A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems
Document Type
Article
Publication Title
Sustainable Operations and Computers
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.
First Page
88
Last Page
101
DOI
10.1016/j.susoc.2024.04.001
Publication Date
1-1-2024
Keywords
Energy Planning Problem, Grey Wolf Optimizer, Multi-objective Optimization, Optimization, Renewable Energy System
Recommended Citation
S. Makhadmeh et al., "A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems," Sustainable Operations and Computers, vol. 5, pp. 88 - 101, Jan 2024.
The definitive version is available at https://doi.org/10.1016/j.susoc.2024.04.001