Optimal distributed generation location and size using a modified teaching–learning based optimization algorithm
► A discrete teaching–learning-based optimization method is employed. ► Optimal sizes and locations to connect DG systems are determined. ► Effectiveness of the algorithm has been tested on two sample networks. ► We prove this approach is highly suitable in DG placement. In this paper, a method whic...
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| Vydané v: | International journal of electrical power & energy systems Ročník 50; s. 65 - 75 |
|---|---|
| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Oxford
Elsevier Ltd
01.09.2013
Elsevier |
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| ISSN: | 0142-0615, 1879-3517 |
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| Abstract | ► A discrete teaching–learning-based optimization method is employed. ► Optimal sizes and locations to connect DG systems are determined. ► Effectiveness of the algorithm has been tested on two sample networks. ► We prove this approach is highly suitable in DG placement.
In this paper, a method which employs a Modified Teaching–Learning Based Optimization (MTLBO) algorithm is proposed to determine the optimal placement and size of Distributed Generation (DG) units in distribution systems. For the sake of clarity, and without loss of generality, the objective function considered is to minimize total electrical power losses, although the problem can be easily configured as multi-objective (other objective functions can be considered at the same time), where the optimal location of DG systems, along with their sizes, are simultaneously obtained. The optimal DG site and size problem is modeled as a mixed integer nonlinear programming problem. Evolutionary methods are used by researchers to solve this problem because of their independence from type of the objective function and constraints. Recently, a new evolutionary method called Teaching–Learning Based Optimization (TLBO) algorithm has been presented, which is modified and used in this paper to find the best sites to connect DG systems in a distribution network, choosing among a large number of potential combinations. A comparison between the proposed algorithm and a brute force method is performed. Besides this, it has also been carried out a comparison using several results available in other articles published by others authors. Numerical results for two test distribution systems have been presented in order to show the effectiveness of the proposed approach. |
|---|---|
| AbstractList | ► A discrete teaching–learning-based optimization method is employed. ► Optimal sizes and locations to connect DG systems are determined. ► Effectiveness of the algorithm has been tested on two sample networks. ► We prove this approach is highly suitable in DG placement.
In this paper, a method which employs a Modified Teaching–Learning Based Optimization (MTLBO) algorithm is proposed to determine the optimal placement and size of Distributed Generation (DG) units in distribution systems. For the sake of clarity, and without loss of generality, the objective function considered is to minimize total electrical power losses, although the problem can be easily configured as multi-objective (other objective functions can be considered at the same time), where the optimal location of DG systems, along with their sizes, are simultaneously obtained. The optimal DG site and size problem is modeled as a mixed integer nonlinear programming problem. Evolutionary methods are used by researchers to solve this problem because of their independence from type of the objective function and constraints. Recently, a new evolutionary method called Teaching–Learning Based Optimization (TLBO) algorithm has been presented, which is modified and used in this paper to find the best sites to connect DG systems in a distribution network, choosing among a large number of potential combinations. A comparison between the proposed algorithm and a brute force method is performed. Besides this, it has also been carried out a comparison using several results available in other articles published by others authors. Numerical results for two test distribution systems have been presented in order to show the effectiveness of the proposed approach. |
