A genetic-based algorithm for fuzzy unit commitment model
This paper presents a fuzzy model for the unit commitment problem (UCP). The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. In the implementatio...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | article |
| منشور في: |
2000
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/14776/1/14776_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14776/2/14776_2.doc |
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| _version_ | 1864513394293342208 |
|---|---|
| author | Mantawy, A.H. |
| author2 | unknown |
| author2_role | author |
| author_facet | Mantawy, A.H. unknown |
| author_role | author |
| dc.creator.none.fl_str_mv | Mantawy, A.H. unknown |
| dc.date.none.fl_str_mv | 2000 2020 |
| dc.format.none.fl_str_mv | application/pdf application/msword |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14776/1/14776_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14776/2/14776_2.doc (2000) A genetic-based algorithm for fuzzy unit commitment model. Power Engineering Society Summer Meeting, 2000. IEEE, 1. |
| dc.language.none.fl_str_mv | en en |
| dc.publisher.none.fl_str_mv | IEEE |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14776/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | A genetic-based algorithm for fuzzy unit commitment model |
| dc.type.none.fl_str_mv | Article PeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | This paper presents a fuzzy model for the unit commitment problem (UCP). The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. In the implementation for the GA, coding of the UCP solutions is based on mixing binary and decimal representations. A fitness function is constructed from the total operating cost of the generating units plus a penalty term determined due to the fuzzy load and spinning reserve membership functions. Numerical results showed an improvement in the solutions costs compared to the results reported in the literature and the GA with crisp UCP model |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_c201f5f8b3e72afbc03435d782b9dce2 |
| identifier_str_mv | (2000) A genetic-based algorithm for fuzzy unit commitment model. Power Engineering Society Summer Meeting, 2000. IEEE, 1. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::14776 |
| publishDate | 2000 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A genetic-based algorithm for fuzzy unit commitment modelMantawy, A.H.unknownComputerThis paper presents a fuzzy model for the unit commitment problem (UCP). The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. In the implementation for the GA, coding of the UCP solutions is based on mixing binary and decimal representations. A fitness function is constructed from the total operating cost of the generating units plus a penalty term determined due to the fuzzy load and spinning reserve membership functions. Numerical results showed an improvement in the solutions costs compared to the results reported in the literature and the GA with crisp UCP modelIEEE20002020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14776/1/14776_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14776/2/14776_2.doc (2000) A genetic-based algorithm for fuzzy unit commitment model. Power Engineering Society Summer Meeting, 2000. IEEE, 1. enenhttps://eprints.kfupm.edu.sa/id/eprint/14776/info:eu-repo/semantics/openAccessoai::147762019-11-01T14:07:25Z |
| spellingShingle | A genetic-based algorithm for fuzzy unit commitment model Mantawy, A.H. Computer |
| status_str | publishedVersion |
| title | A genetic-based algorithm for fuzzy unit commitment model |
| title_full | A genetic-based algorithm for fuzzy unit commitment model |
| title_fullStr | A genetic-based algorithm for fuzzy unit commitment model |
| title_full_unstemmed | A genetic-based algorithm for fuzzy unit commitment model |
| title_short | A genetic-based algorithm for fuzzy unit commitment model |
| title_sort | A genetic-based algorithm for fuzzy unit commitment model |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/14776/1/14776_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14776/2/14776_2.doc |