This review explores the crucial role of control strategies in optimizing MG operations and ensuring efficient utilization of distributed energy resources, storage systems, networks, and loads. First, a hybrid prediction model. This paper proposes an integrated framework to improve microgrid energy management through the integration of renewable energy sources, electric vehicles, and adaptive demand response strategies. Integrating diverse renewable energy sources into the grid has further emphasized the need for effec-tive management and sophisticated. Microgrids are essential to the development of the present and future electricity networks, as they can provide many advantages to the expanding and complex power systems, such as better power quality, increased integration of clean and renewable energy sources, increased efficiency, and increased. This paper investigates the application of ant colony optimization (ACO) for energy management in microgrids, incorporating distributed generation resources such as solar panels, fuel cells, wind turbines, battery storage, and microturbine. The study evaluates energy management in two scenarios.