This study reviews the applications of fuzzy logic in energy management systems (EMS) for hybrid renewable energy systems (HRES). Hybrid Renewable Energy Systems (HRES) constitute a collection of renewable sources, including solar, wind or hydropower to provide energy reliably and sustainably, however their performance is highly influenced by the intermittent and unpredictable characteristics of green energy generation. Thanks to its capacity to work in the shaded overall vision, fuzzy logic is an excellent fit for this obstacle in spite of uncertainty, undeniable and deficient information. The key components of the fuzzy logic-based EMS are (fuzzification, rule base, inference mechanism and defuzzification) which demonstrate how these components support an adaptive and intelligent energy management. This contributes to the flexibility, efficiency and reliability of HRES by dynamically responding to fluctuations in energy generation and demand. As per the paper, using fuzzy logic together with artificial intelligence and machine learning can also help improve forecasting and decision-making. All in all, fuzzy logic shows itself as a useful mechanism for sustainable energy optimization.
Adedeji et al. (Thu,) studied this question.