Optimal capacity planning with economic emission considerations in isolated solar-wind-diesel microgrid using combined arithmetic-golden jackal optimization

• Optimization of isolated solar-wind-diesel microgrid to reduce reliance on diesel generators, lower operational costs, and mitigate environmental pollution in remote areas. • The objective is achieving optimal capacity planning by considering economic and emission dispatch factors • Optimization is carried out using combination of metaheuristic methods “arithmetic optimization algorithm” and “golden jackal optimization” to enhance the search process. • Performance analysis is conducted by simulating and comparing three scenarios of only diesel generators, solar-wind-diesel and solar-wind with low number of diesel generators. • Results demonstrate significant cost savings using the solar-wind-diesel microgrid under the proposed combined optimization method compared to the conventional methods. This study aims to optimize an isolated solar-wind-diesel microgrid to reduce reliance on diesel generators, lower operational costs, and mitigate environmental pollution in remote areas. In this optimization, arithmetic optimization algorithm and golden jackal optimization are combined for achieving optimal capacity planning, considering economic and emission dispatch factors. This combination enhances the optimization by considering the balance in exploration and exploitation offered by the arithmetic operators of the arithmetic optimization algorithm and the dynamic adjustment by the adaptive search of the golden jackal optimization. Performance analysis is conducted by simulating and comparing three scenarios of only diesel generators, solar-wind-diesel and solar-wind with low number of diesel generators. The results demonstrate significant cost savings using the solar-wind-diesel microgrid under the proposed combined optimization compared to the arithmetic optimization algorithm and golden jackal algorithm and conventional metaheuristic optimization based on genetic algorithms. Fig. 1. Methodology of the optimal capacity planning considering EED.

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Publication Details

Journal
Energy and AI
Published
2025-01-01
DOI
https://doi.org/10.1016/j.egyai.2025.100469
Citations
7
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
8.50
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article

Optimal capacity planning with economic emission considerations in isolated solar-wind-diesel microgrid using combined arithmetic-golden jackal optimization

Ehab F. El‐Saadany, Adel Merabet, Ahmed Al‐Durra, Tarek El Fouly et al.
7 citations
Energy and AI
Microgrid Control and Optimization
8.50
article

Optimal capacity planning with economic emission considerations in isolated solar-wind-diesel microgrid using combined arithmetic-golden jackal optimization

Ehab F. El‐Saadany, Adel Merabet, Ahmed Al‐Durra, Tarek El Fouly, Sujoy Barua
article en
7 citations

Abstract

• Optimization of isolated solar-wind-diesel microgrid to reduce reliance on diesel generators, lower operational costs, and mitigate environmental pollution in remote areas. • The objective is achieving optimal capacity planning by considering economic and emission dispatch factors • Optimization is carried out using combination of metaheuristic methods “arithmetic optimization algorithm” and “golden jackal optimization” to enhance the search process. • Performance analysis is conducted by simulating and comparing three scenarios of only diesel generators, solar-wind-diesel and solar-wind with low number of diesel generators. • Results demonstrate significant cost savings using the solar-wind-diesel microgrid under the proposed combined optimization method compared to the conventional methods. This study aims to optimize an isolated solar-wind-diesel microgrid to reduce reliance on diesel generators, lower operational costs, and mitigate environmental pollution in remote areas. In this optimization, arithmetic optimization algorithm and golden jackal optimization are combined for achieving optimal capacity planning, considering economic and emission dispatch factors. This combination enhances the optimization by considering the balance in exploration and exploitation offered by the arithmetic operators of the arithmetic optimization algorithm and the dynamic adjustment by the adaptive search of the golden jackal optimization. Performance analysis is conducted by simulating and comparing three scenarios of only diesel generators, solar-wind-diesel and solar-wind with low number of diesel generators. The results demonstrate significant cost savings using the solar-wind-diesel microgrid under the proposed combined optimization compared to the arithmetic optimization algorithm and golden jackal algorithm and conventional metaheuristic optimization based on genetic algorithms. Fig. 1. Methodology of the optimal capacity planning considering EED.

Energy and AIVol. 19
Khalifa University of Science and Technology (AE), Saint Mary's University (CA)
Affordable and clean energy
Openalex Percentile: Top 3%
Microgrid Control and Optimization
8.50
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