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

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.