016/j.compeleceng.2020.106893_bib0029) 2000; 11 Baran (10.1016/j.compeleceng.2020.106893_bib0024) 1989; 4 Yang (10.1016/j.compeleceng.2020.106893_bib0015) 2009 |
| References_xml | – volume: 23 start-page: 1340 year: 2010 end-page: 1349 ident: bib0006 article-title: A hybrid self-adaptive particle swarm optimization and modified shuffled frog leaping algorithm for distribution feeder reconfiguration publication-title: Eng Appl Artif Intell – volume: 5 start-page: 4 year: 1997 end-page: 8 ident: bib0021 article-title: A discrete binary version of the particle swarm algorithm publication-title: IEEE international conference on systems, man, and cybernetics computational cybernetics and simulation – volume: 169 start-page: 206 year: 2019 end-page: 213 ident: bib0014 article-title: Radial distribution network reconfiguration for power losses reduction based on improved selective BPSO publication-title: Electric Power Syst Res – volume: 5 start-page: 1568 year: 1990 end-page: 1574 ident: bib0026 article-title: Optimal network reconfigurations in distribution systems: part 2: solution algorithms and numerical results publication-title: IEEE Trans Power Delivery – volume: 3 start-page: 98 year: 2009 end-page: 110 ident: bib0012 article-title: Distribution system restoration using genetic algorithm with distributed generation publication-title: Modern Appl Sci – volume: 79 start-page: 1521 year: 2009 end-page: 1530 ident: bib0002 article-title: Distribution systems reconfiguration using a modified particle swarm optimization algorithm publication-title: Electric Power Syst Res – volume: 0 start-page: 1 year: 2019 end-page: 29 ident: bib0005 article-title: Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems publication-title: Int J Ambient Energy – volume: 52 start-page: 93 year: 2017 end-page: 108 ident: bib0004 article-title: Multi-objective electric distribution network reconfiguration solution using runner-root algorithm publication-title: Appl Soft Comput – volume: 11 start-page: 150 year: 2000 end-page: 159 ident: bib0029 article-title: Reconfiguração de sistemas de distribuição radiais utilizando o critério de queda de tensão publication-title: Controle e Automação – year: 2019 ident: bib0001 article-title: Multi-objective distribution network reconfiguration optimization problem publication-title: Electr Eng – volume: 166 start-page: 111 year: 2019 end-page: 137 ident: bib0023 article-title: Numerical algorithm for the solutions of fractional order systems of dirichlet function types with comparative analysis publication-title: Fundam Inform – volume: 27 start-page: 968 year: 2012 end-page: 974 ident: bib0031 article-title: Reconfiguration of radial electrical distribution network through minimum-current circular-updating-mechanism method publication-title: IEEE Trans Power Syst – volume: 176 year: 2019 ident: bib0003 article-title: An initial-point strategy for optimizing distribution system reconfiguration publication-title: Electric Power Syst Res – year: 2004 ident: bib0017 article-title: Practical genetic algorithms – volume: 4 start-page: 1401 year: 1989 end-page: 1407 ident: bib0024 article-title: Network reconfiguration in distribution systems for loss reduction and load balancing publication-title: IEEE Trans Power Delivery – volume: 9 start-page: 1 year: 2013 end-page: 14 ident: bib0020 article-title: S-shaped versus V-shaped transfer functions for binary particle swarm optimization publication-title: Swarm Evol Comput – start-page: 210 year: 2009 end-page: 214 ident: bib0015 article-title: World congress on nature and biologically inspired computing publication-title: NABIC 2009 - proceedings – volume: 166 start-page: 87 year: 2019 end-page: 110 ident: bib0008 article-title: Application of residual power series method for the solution of time-fractional schrödinger equations in one-dimensional space publication-title: Fundam Inform – volume: 5 start-page: 73 year: 2014 ident: bib0013 article-title: Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization publication-title: Int J Energy Environ Eng – volume: 84 year: 2019 ident: bib0007 article-title: An improved cuckoo search algorithm for the problem of electric distribution network reconfiguration publication-title: Appl Soft Comput – volume: 21 start-page: 202 year: 2006 end-page: 209 ident: bib0027 article-title: A fuzzy multiobjective approach for network reconfiguration of distribution systems publication-title: IEEE Trans Power Delivery – start-page: 1 year: 2018 end-page: 8 ident: bib0016 article-title: Coyote optimization algorithm: a new metaheuristic for global optimization problems publication-title: IEEE congress on evolutionary computation (CEC) – volume: 77 start-page: 360 year: 2016 