ECONOMIC AND ENERGY MANAGEMENT OF MICROGRID USING METAHEURISTIC TECHNIQUES: A REVIEW

Abstract

To address problems with energy management in microgrids, this paper examines several methods for calculating emissions and economics. Microgrid efficiency may be improved by integrating various energy sources, such as solar, wind, and battery energy storage systems (BESS). This can be achieved by a thorough examination of various technologies and existing innovations in the field. Keeping the system stable, controlling energy, ensuring a steady power supply, reducing emissions of greenhouse gases, and keeping operational costs down are the main goals. This paper presents a variety of optimization algorithms for energy management systems, including hybrid, opposition-based, metaheuristic, AI, and classical approaches. Microgrid design and development in the modern day is thoroughly examined in this book, which covers topics such as artificial neural networks (ANNs), fuzzy logic, ML, neural networks, reinforcement learning, etc. The essay acknowledged more than 200 scholarly journals.