| Author | Martín García, Juan Andrés Gil Mena, Antonio José |
| Author_xml | – sequence: 1 givenname: Juan Andrés surname: Martín García fullname: Martín García, Juan Andrés email: juanandres.martin@uca.es – sequence: 2 givenname: Antonio José surname: Gil Mena fullname: Gil Mena, Antonio José email: antonio.gil@uca.es |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27205091$$DView record in Pascal Francis |
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| Cites_doi | 10.1016/j.ins.2011.08.006 10.1109/TEC.2010.2044414 10.1109/TPWRS.2005.846219 10.1016/j.epsr.2006.06.005 10.1016/j.ijepes.2010.01.029 10.1109/TPWRS.2004.836189 10.1016/j.ijepes.2012.08.043 10.1016/j.ijepes.2011.08.023 10.1080/15325000590964254 10.1016/j.ijepes.2009.11.021 10.1109/PESW.2001.916995 10.1016/j.epsr.2011.11.016 10.1016/j.energy.2011.11.023 10.1109/TPWRS.2005.852115 10.1016/j.epsr.2006.11.014 10.1016/j.ijepes.2011.10.032 10.1016/j.ijepes.2006.02.013 10.1016/j.engappai.2012.07.004 10.1016/j.protcy.2012.10.031 10.1016/j.ijepes.2012.10.004 10.1016/j.ijepes.2006.02.003 10.1016/j.energy.2012.02.023 10.1016/j.ijepes.2012.09.010 10.3923/rjasci.2010.137.145 10.1016/j.cad.2010.12.015 10.1016/j.epsr.2008.12.007 10.1049/ip-gtd:20041193 10.1016/j.enconman.2011.06.001 10.1016/j.ijepes.2011.06.023 |
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| Keywords | Distribution systems Modified Teaching–Learning-Based Optimization (MTLBO) Power loss reduction Optimal placement Distributed Generation (DG) Performance evaluation Positioning Modified Teaching-Learning-Based Optimization method Multiobjective programming Distributed power generation Optimization Optimal design Learning Facility location Power losses Learning algorithm Distribution network Mixed integer programming Nonlinear problems Optimization (MTLBO) Electrical network Numerical simulation Objective function Electric power production Effectiveness factor Comparative study |
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| References | Gandomkar, Vakilian, Ehsan (b0065) 2005; 33 Rao, Patel (b0165) 2013; 4 Moradi, Abedini (b0095) 2012; 34 Keane, O’Malley (b0015) 2005; 20 de Souza, Fernandes, Aoki, Sans, Oening, Marcilio (b0120) 2013; 46 Ghosh, Ghoshal, Ghosh Sa (b0070) 2010; 32 Zhang, Fu, Zhang (b0175) 2007; 77 López-Lezama, Contreras, Padilha-Feltri (b0105) 2012; 36 Rao, Savsani, Vakharia (b0155) 2012; 183 Hosseinpour H, Niknam T, Taheri SI. A Modified TLBO algorithm for placement of AVRs considering DGs. In: 26th Int Power Syst Conf; 2011, p. 1–8. Raoofat (b0100) 2011; 33 Niknam, Azizipanah-Abarghooee, Narimani (b0145) 2012; 25 Gautam, Mithulananthan (b0020) 2007; 77 Falaghi, Haghifam (b0055) 2007 Singh, Goswami (b0080) 2010; 32 Acharya, Mahat, Mithulananthan (b0030) 2006; 28 Borges, Falcao (b0045) 2006; 28 Nara K, Hayashi Y, Ikeda K, Ashizawa T. Application of Tabu Search to optimal placement of distributed generators. In: Proc IEEE power engineering society winter meeting, vol. 2; 2001, p. 918–23. Nayak, Nayak, Rout (b0150) 2012; 6 Injeti, Kumar (b0110) 2013; 45 Niknam, Fard, Baziar (b0140) 2012; 42 Akorede, Hizam, Aris, Ab Kadir (b0005) 2010; 5 Ziari, Ledwich, Ghosh (b0115) 2013; 46 Gozel, Hocaoglu (b0035) 2009; 79 Rao, Savsani, Vakharia (b0125) 2011; 43 Hung, Mithulananthan, Bansal (b0075) 2010; 25 Alrashidi, AlHajri (b0085) 2011; 52 Azizipanah-Abarghooee, Niknam, Roosta, Malekpour, Zare (b0135) 2012; 37 Celli, Ghiani, Mocci, Pilo (b0060) 2005; 20 Baran, Wu (b0170) 1989; 4 Gómez-González, López, Jurado (b0090) 2012; 84 Harrison GP, Wallace AR. Optimal power flow evaluation of distribution network capacity for the connection of distributed generation. In: Proc IEE generation transmission, distribution, vol. 152; 2005, p. 115–22. Wang, Nehrir (b0025) 2004; 19 Rao, Patel (b0160) 2012; 3 Ardakani, Kavyani, Pourmousavi, Hosseinian, Abedi (b0050) 2007 Acharya (10.1016/j.ijepes.2013.02.023_b0030) 2006; 28 Azizipanah-Abarghooee (10.1016/j.ijepes.2013.02.023_b0135) 2012; 37 Falaghi (10.1016/j.ijepes.2013.02.023_b0055) 2007 Ghosh (10.1016/j.ijepes.2013.02.023_b0070) 2010; 32 Ardakani (10.1016/j.ijepes.2013.02.023_b0050) 2007 Nayak (10.1016/j.ijepes.2013.02.023_b0150) 2012; 6 López-Lezama (10.1016/j.ijepes.2013.02.023_b0105) 2012; 36 Alrashidi (10.1016/j.ijepes.2013.02.023_b0085) 2011; 52 Baran (10.1016/j.ijepes.2013.02.023_b0170) 1989; 4 Keane (10.1016/j.ijepes.2013.02.023_b0015) 2005; 20 de Souza (10.1016/j.ijepes.2013.02.023_b0120) 2013; 46 Injeti (10.1016/j.ijepes.2013.02.023_b0110) 2013; 45 Niknam (10.1016/j.ijepes.2013.02.023_b0140) 2012; 42 Hung (10.1016/j.ijepes.2013.02.023_b0075) 2010; 25 Gómez-González (10.1016/j.ijepes.2013.02.023_b0090) 2012; 84 Singh (10.1016/j.ijepes.2013.02.023_b0080) 2010; 32 Niknam (10.1016/j.ijepes.2013.02.023_b0145) 2012; 25 Raoofat (10.1016/j.ijepes.2013.02.023_b0100) 2011; 33 Moradi (10.1016/j.ijepes.2013.02.023_b0095) 2012; 34 Rao (10.1016/j.ijepes.2013.02.023_b0165) 2013; 4 Zhang (10.1016/j.ijepes.2013.02.023_b0175) 2007; 77 10.1016/j.ijepes.2013.02.023_b0040 Celli (10.1016/j.ijepes.2013.02.023_b0060) 2005; 20 Gandomkar (10.1016/j.ijepes.2013.02.023_b0065) 2005; 33 Borges (10.1016/j.ijepes.2013.02.023_b0045) 2006; 28 Rao (10.1016/j.ijepes.2013.02.023_b0160) 2012; 3 Rao (10.1016/j.ijepes.2013.02.023_b0125) 2011; 43 Ziari (10.1016/j.ijepes.2013.02.023_b0115) 2013; 46 Akorede (10.1016/j.ijepes.2013.02.023_b0005) 2010; 5 10.1016/j.ijepes.2013.02.023_b0010 10.1016/j.ijepes.2013.02.023_b0130 Wang (10.1016/j.ijepes.2013.02.023_b0025) 2004; 19 Rao (10.1016/j.ijepes.2013.02.023_b0155) 2012; 183 Gautam (10.1016/j.ijepes.2013.02.023_b0020) 2007; 77 Gozel (10.1016/j.ijepes.2013.02.023_b0035) 2009; 79 |
| References_xml | – reference: Nara K, Hayashi Y, Ikeda K, Ashizawa T. Application of Tabu Search to optimal placement of distributed generators. In: Proc IEEE power engineering society winter meeting, vol. 2; 2001, p. 918–23. – volume: 84 start-page: 174 year: 2012 end-page: 180 ident: b0090 article-title: Optimization of distributed generation systems using a new discrete PSO and OPF publication-title: Electr Power Syst Res – volume: 3 start-page: 535 year: 2012 end-page: 560 ident: b0160 article-title: An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems publication-title: Int J Ind Eng Comput – volume: 19 start-page: 2068 year: 2004 end-page: 2076 ident: b0025 article-title: Analytical approaches for optimal placement of distributed generation sources in power systems publication-title: IEEE Trans Power Syst – volume: 46 start-page: 145 year: 2013 end-page: 152 ident: b0120 article-title: Sensitivity analysis to connect distributed generation publication-title: Int J Electr Power Energy Syst – volume: 32 start-page: 637 year: 2010 end-page: 644 ident: b0080 article-title: Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction and voltage improvement including voltage rise issue publication-title: Int J Electr Power Energy Syst – volume: 79 start-page: 912 year: 2009 end-page: 918 ident: b0035 article-title: An analytical method for the sizing and siting of distributed generators in radial systems publication-title: Electr Power Syst Res – year: 2007 ident: b0050 article-title: Siting and sizing of distributed generation for loss reduction – volume: 77 start-page: 685 year: 2007 end-page: 694 ident: b0175 article-title: An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems publication-title: Electr Power Syst Res – volume: 5 start-page: 137 year: 2010 end-page: 145 ident: b0005 article-title: A review of strategies for optimal placement of distributed generation in power distribution systems publication-title: Res J Appl Sci – volume: 45 start-page: 142 year: 2013 end-page: 151 ident: b0110 article-title: A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems publication-title: Int J Electr Power Energy Syst – volume: 37 start-page: 322 year: 2012 end-page: 335 ident: b0135 article-title: Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method publication-title: Energy – reference: Harrison GP, Wallace AR. Optimal power flow evaluation of distribution network capacity for the connection of distributed generation. In: Proc IEE generation transmission, distribution, vol. 152; 2005, p. 115–22. – volume: 