end-page: 371 ident: bib0025 article-title: Optimal siting and sizing of distributed generation accompanied by reconfiguration of distribution networks for maximum loss reduction by using a new UVDA-based heuristic method publication-title: Int J Electrical Power Energy Syst – volume: 1 start-page: 1 year: 2015 end-page: 9 ident: bib0028 article-title: Minimum-loss network reconfiguration: a minimum spanning tree problem. Sustainable Energy publication-title: Grids Networks – volume: 7 start-page: 1044 year: 1992 end-page: 1051 ident: bib0011 article-title: Implementation of genetic algorithm for distribution systems loss minimum re-configuration publication-title: IEEE Trans Power Syst – volume: 55 year: 2018 ident: bib0022 article-title: Numerical solutions of systems of first-order, two-point BVPs based on the reproducing kernel algorithm publication-title: Calcolo – volume: 12 start-page: 1303 year: 2018 end-page: 1313 ident: bib0030 article-title: Simultaneous distribution system reconfiguration and DG sizing algorithm without load flow solution. IET Generation publication-title: Trans Distribut – volume: 9 start-page: 727 year: 2010 end-page: 745 ident: bib0019 article-title: BGSA: binary gravitational search algorithm publication-title: Nat Comput – volume: 25 start-page: 663 year: 2014 end-page: 681 ident: bib0018 article-title: Binary bat algorithm publication-title: Neural Comput Appl – start-page: 0 year: 2019 ident: bib0010 article-title: Optimal operation of transmission power networks by using improved stochastic fractal search algorithm publication-title: Neural Comput Appl – volume: 143 start-page: 400 year: 2017 end-page: 408 ident: bib0009 article-title: Setting directional overcurrent protection parameters using hybrid GA optimizer publication-title: Electric Power Syst Res – year: 2019 ident: 10.1016/j.compeleceng.2020.106893_bib0001 article-title: Multi-objective distribution network reconfiguration optimization problem publication-title: Electr Eng doi: 10.1007/s00202-019-00755-3 – volume: 84 year: 2019 ident: 10.1016/j.compeleceng.2020.106893_bib0007 article-title: An improved cuckoo search algorithm for the problem of electric distribution network reconfiguration publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2019.105720 – volume: 25 start-page: 663 year: 2014 ident: 10.1016/j.compeleceng.2020.106893_bib0018 article-title: Binary bat algorithm publication-title: Neural Comput Appl doi: 10.1007/s00521-013-1525-5 – year: 2004 ident: 10.1016/j.compeleceng.2020.106893_bib0017 – start-page: 1 year: 2018 ident: 10.1016/j.compeleceng.2020.106893_bib0016 article-title: Coyote optimization algorithm: a new metaheuristic for global optimization problems – volume: 52 start-page: 93 year: 2017 ident: 10.1016/j.compeleceng.2020.106893_bib0004 article-title: Multi-objective electric distribution network reconfiguration solution using runner-root algorithm publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2016.12.018 – volume: 9 start-page: 727 year: 2010 ident: 10.1016/j.compeleceng.2020.106893_bib0019 article-title: BGSA: binary gravitational search algorithm publication-title: Nat Comput doi: 10.1007/s11047-009-9175-3 – volume: 55 year: 2018 ident: 10.1016/j.compeleceng.2020.106893_bib0022 article-title: Numerical solutions of systems of first-order, two-point BVPs based on the reproducing kernel algorithm publication-title: Calcolo doi: 10.1007/s10092-018-0274-3 – volume: 11 start-page: 150 year: 2000 ident: 10.1016/j.compeleceng.2020.106893_bib0029 article-title: Reconfiguração de sistemas de distribuição radiais utilizando o critério de queda de tensão publication-title: Controle e Automação – volume: 0 start-page: 1 year: 2019 ident: 10.1016/j.compeleceng.2020.106893_bib0005 article-title: Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems publication-title: Int J Ambient Energy – volume: 12 start-page: 1303 year: 2018 ident: 10.1016/j.compeleceng.2020.106893_bib0030 article-title: Simultaneous distribution system reconfiguration and DG sizing algorithm without load flow solution. IET Generation publication-title: Trans Distribut doi: 10.1049/iet-gtd.2017.0338 – volume: 1 start-page: 1 year: 2015 ident: 10.1016/j.compeleceng.2020.106893_bib0028 article-title: Minimum-loss network reconfiguration: a minimum spanning tree problem. Sustainable Energy publication-title: Grids Networks – volume: 4 start-page: 1401 year: 1989 ident: 10.1016/j.compeleceng.2020.106893_bib0024 article-title: Network reconfiguration in distribution systems for loss reduction and load balancing publication-title: IEEE Trans Power Delivery doi: 10.1109/61.25627 – start-page: 210 year: 2009 ident: 10.1016/j.compeleceng.2020.106893_bib0015 article-title: