Model Predictive Control-Adaptive Neuro-Fuzzy Inference System Control Strategies for Photovoltaic-Wind Microgrid: Feasibility Review

Microgrids are increasingly gaining attention in the modern power industry. This is because it provides an attractive technology for utilizing distributed renewable energy resources such as Photovoltaic (PV) and Wind. The main problem currently facing PV-Wind microgrids is that of lower power quality due to their intermittent nature. This leads to variations in voltage and frequency which must be regulated and managed using a microgrid control system. This paper reviews the application of Model Predictive Control (MPC) and Adaptive Neuro-Fuzzy Inference System (ANFIS) control strategies to PV-Wind based microgrids. The outcome of the review was that these two control strategies can be hybridized to complement each other when applied in a Multilevel Microgrid Control System (MMCS). This improves the power quality of the microgrid in terms of better regulation of voltage and frequency. The research directions in this field lean towards the hybridization of artificial intelligence with analytical methods to optimize microgrid performance.