32 start-page: 849 year: 2010 end-page: 856 ident: b0070 article-title: Optimal sizing and placement of distributed generation in a network system publication-title: Int J Electr Power Energy Syst – reference: Hosseinpour H, Niknam T, Taheri SI. A Modified TLBO algorithm for placement of AVRs considering DGs. In: 26th Int Power Syst Conf; 2011, p. 1–8. – volume: 4 start-page: 29 year: 2013 end-page: 50 ident: b0165 article-title: Comparative performance of an elitist teaching-learning-based optimization algorithm for solving unconstrained optimization problems publication-title: Int J Ind Eng Comput – volume: 25 start-page: 1577 year: 2012 end-page: 1588 ident: b0145 article-title: A new multi objective optimization approach based on TLBO for location of automatic voltage regulators in distribution systems publication-title: Eng Appl Artif Intell – year: 2007 ident: b0055 article-title: ACO based algorithm for distributed generation sources allocation and sizing in distribution systems – volume: 33 start-page: 1429 year: 2011 end-page: 1436 ident: b0100 article-title: Simultaneous allocation of DGs and remote controllable switches in distribution networks considering multilevel load model publication-title: Int J Electr Power Energy Syst – volume: 6 start-page: 255 year: 2012 end-page: 264 ident: b0150 article-title: Application of multi-objective teaching learning based optimization algorithm to optimal power flow problem publication-title: Proc Technol – volume: 33 start-page: 1351 year: 2005 end-page: 1362 ident: b0065 article-title: A genetic-based tabu search algorithms for optimal DG allocation in distribution networks publication-title: Electr Power Compon Syst – volume: 34 start-page: 66 year: 2012 end-page: 74 ident: b0095 article-title: A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems publication-title: Int J Electr Power Energy Syst – volume: 20 start-page: 1640 year: 2005 end-page: 1646 ident: b0015 article-title: Optimal allocation of embedded generation on distribution networks publication-title: IEEE Trans Power Syst – volume: 25 start-page: 814 year: 2010 end-page: 820 ident: b0075 article-title: Analytical expressions for DG allocation in primary distribution networks publication-title: IEEE Trans Energy Convers – volume: 36 start-page: 117 year: 2012 end-page: 126 ident: b0105 article-title: Location and contract pricing of distributed generation using a genetic algorithm publication-title: Int J Electr Power Energy Syst – volume: 183 start-page: 1 year: 2012 end-page: 15 ident: b0155 article-title: Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems publication-title: Inform Sci – volume: 28 start-page: 669 year: 2006 end-page: 678 ident: b0030 article-title: An analytical approach for DG allocation in primary distribution network publication-title: Int J Electr Power Energy Syst – volume: 4 start-page: 735 year: 1989 end-page: 743 ident: b0170 article-title: Optimum sizing of capacitor placed on radial distribution systems publication-title: IEEE Trans PWRD – volume: 42 start-page: 563 year: 2012 end-page: 573 ident: b0140 article-title: Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants publication-title: Energy – volume: 77 start-page: 1627 year: 2007 end-page: 1636 ident: b0020 article-title: Optimal DG placement in deregulated electricity market publication-title: Electr Power Syst Res – volume: 52 start-page: 3301 year: 2011 end-page: 3308 ident: b0085 article-title: Optimal planning of multiple distributed generation sources in distribution networks: a new approach publication-title: Energy Convers Manage – volume: 20 start-page: 750 year: 2005 end-page: 757 ident: b0060 article-title: A multiobjective evolutionary algorithm for the sizing and sitting of distributed generation publication-title: IEEE Trans Power Syst – volume: 28 start-page: 413 year: 2006 end-page: 420 ident: b0045 article-title: Optimal distributed generation allocation for reliability, losses and voltage improvement publication-title: Int J Electr Power Energy Syst – volume: 46 start-page: 250 year: 2013 end-page: 257 ident: b0115 article-title: A new technique for optimal allocation and sizing