Hybrid renewable energy systems (HRES) are increasingly recognized as viable solutions to the variability inherent in renewable energy sources, enhancing the reliability, resilience, and flexibility of power supplies. This review critically evaluates recent advancements in both on-grid and off-grid microgrids that incorporate renewable energy sources (RES), battery energy storage systems (BESS), and electric vehicle (EV) infrastructure. Particular emphasis was placed on two critical aspects: optimal system sizing and energy management systems (EMS). This review further investigates how current research addresses uncertainty, particularly concerning intermittent renewable generation, load demand fluctuations, and electricity market variability. Through a synthesis of the literature, it is evident that mathematical programming, meta-heuristic optimization, and machine learning have emerged as the predominant methodologies for component sizing, energy scheduling, power balancing, and reliability enhancement. In addition to summarizing existing studies, this review identifies major methodological trends, compares the strengths and limitations of current approaches, and highlights key research gaps and future priorities. This paper provides a focused and critical overview of current HRES-based microgrid design and control strategies, offering valuable insights for researchers, practitioners, and policymakers working towards more sustainable and intelligent energy systems.
Gebru et al. (2026) studied this question.