A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems
This paper presents the energy planning problem (EPP) as an optimization problem to find the optimal schedules to minimize energy consumption costs and demand and enhance users’ comfort levels. The grey wolf optimizer (GWO), One of the most powerful optimization methods, is adjusted and adapted to a...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co. Ltd.
2024-01-01
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| Series: | Sustainable Operations and Computers |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666412724000059 |
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| author | Sharif Naser Makhadmeh Mohammed Azmi Al-Betar Feras Al-Obeidat Osama Ahmad Alomari Ammar Kamal Abasi Mohammad Tubishat Zenab Elgamal Waleed Alomoush |
| author_facet | Sharif Naser Makhadmeh Mohammed Azmi Al-Betar Feras Al-Obeidat Osama Ahmad Alomari Ammar Kamal Abasi Mohammad Tubishat Zenab Elgamal Waleed Alomoush |
| author_sort | Sharif Naser Makhadmeh |
| collection | DOAJ |
| description | This paper presents the energy planning problem (EPP) as an optimization problem to find the optimal schedules to minimize energy consumption costs and demand and enhance users’ comfort levels. The grey wolf optimizer (GWO), One of the most powerful optimization methods, is adjusted and adapted to address EPP optimally and achieve its objectives efficiently. The GWO is adapted due to its high performance in addressing NP-complex hard problems like the EPP, where it contains efficient and dynamic parameters that enhance its exploration and exploitation capabilities, particularly for large search spaces. In addition, new energy and real-world resources based on solar renewable energy systems (RESs) are combined with the proposed GWO to enhance its performance and ensure the optimisation of EPP objectives. Furthermore, EPP is presented as a multi-objective planning problem to optimize all objectives simultaneously. To efficiently investigate the proposed method performance, the results obtained by the GWO with the RESs are compared in three stages: comparison with original methods without RESs, comparison with methods using RESs, and comparison with state-of-the-art. The obtained results proved the robust performance of the proposed method in handling EPP and optimizing its objectives. |
| format | Article |
| id | doaj-art-61566f2eb3a34a4f9667cc3eba59cf9e |
| institution | OA Journals |
| issn | 2666-4127 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | KeAi Communications Co. Ltd. |
| record_format | Article |
| series | Sustainable Operations and Computers |
| spelling | doaj-art-61566f2eb3a34a4f9667cc3eba59cf9e2025-08-20T02:07:35ZengKeAi Communications Co. Ltd.Sustainable Operations and Computers2666-41272024-01-0158810110.1016/j.susoc.2024.04.001A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systemsSharif Naser Makhadmeh0Mohammed Azmi Al-Betar1Feras Al-Obeidat2Osama Ahmad Alomari3Ammar Kamal Abasi4Mohammad Tubishat5Zenab Elgamal6Waleed Alomoush7Corresponding author.; Department of Data Science and Artificial Intelligence, University of Petra, Amman, 11196, Jordan; Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab EmiratesArtificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates; Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, P.O. Box 50, Al-Huson, Irbid, JordanCollege of Technological Innovation, Zayed University, Abu Dhabi, United Arab EmiratesDepartment of Computer Science and Information Technology, College of Engineering, Abu Dhabi University, Abu Dhabi, United Arab EmiratesMachine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab EmiratesCollege of Technological Innovation, Zayed University, Abu Dhabi, United Arab EmiratesSchool of Computing, Skyline University College, Sharjah, UAESchool of Information Technology, Skyline University College, Sharjah P.O. Box 1797, United Arab EmiratesThis paper presents the energy planning problem (EPP) as an optimization problem to find the optimal schedules to minimize energy consumption costs and demand and enhance users’ comfort levels. The grey wolf optimizer (GWO), One of the most powerful optimization methods, is adjusted and adapted to address EPP optimally and achieve its objectives efficiently. The GWO is adapted due to its high performance in addressing NP-complex hard problems like the EPP, where it contains efficient and dynamic parameters that enhance its exploration and exploitation capabilities, particularly for large search spaces. In addition, new energy and real-world resources based on solar renewable energy systems (RESs) are combined with the proposed GWO to enhance its performance and ensure the optimisation of EPP objectives. Furthermore, EPP is presented as a multi-objective planning problem to optimize all objectives simultaneously. To efficiently investigate the proposed method performance, the results obtained by the GWO with the RESs are compared in three stages: comparison with original methods without RESs, comparison with methods using RESs, and comparison with state-of-the-art. The obtained results proved the robust performance of the proposed method in handling EPP and optimizing its objectives.http://www.sciencedirect.com/science/article/pii/S2666412724000059Renewable Energy SystemOptimizationGrey Wolf OptimizerEnergy Planning ProblemMulti-objective Optimization |
| spellingShingle | Sharif Naser Makhadmeh Mohammed Azmi Al-Betar Feras Al-Obeidat Osama Ahmad Alomari Ammar Kamal Abasi Mohammad Tubishat Zenab Elgamal Waleed Alomoush A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems Sustainable Operations and Computers Renewable Energy System Optimization Grey Wolf Optimizer Energy Planning Problem Multi-objective Optimization |
| title | A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems |
| title_full | A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems |
| title_fullStr | A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems |
| title_full_unstemmed | A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems |
| title_short | A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems |
| title_sort | multi objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems |
| topic | Renewable Energy System Optimization Grey Wolf Optimizer Energy Planning Problem Multi-objective Optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2666412724000059 |
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