Heuristic Evolutionary Optimization for Control and Management of Renewable-Based Hybrid Microgrids

The surge in renewable energy and distributed generation necessitates advanced control systems for network performance enhancement. However, the lack of a standardized evaluation framework hampers comparisons, especially in complex hybrid networks. Hybrid energy systems offer greener and more reliable networks but require sophisticated control methods. To address this challenge, research explores novel linear and nonlinear techniques. This overview focuses on heuristic evolutionary optimization methods for Microgrids, covering AC, DC, and hybrid AC-DC systems, highlighting current research and future control requirements.