Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach
This paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operat...
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MDPI AG
2021-06-01
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| Series: | Computation |
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| Online Access: | https://www.mdpi.com/2079-3197/9/6/67 |
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| author | Oscar Danilo Montoya Alexander Molina-Cabrera Luis Fernando Grisales-Noreña Ricardo Alberto Hincapié Mauricio Granada |
| author_facet | Oscar Danilo Montoya Alexander Molina-Cabrera Luis Fernando Grisales-Noreña Ricardo Alberto Hincapié Mauricio Granada |
| author_sort | Oscar Danilo Montoya |
| collection | DOAJ |
| description | This paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operator and the generation of solutions using a Gaussian normal distribution based on the exploration and exploitation schemes of the vortex search algorithm. The master stage is entrusted with determining the configuration of the phases by using an integer codification. In the slave stage, a power flow for imbalanced distribution grids based on the three-phase version of the successive approximation method was used to determine the costs of daily energy losses. The objective of the optimization model is to minimize the annual operative costs of the network by considering the daily active and reactive power curves. Numerical results from a modified version of the IEEE 37-node test feeder demonstrate that it is possible to reduce the annual operative costs of the network by approximately 20% by using optimal load balancing. In addition, numerical results demonstrated that the improved version of the CBGA is at least three times faster than the classical CBGA, this was obtained in the peak load case for a test feeder composed of 15 nodes; also, the improved version of the CBGA was nineteen times faster than the vortex search algorithm. Other comparisons with the sine–cosine algorithm and the black hole optimizer confirmed the efficiency of the proposed optimization method regarding running time and objective function values. |
| first_indexed | 2024-03-10T10:34:53Z |
| format | Article |
| id | doaj.art-24cdf2596bf541eab293fccb15a9f2e7 |
| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-03-10T10:34:53Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-24cdf2596bf541eab293fccb15a9f2e72023-11-21T23:22:23ZengMDPI AGComputation2079-31972021-06-01966710.3390/computation9060067Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization ApproachOscar Danilo Montoya0Alexander Molina-Cabrera1Luis Fernando Grisales-Noreña2Ricardo Alberto Hincapié3Mauricio Granada4Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá D.C. 11021, ColombiaFacultad de Ingeniería, Universidad Tecnológica de Pereira, Pereira 660003, ColombiaGrupo GIIEN, Facultad de Ingeniería, Institución Universitaria Pascual Bravo, Medellín 050036, ColombiaFacultad de Ingeniería, Universidad Tecnológica de Pereira, Pereira 660003, ColombiaFacultad de Ingeniería, Universidad Tecnológica de Pereira, Pereira 660003, ColombiaThis paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operator and the generation of solutions using a Gaussian normal distribution based on the exploration and exploitation schemes of the vortex search algorithm. The master stage is entrusted with determining the configuration of the phases by using an integer codification. In the slave stage, a power flow for imbalanced distribution grids based on the three-phase version of the successive approximation method was used to determine the costs of daily energy losses. The objective of the optimization model is to minimize the annual operative costs of the network by considering the daily active and reactive power curves. Numerical results from a modified version of the IEEE 37-node test feeder demonstrate that it is possible to reduce the annual operative costs of the network by approximately 20% by using optimal load balancing. In addition, numerical results demonstrated that the improved version of the CBGA is at least three times faster than the classical CBGA, this was obtained in the peak load case for a test feeder composed of 15 nodes; also, the improved version of the CBGA was nineteen times faster than the vortex search algorithm. Other comparisons with the sine–cosine algorithm and the black hole optimizer confirmed the efficiency of the proposed optimization method regarding running time and objective function values.https://www.mdpi.com/2079-3197/9/6/67three-phase distribution networksphase-balancing problemimproved Chu and Beasley genetic algorithmmutation multi-point criteriavortex search algorithmnormal Gaussian distribution |
| spellingShingle | Oscar Danilo Montoya Alexander Molina-Cabrera Luis Fernando Grisales-Noreña Ricardo Alberto Hincapié Mauricio Granada Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach Computation three-phase distribution networks phase-balancing problem improved Chu and Beasley genetic algorithm mutation multi-point criteria vortex search algorithm normal Gaussian distribution |
| title | Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach |
| title_full | Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach |
| title_fullStr | Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach |
| title_full_unstemmed | Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach |
| title_short | Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach |
| title_sort | improved genetic algorithm for phase balancing in three phase distribution networks a master slave optimization approach |
| topic | three-phase distribution networks phase-balancing problem improved Chu and Beasley genetic algorithm mutation multi-point criteria vortex search algorithm normal Gaussian distribution |
| url | https://www.mdpi.com/2079-3197/9/6/67 |
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