A comprehensive review of microgrid control methods: Focus on AI, optimization, and predictive techniques - Limouni, Tariq; Yaagoubi, Reda; Bouziane, Khalid; Guissi, Khalid; Baali, El Houssain (Computers & electrical engineering, 2025)
•A review of recent control techniques, with a focus on AI, optimization, and predictive methods, is presented.•Control techniques are reviewed based on the control objectives, architecture, and microgrid characteristics.•This assessment highlights the benefits and limitations of various control methods.•This review explores the potential and challenges for hybridizing control techniques and emphasizes the need for more intelligent solutions.•Key research directions for future studies on microgrid control were identified. With the depletion of fossil fuels, the integration of renewable energy sources as distributed energy resources has become mandatory. However, the uncertainty and intermittent nature of these sources introduce significant challenges to their integration into microgrids. Effective control systems are essential for ensuring smooth integration, managing energy storage systems, and maintaining microgrid safety. In this study, a review of recent control methods applied in microgrid management was conducted with a focus on AI, optimization, and predictive techniques. These advanced and intelligent control methods were chosen for their potential to address current challenges. This study examined the benefits, limitations, and areas for future improvement. In addition, it explores the potential and the challenges of hybrid control techniques, which are less discussed in the literature, to further enhance control system efficiency and performance.