Affiliation:
1. School of Art Hunan City University Yiyang China
2. Department of Education Graduate School of Sehan University Jeollanam‐do South Korea
3. The Second Ship Design Institute of Wuhan Wuhan China
4. University of Tehran Tehran Iran
5. College of Technical Engineering The Islamic University Najaf Iraq
Abstract
AbstractThis study provides an optimal and efficient energy management strategy (EMS) for the cost‐effective performance of a combined solar and green energy microgrid in both independent and grid‐connected modes. A microgrid is formed by the system that includes a fuel cell (FC), a battery storage (BS), and a photovoltaic system (PV). Evidently, the unguaranteed features of the renewable energy and load electricity generate instability problems as well as economic ones, like operational expenses. To tackle these issues, a novel procedure is proposed that has been improved by a modified metaheuristic algorithm, called chaotic map‐based chameleon Swarm Algorithm (CCSA). In this method, the simulation is based on a one‐day planning perspective. The method aims to supply the power requirements of the load at the lowest possible cost under a constant DC bus voltage, protect the battery from overcharging and depletion, and improve the efficiency of the total system. To illustrate the suggested method's effectiveness, the simulation results of CCSA are compared with some studied methods in the literature, including GAMS, bald eagle search optimization algorithm (BEOA), original chameleon swarm algorithm (CSA), and grey wolf optimization algorithm (GWOA).
Publisher
Institution of Engineering and Technology (IET)
Subject
Renewable Energy, Sustainability and the Environment
Cited by
3 articles.
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