Makhadmeh, Sharif Naser, Al-Betar, Mohammed Azmi, Al-Obeidat, Feras, Alomari, Osama Ahmad, Abasi, Ammar Kamal and Tubishat, Mohammad (2024) A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems. Sustainable Operations and Computers, 5. pp. 88-101. ISSN 26664127
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Abstract
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.
Affiliation: | Skyline University College |
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SUC Author(s): | Elgamal, Zenab and Alomoush, Waleed |
All Author(s): | Makhadmeh, Sharif Naser, Al-Betar, Mohammed Azmi, Al-Obeidat, Feras, Alomari, Osama Ahmad, Abasi, Ammar Kamal and Tubishat, Mohammad |
Item Type: | Article |
Subjects: | A Business and Management > AS Business Strategy A Business and Management > AV Sustainable Development |
Depositing User: | Mr Mosys Team |
Date Deposited: | 26 Jun 2024 08:09 |
Last Modified: | 26 Jun 2024 08:09 |
URI: | https://research.skylineuniversity.ac.ae/id/eprint/895 |
Publisher URL: | https://doi.org/10.1016/j.susoc.2024.04.001 |
Publisher OA policy: | |
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