World congress on nature and biologically inspired computing – volume: 79 start-page: 1521 year: 2009 ident: 10.1016/j.compeleceng.2020.106893_bib0002 article-title: Distribution systems reconfiguration using a modified particle swarm optimization algorithm publication-title: Electric Power Syst Res doi: 10.1016/j.epsr.2009.05.004 – volume: 21 start-page: 202 year: 2006 ident: 10.1016/j.compeleceng.2020.106893_bib0027 article-title: A fuzzy multiobjective approach for network reconfiguration of distribution systems publication-title: IEEE Trans Power Delivery doi: 10.1109/TPWRD.2005.852335 – volume: 23 start-page: 1340 year: 2010 ident: 10.1016/j.compeleceng.2020.106893_bib0006 article-title: A hybrid self-adaptive particle swarm optimization and modified shuffled frog leaping algorithm for distribution feeder reconfiguration publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2010.02.005 – start-page: 0 year: 2019 ident: 10.1016/j.compeleceng.2020.106893_bib0010 article-title: Optimal operation of transmission power networks by using improved stochastic fractal search algorithm publication-title: Neural Comput Appl – volume: 7 start-page: 1044 year: 1992 ident: 10.1016/j.compeleceng.2020.106893_bib0011 article-title: Implementation of genetic algorithm for distribution systems loss minimum re-configuration publication-title: IEEE Trans Power Syst doi: 10.1109/59.207317 – volume: 9 start-page: 1 year: 2013 ident: 10.1016/j.compeleceng.2020.106893_bib0020 article-title: S-shaped versus V-shaped transfer functions for binary particle swarm optimization publication-title: Swarm Evol Comput doi: 10.1016/j.swevo.2012.09.002 – volume: 5 start-page: 4 year: 1997 ident: 10.1016/j.compeleceng.2020.106893_bib0021 article-title: A discrete binary version of the particle swarm algorithm – volume: 77 start-page: 360 year: 2016 ident: 10.1016/j.compeleceng.2020.106893_bib0025 article-title: Optimal siting and sizing of distributed generation accompanied by reconfiguration of distribution networks for maximum loss reduction by using a new UVDA-based heuristic method publication-title: Int J Electrical Power Energy Syst doi: 10.1016/j.ijepes.2015.11.039 – volume: 169 start-page: 206 year: 2019 ident: 10.1016/j.compeleceng.2020.106893_bib0014 article-title: Radial distribution network reconfiguration for power losses reduction based on improved selective BPSO publication-title: Electric Power Syst Res doi: 10.1016/j.epsr.2018.12.030 – volume: 176 year: 2019 ident: 10.1016/j.compeleceng.2020.106893_bib0003 article-title: An initial-point strategy for optimizing distribution system reconfiguration publication-title: Electric Power Syst Res doi: 10.1016/j.epsr.2019.105943 – volume: 27 start-page: 968 year: 2012 ident: 10.1016/j.compeleceng.2020.106893_bib0031 article-title: Reconfiguration of radial electrical distribution network through minimum-current circular-updating-mechanism method publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2011.2174258 – volume: 143 start-page: 400 year: 2017 ident: 10.1016/j.compeleceng.2020.106893_bib0009 article-title: Setting directional overcurrent protection parameters using hybrid GA optimizer publication-title: Electric Power Syst Res doi: 10.1016/j.epsr.2016.09.017 – volume: 3 start-page: 98 year: 2009 ident: 10.1016/j.compeleceng.2020.106893_bib0012 article-title: Distribution system restoration using genetic algorithm with distributed generation publication-title: Modern Appl Sci doi: 10.5539/mas.v3n4p98 – volume: 5 start-page: 1568 year: 1990 ident: 10.1016/j.compeleceng.2020.106893_bib0026 article-title: Optimal network reconfigurations in distribution systems: part 2: solution algorithms and numerical results publication-title: IEEE Trans Power Delivery doi: 10.1109/61.58002 – volume: 5 start-page: 73 year: 2014 ident: 10.1016/j.compeleceng.2020.106893_bib0013 article-title: Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization publication-title: Int J Energy Environ Eng doi: 10.1007/s40095-014-0073-9 – volume: 166 start-page: 87 year: 2019 ident: 10.1016/j.compeleceng.2020.106893_bib0008 article-title: Application of residual power series method for the solution of time-fractional schrödinger equations in one-dimensional space publication-title: Fundam Inform doi: 10.3233/FI-2019-1795 – volume: 166 start-page: 111 year: 2019 ident: 10.1016/j.compeleceng.2020.106893_bib0023 article-title: Numerical algorithm for the solutions of fractional order systems of dirichlet function types with comparative analysis publication-title: Fundam Inform doi: 10.3233/FI-2019-1796 |
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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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