Solving economic dispatch problem with valve-point effects using swarm-based mean–variance mapping optimization (MVMOS)
Mean–variance mapping optimization (MVMO) is a new population-based metaheuristic technique which is successfully applied for different power system optimization problems. The special feature of MVMO is the mapping function applied for the mutation based on the mean and variance of n-best population...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2015-12-01
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| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/23311916.2015.1076983 |
| _version_ | 1797725842165465088 |
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| author | T.H. Khoa P.M. Vasant M.S. Balbir Singh V.N. Dieu |
| author_facet | T.H. Khoa P.M. Vasant M.S. Balbir Singh V.N. Dieu |
| author_sort | T.H. Khoa |
| collection | DOAJ |
| description | Mean–variance mapping optimization (MVMO) is a new population-based metaheuristic technique which is successfully applied for different power system optimization problems. The special feature of MVMO is the mapping function applied for the mutation based on the mean and variance of n-best population. Recently, the modified version of MVMO has been developed to become more powerful, named as swarm-based mean–variance mapping optimization (MVMOS). This paper proposes MVMOS as a new approach for solving the economic dispatch (ED) problem considering valve-point effects. To validate the performance of the proposed method, the MVMOS is tested on three systems including 3, 13, and 40 thermal generating units with valve-point effects and the obtained results from MVMOS are compared to those from other existing methods in the literature. Test results have indicated that the proposed MVMOS is more robust and produces better solution quality than many other methods. Therefore, the MVMOS is efficient for solving the ED with valve-point effects. |
| first_indexed | 2024-03-12T10:37:02Z |
| format | Article |
| id | doaj.art-d915c8df839b44f692fa63ff9c25f590 |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-03-12T10:37:02Z |
| publishDate | 2015-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-d915c8df839b44f692fa63ff9c25f5902023-09-02T08:41:23ZengTaylor & Francis GroupCogent Engineering2331-19162015-12-012110.1080/23311916.2015.10769831076983Solving economic dispatch problem with valve-point effects using swarm-based mean–variance mapping optimization (MVMOS)T.H. Khoa0P.M. Vasant1M.S. Balbir Singh2V.N. Dieu3Universiti Teknologi PETRONASUniversiti Teknologi PETRONASUniversiti Teknologi PETRONASHCMC University of TechnologyMean–variance mapping optimization (MVMO) is a new population-based metaheuristic technique which is successfully applied for different power system optimization problems. The special feature of MVMO is the mapping function applied for the mutation based on the mean and variance of n-best population. Recently, the modified version of MVMO has been developed to become more powerful, named as swarm-based mean–variance mapping optimization (MVMOS). This paper proposes MVMOS as a new approach for solving the economic dispatch (ED) problem considering valve-point effects. To validate the performance of the proposed method, the MVMOS is tested on three systems including 3, 13, and 40 thermal generating units with valve-point effects and the obtained results from MVMOS are compared to those from other existing methods in the literature. Test results have indicated that the proposed MVMOS is more robust and produces better solution quality than many other methods. Therefore, the MVMOS is efficient for solving the ED with valve-point effects.http://dx.doi.org/10.1080/23311916.2015.1076983mean–variance mapping optimizationeconomic dispatchvalve-point effectsmetaheuristicnonconvex objective functionswarm-based mean-variance mapping optimization |
| spellingShingle | T.H. Khoa P.M. Vasant M.S. Balbir Singh V.N. Dieu Solving economic dispatch problem with valve-point effects using swarm-based mean–variance mapping optimization (MVMOS) Cogent Engineering mean–variance mapping optimization economic dispatch valve-point effects metaheuristic nonconvex objective function swarm-based mean-variance mapping optimization |
| title | Solving economic dispatch problem with valve-point effects using swarm-based mean–variance mapping optimization (MVMOS) |
| title_full | Solving economic dispatch problem with valve-point effects using swarm-based mean–variance mapping optimization (MVMOS) |
| title_fullStr | Solving economic dispatch problem with valve-point effects using swarm-based mean–variance mapping optimization (MVMOS) |
| title_full_unstemmed | Solving economic dispatch problem with valve-point effects using swarm-based mean–variance mapping optimization (MVMOS) |
| title_short | Solving economic dispatch problem with valve-point effects using swarm-based mean–variance mapping optimization (MVMOS) |
| title_sort | solving economic dispatch problem with valve point effects using swarm based mean variance mapping optimization mvmos |
| topic | mean–variance mapping optimization economic dispatch valve-point effects metaheuristic nonconvex objective function swarm-based mean-variance mapping optimization |
| url | http://dx.doi.org/10.1080/23311916.2015.1076983 |
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