Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List
This paper presents an approach to solve the unit commitment problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority List optimisation technique (MAEP-PL). The objective of this study is to search for generation scheduling such that the total operating cost can be...
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Springer Verlag
2023
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| author | Othman M.N.C. Rahman T.K.A. Mokhlis H. Aman M.M. |
| author2 | 57647356300 |
| author_facet | 57647356300 Othman M.N.C. Rahman T.K.A. Mokhlis H. Aman M.M. |
| author_sort | Othman M.N.C. |
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| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | This paper presents an approach to solve the unit commitment problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority List optimisation technique (MAEP-PL). The objective of this study is to search for generation scheduling such that the total operating cost can be minimised when subjected to a variety of constraints, while at the same time reducing its computational time. The proposed technique assimilates the concepts of Priority Listing (PL), Multi-agent System (MAS) and Evolutionary Programming (EP) as its basis. In the proposed technique, deterministic PL technique is applied to produce a population of initial solutions. The search process is refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. The developed technique is tested on ten generating units test system for a 24-h scheduling period, and the results are compared with the standard Evolutionary Programming (EP), Evolutionary Programming with Priority Listing (EP-PL) and Multi-agent Evolutionary Programming (MAEP) optimisation techniques. From the obtained results and the comparative studies, it was found that the proposed MAEP-PL optimisation technique is able to solve the unit commitment problem where the total daily generation cost is effectively minimised and the computation time is reduced as compared to other techniques. � 2015, King Fahd University of Petroleum & Minerals. |
| format | Article |
| id | my.uniten.dspace-22225 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Springer Verlag |
| record_format | dspace |
| spelling | my.uniten.dspace-222252023-05-29T13:59:42Z Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List Othman M.N.C. Rahman T.K.A. Mokhlis H. Aman M.M. 57647356300 8922419700 8136874200 55142313300 This paper presents an approach to solve the unit commitment problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority List optimisation technique (MAEP-PL). The objective of this study is to search for generation scheduling such that the total operating cost can be minimised when subjected to a variety of constraints, while at the same time reducing its computational time. The proposed technique assimilates the concepts of Priority Listing (PL), Multi-agent System (MAS) and Evolutionary Programming (EP) as its basis. In the proposed technique, deterministic PL technique is applied to produce a population of initial solutions. The search process is refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. The developed technique is tested on ten generating units test system for a 24-h scheduling period, and the results are compared with the standard Evolutionary Programming (EP), Evolutionary Programming with Priority Listing (EP-PL) and Multi-agent Evolutionary Programming (MAEP) optimisation techniques. From the obtained results and the comparative studies, it was found that the proposed MAEP-PL optimisation technique is able to solve the unit commitment problem where the total daily generation cost is effectively minimised and the computation time is reduced as compared to other techniques. � 2015, King Fahd University of Petroleum & Minerals. Final 2023-05-29T05:59:42Z 2023-05-29T05:59:42Z 2015 Article 10.1007/s13369-015-1780-0 2-s2.0-84944704050 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944704050&doi=10.1007%2fs13369-015-1780-0&partnerID=40&md5=195d79e09636e320e761662826b4aa86 https://irepository.uniten.edu.my/handle/123456789/22225 40 11 3247 3261 Springer Verlag Scopus |
| spellingShingle | Othman M.N.C. Rahman T.K.A. Mokhlis H. Aman M.M. Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List |
| title | Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List |
| title_full | Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List |
| title_fullStr | Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List |
| title_full_unstemmed | Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List |
| title_short | Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List |
| title_sort | solving unit commitment problem using multi-agent evolutionary programming incorporating priority list |
| url_provider | http://dspace.uniten.edu.my/ |