Multi-objective distribution network reconfiguration optimization problem
This paper dealt with the optimal reconfiguration of a power distribution network where a genetic algorithm (GA) based on graph theory was considered. This paper addressed this issue as a multi-criteria one with low investment cost and reduced active power losses objectives. The topological and volt...
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| Vydáno v: | Electrical engineering Ročník 101; číslo 1; s. 45 - 55 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.04.2019
Springer Nature B.V |
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| ISSN: | 0948-7921, 1432-0487 |
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| Abstract | This paper dealt with the optimal reconfiguration of a power distribution network where a genetic algorithm (GA) based on graph theory was considered. This paper addressed this issue as a multi-criteria one with low investment cost and reduced active power losses objectives. The topological and voltage stability constraints were taken into account in this study, and each objective was firstly optimized individually. The Pareto-optimality principle for the criteria trade-off was then presented. In order to calculate the active power losses, a new load-flow approach was implemented. The genetic algorithm was tested on IEEE 10-bus system. Results show that the proposed load-flow algorithm was an efficient tool to obtain an accurate calculus for the system power losses. Efficiency and capability of the GA to achieve good solutions in a conspicuously short time are also discussed, and all the simulation results explained that the two objectives mentioned above are conflicting with each other. |
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| AbstractList | This paper dealt with the optimal reconfiguration of a power distribution network where a genetic algorithm (GA) based on graph theory was considered. This paper addressed this issue as a multi-criteria one with low investment cost and reduced active power losses objectives. The topological and voltage stability constraints were taken into account in this study, and each objective was firstly optimized individually. The Pareto-optimality principle for the criteria trade-off was then presented. In order to calculate the active power losses, a new load-flow approach was implemented. The genetic algorithm was tested on IEEE 10-bus system. Results show that the proposed load-flow algorithm was an efficient tool to obtain an accurate calculus for the system power losses. Efficiency and capability of the GA to achieve good solutions in a conspicuously short time are also discussed, and all the simulation results explained that the two objectives mentioned above are conflicting with each other. |
| Author | Souifi, Hayfa Kahouli, Omar Hadj Abdallah, Hsan |
| Author_xml | – sequence: 1 givenname: Hayfa surname: Souifi fullname: Souifi, Hayfa email: ha.souifi@gmail.com organization: Electrical Department, National Engineering School of Sfax-Tunisia (ENIS Tunisia), Sfax University – sequence: 2 givenname: Omar surname: Kahouli fullname: Kahouli, Omar organization: Electrical Department, National Engineering School of Sfax-Tunisia (ENIS Tunisia), Sfax University – sequence: 3 givenname: Hsan surname: Hadj Abdallah fullname: Hadj Abdallah, Hsan organization: Electrical Department, National Engineering School of Sfax-Tunisia (ENIS Tunisia), Sfax University |
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| Cites_doi | 10.1016/j.epsr.2013.06.010 10.1109/TPWRS.2012.2197227 10.1109/TPWRS.2010.2059051 10.3390/en10040455 10.1109/TPWRD.2011.2179950 10.1016/j.epsr.2009.05.004 10.1016/j.epsr.2012.12.005 10.1007/s12667-016-0195-7 10.1109/TPWRS.2007.913303 10.1016/j.epsr.2005.03.002 10.1016/j.ijepes.2012.08.005 10.1090/S0002-9939-1956-0078686-7 10.1016/j.epsr.2013.06.021 10.1109/61.25627 10.1109/TPWRS.2008.920047 10.1016/j.ijepes.2011.10.031 10.1016/j.ijepes.2015.06.020 10.1109/EPSCICON.2014.6887494 10.25130/tjes.20.3.08 |
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| Keywords | Voltage stability Graph theory Load-flow Distribution network reconfiguration Genetic algorithm Optimization |
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| SubjectTerms | Computer simulation Economics and Management Electric power distribution Electrical Engineering Electrical Machines and Networks Energy Policy Engineering Genetic algorithms Graph theory Load-Flow Mathematical analysis Multiple criterion Multiple objective analysis Networks Original Paper Pareto optimization Power efficiency Power Electronics Power loss Reconfiguration Voltage stability |
| Title | Multi-objective distribution network reconfiguration optimization problem |
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