Optimal sizing of a proposed stand-alone hybrid energy system in a remote region of southwest Egypt applying different meta-heuristic algorithms

Hybrid energy system (HES) is considered a solution to the energy supply issue, particularly in rural areas to achieve their sustainable development goals. The rise in energy consumption has increased the appeal of renewable resources, because of their potential to supply consumers with competitive,...

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Bibliographic Details
Published in:Neural computing & applications 2024-09, Vol.36 (26), p.16251-16269
Main Authors: Abdelsattar, Montaser, Mesalam, Abdelgayed, Diab, Ahmed A. Zaki, Fawzi, Abdelrahman, Hamdan, I.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Clean energy
Comparative studies
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Cost analysis
Data Mining and Knowledge Discovery
Design optimization
Dynamic control
Energy consumption
Heuristic methods
Hybrid systems
Image Processing and Computer Vision
Nuclear accidents
Original Article
Probability and Statistics in Computer Science
Renewable resources
Search algorithms
Sizing
Sustainable development
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Summary:Hybrid energy system (HES) is considered a solution to the energy supply issue, particularly in rural areas to achieve their sustainable development goals. The rise in energy consumption has increased the appeal of renewable resources, because of their potential to supply consumers with competitive, carbon-free electricity. This paper suggests strategies for managing energy and the most recently published optimizers for designing a stand-alone HES positioned in a remote region of southwest Egypt. This HES includes two green energy sources (wind and solar) and a storage system for energy (battery) as the first backup in addition to a second backup (diesel). The most recent sizing techniques employing the Chernobyl disaster optimizer, dynamic control cuckoo search (DCCS), and gold rush optimizer have been suggested to obtain the optimal design of the utilized HES. Furthermore, an in-depth evaluation of the applied optimization approaches has been achieved based on a comparative study. A detailed analysis of the studied algorithms aims to identify the optimum algorithm that provides the lowest possible cost at the highest level of reliability for the proposed HES. The simulation results verified that, the DCCS algorithm outperformed other algorithms, indicating its potential for achieving promising solutions.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-024-09902-9