Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization
This study deals with the minimization of the operational and investment cost in the distribution and operation of the power flow considering the installation of fixed-step capacitor banks. This issue is represented by a nonlinear mixed-integer programming mathematical model which is solved by apply...
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Published in | Electronics (Basel) Vol. 10; no. 4; p. 419 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Abstract | This study deals with the minimization of the operational and investment cost in the distribution and operation of the power flow considering the installation of fixed-step capacitor banks. This issue is represented by a nonlinear mixed-integer programming mathematical model which is solved by applying the Chu and Beasley genetic algorithm (CBGA). While this algorithm is a classical method for resolving this type of optimization problem, the solutions found using this approach are better than those reported in the literature using metaheuristic techniques and the General Algebraic Modeling System (GAMS). In addition, the time required for the CBGA to get results was reduced to a few seconds to make it a more robust, efficient, and capable tool for distribution system analysis. Finally, the computational sources used in this study were developed in the MATLAB programming environment by implementing test feeders composed of 10, 33, and 69 nodes with radial and meshed configurations. |
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AbstractList | This study deals with the minimization of the operational and investment cost in the distribution and operation of the power flow considering the installation of fixed-step capacitor banks. This issue is represented by a nonlinear mixed-integer programming mathematical model which is solved by applying the Chu and Beasley genetic algorithm (CBGA). While this algorithm is a classical method for resolving this type of optimization problem, the solutions found using this approach are better than those reported in the literature using metaheuristic techniques and the General Algebraic Modeling System (GAMS). In addition, the time required for the CBGA to get results was reduced to a few seconds to make it a more robust, efficient, and capable tool for distribution system analysis. Finally, the computational sources used in this study were developed in the MATLAB programming environment by implementing test feeders composed of 10, 33, and 69 nodes with radial and meshed configurations. |
Author | Montoya, Oscar Danilo Riaño, Fabio Edison Chamorro, Harold R. Cruz, Jonathan Felipe Alvarado-Barrios, Lazaro |
Author_xml | – sequence: 1 givenname: Fabio Edison orcidid: 0000-0003-3277-2497 surname: Riaño fullname: Riaño, Fabio Edison – sequence: 2 givenname: Jonathan Felipe orcidid: 0000-0002-2548-3518 surname: Cruz fullname: Cruz, Jonathan Felipe – sequence: 3 givenname: Oscar Danilo orcidid: 0000-0001-6051-4925 surname: Montoya fullname: Montoya, Oscar Danilo – sequence: 4 givenname: Harold R. orcidid: 0000-0003-1746-5560 surname: Chamorro fullname: Chamorro, Harold R. – sequence: 5 givenname: Lazaro orcidid: 0000-0002-6030-9582 surname: Alvarado-Barrios fullname: Alvarado-Barrios, Lazaro |
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SubjectTerms | Capacitor banks Chu and Beasley genetic algorithm combinatorial optimization Cost control Customer services discrete codification Electrical Engineering Elektro- och systemteknik Energy Feeders fixed-step capacitor banks Genetic algorithms Heuristic methods Integer programming Linear programming Mathematical models Mixed integer Net present value operative costs minimization Optimeringslära och systemteori Optimization Optimization algorithms Optimization and Systems Theory Power flow Power supply Programming environments Robustness (mathematics) Systems analysis Test systems |
Title | Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization |
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