A Comprehensive Review on Applications of Grey Wolf Optimizer in Energy Systems
Mohammad Nasir (Universidad de Málaga)
Ali Sadollah (University of Science and Culture, Tehran)
Seyedali Mirjalili (Obuda University, Torrens University Australia)
Seyed Amir Mansouri (TU Delft - Energy and Industry)
Murodbek Safaraliev (Ural Federal University)
Ahmad Rezaee Jordehi (Islasmic Azad University)
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Abstract
In the field of optimization problems, the optimization of energy systems problems is of significant importance, mainly due to their dramatic role in achieving sustainability. The complexity of energy systems optimization problems, intense constraints, and various decision variables have led many researchers to utilize meta-heuristics optimization algorithms to optimize such issues and improve energy systems. Meta-heuristic algorithms that can find global solutions and prevent trapping in local optima can efficiently solve energy systems problems. Grey Wolf Optimizer (GWO), one of the well-known meta-heuristic optimizers inspired by the grouped hunting process of wolves, has been employed in different studies to deal with energy systems optimization problems. GWO has received much attention in the literature due to its proper exploratory and exploitative features, rapid and mature convergence rate, and simplicity in design and coding. This paper reviews various GWO applications for tackling optimization problems related to production, conversion, transmission and distribution, storage, and energy consumption. It is highly believed that this paper can be a practical and innovative reference for researchers, professionals, and engineers.