of capacitors and setting of LTC publication-title: Int J Electr Power Energy Syst – volume: 43 start-page: 303 year: 2011 end-page: 315 ident: b0125 article-title: Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems publication-title: Comput-Aided Design – volume: 183 start-page: 1 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0155 article-title: Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems publication-title: Inform Sci doi: 10.1016/j.ins.2011.08.006 – year: 2007 ident: 10.1016/j.ijepes.2013.02.023_b0055 – volume: 25 start-page: 814 year: 2010 ident: 10.1016/j.ijepes.2013.02.023_b0075 article-title: Analytical expressions for DG allocation in primary distribution networks publication-title: IEEE Trans Energy Convers doi: 10.1109/TEC.2010.2044414 – volume: 20 start-page: 750 year: 2005 ident: 10.1016/j.ijepes.2013.02.023_b0060 article-title: A multiobjective evolutionary algorithm for the sizing and sitting of distributed generation publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2005.846219 – volume: 77 start-page: 685 year: 2007 ident: 10.1016/j.ijepes.2013.02.023_b0175 article-title: An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems publication-title: Electr Power Syst Res doi: 10.1016/j.epsr.2006.06.005 – volume: 32 start-page: 849 year: 2010 ident: 10.1016/j.ijepes.2013.02.023_b0070 article-title: Optimal sizing and placement of distributed generation in a network system publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2010.01.029 – volume: 19 start-page: 2068 year: 2004 ident: 10.1016/j.ijepes.2013.02.023_b0025 article-title: Analytical approaches for optimal placement of distributed generation sources in power systems publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2004.836189 – year: 2007 ident: 10.1016/j.ijepes.2013.02.023_b0050 – volume: 45 start-page: 142 year: 2013 ident: 10.1016/j.ijepes.2013.02.023_b0110 article-title: A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2012.08.043 – volume: 34 start-page: 66 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0095 article-title: A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2011.08.023 – volume: 33 start-page: 1351 year: 2005 ident: 10.1016/j.ijepes.2013.02.023_b0065 article-title: A genetic-based tabu search algorithms for optimal DG allocation in distribution networks publication-title: Electr Power Compon Syst doi: 10.1080/15325000590964254 – volume: 32 start-page: 637 year: 2010 ident: 10.1016/j.ijepes.2013.02.023_b0080 article-title: Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction and voltage improvement including voltage rise issue publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2009.11.021 – ident: 10.1016/j.ijepes.2013.02.023_b0040 doi: 10.1109/PESW.2001.916995 – volume: 84 start-page: 174 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0090 article-title: Optimization of distributed generation systems using a new discrete PSO and OPF publication-title: Electr Power Syst Res doi: 10.1016/j.epsr.2011.11.016 – volume: 37 start-page: 322 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0135 article-title: Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method publication-title: Energy doi: 10.1016/j.energy.2011.11.023 – volume: 20 start-page: 1640 year: 2005 ident: 10.1016/j.ijepes.2013.02.023_b0015 article-title: Optimal allocation of embedded generation on distribution networks publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2005.852115 – volume: 77 start-page: 1627 year: 2007 ident: 10.1016/j.ijepes.2013.02.023_b0020 article-title: Optimal DG placement in deregulated electricity market publication-title: Electr Power Syst Res doi: 10.1016/j.epsr.2006.11.014 – ident: 10.1016/j.ijepes.2013.02.023_b0130 – volume: 36 start-page: 117 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0105 article-title: Location and contract pricing of distributed generation using a genetic algorithm publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2011.10.032 – volume: 28 start-page: 669 year: 2006 ident: 10.1016/j.ijepes.2013.02.023_b0030 article-title: An analytical approach for DG allocation in primary distribution network publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2006.02.013 – volume: 25 start-page: 1577 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0145 article-title: A new multi objective optimization approach based on TLBO for location of automatic voltage regulators in distribution systems publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2012.07.004 – volume: 6 start-page: 255 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0150 article-title: Application of multi-objective teaching learning based optimization algorithm to optimal power flow problem publication-title: Proc Technol doi: 10.1016/j.protcy.2012.10.031 – volume: 4 start-page: 29 year: 2013 ident: 10.1016/j.ijepes.2013.02.023_b0165 article-title: Comparative performance of an elitist teaching-learning-based optimization algorithm for solving unconstrained optimization problems publication-title: Int J Ind Eng Comput – volume: 46 start-page: 145 year: 2013 ident: 10.1016/j.ijepes.2013.02.023_b0120 article-title: Sensitivity analysis to connect distributed generation publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2012.10.004 – volume: 4 start-page: 735 year: 1989 ident: 10.1016/j.ijepes.2013.02.023_b0170 article-title: Optimum sizing of capacitor placed on radial distribution systems publication-title: IEEE Trans PWRD – volume: 28 start-page: 413 year: 2006 ident: 10.1016/j.ijepes.2013.02.023_b0045 article-title: Optimal distributed generation allocation for reliability, losses and voltage improvement publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2006.02.003 – volume: 42 start-page: 563 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0140 article-title: Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants publication-title: Energy doi: 10.1016/j.energy.2012.02.023 – volume: 46 start-page: 250 year: 2013 ident: 10.1016/j.ijepes.2013.02.023_b0115 article-title: A new technique for optimal allocation and sizing of capacitors and setting of LTC publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2012.09.010 – volume: 5 start-page: 137 year: 2010 ident: 10.1016/j.ijepes.2013.02.023_b0005 article-title: A review of strategies for optimal placement of distributed generation in power distribution systems publication-title: Res J Appl Sci doi: 10.3923/rjasci.2010.137.145 – volume: 43 start-page: 303 year: 2011 ident: 10.1016/j.ijepes.2013.02.023_b0125 article-title: Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems publication-title: Comput-Aided Design doi: 10.1016/j.cad.2010.12.015 – volume: 3 start-page: 535 year: 2012 ident: 10.1016/j.ijepes.2013.02.023_b0160 article-title: An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems publication-title: Int J Ind Eng Comput – volume: 79 start-page: 912 year: 2009 ident: 10.1016/j.ijepes.2013.02.023_b0035 article-title: An analytical method for the sizing and siting of distributed generators in radial systems publication-title: Electr Power Syst Res doi: 10.1016/j.epsr.2008.12.007 – ident: 10.1016/j.ijepes.2013.02.023_b0010 doi: 10.1049/ip-gtd:20041193 – volume: 52 start-page: 3301 year: 2011 ident: 10.1016/j.ijepes.2013.02.023_b0085 article-title: Optimal planning of multiple distributed generation sources in distribution networks: a new approach publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2011.06.001 – volume: 33 start-page: 1429 year: 2011 ident: 10.1016/j.ijepes.2013.02.023_b0100 article-title: Simultaneous allocation of DGs and remote controllable switches in distribution networks considering multilevel load model publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2011.06.023 |
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| SubjectTerms | Applied sciences Distributed Generation (DG) Distribution systems Electric power plants Electrical engineering. Electrical power engineering Electrical power engineering Exact sciences and technology Miscellaneous Modified Teaching–Learning-Based Optimization (MTLBO) Optimal placement Power loss reduction Power networks and lines |
| Title | Optimal distributed generation location and size using a modified teaching–learning based optimization algorithm |
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