Energy management system for an isolated microgrid based on Fuzzy logic control and meta-heuristic algorithms

Nowadays, the emergence of isolated-mode microgrids is becoming more notorious for supplying electricity to isolated rural areas. However, the optimal implementation of a microgrid depends on several factors, such as its geographical location, sizing, operating cost, social impact, among others. Therefore, it is necessary to propose feasible solutions for incorporating systems based on isolated microgrids to improve the coverage of electric power in developing countries such as Ecuador, where microgrid implementations are still not reported. In this regard, this study proposes a design of an Energy Management System (EMS) based on Fuzzy Logic Control (FLC) for isolated microgrids. The proposed approach uses the forecast of generation and load powers, considers the diesel generator start-up and shut-down operation times, takes advantage of the available solar resource, and keeps the State of Charge (SOC) value of the battery storage system within the safety limits. In addition, the membership functions of the designed FLC are adjusted and compared using meta-heuristic algorithms such as Cuckoo Search (CS) and Particle Swarm Optimization (PSO) to find better solutions. The results show that the EMS adjusted with the PSO algorithm improves the performance.