Optimal Type-2 Fuzzy Logic Control for Sizing and Control Grid Connected PV System with Battery

In this study, Grey Wolf Optimizer (GWO) is employed to optimally design the system depending on the percentage of the possibility of power supply interruption loss of power supply probability (LPSP) to reach the lowest possible cost of the grid connected PV system with battery (GCPVB). Also, GWO is used to determine the optimal gains of Type2- fuzzy logic controllers (T2-FLC) for photovoltaic (PV) power plants to ensure maximum power point tracking (MPPT) of the GCPVB system based on incremental conductance (IC) algorithm. The T2FLC controller is designed to regulate the system’s power flow and ensure that the battery is charged and discharged at optimal rates, while the LPSP is used to determine the optimal battery capacity required to minimize the loss of power supply. The proposed strategy is evaluated using simulation studies under different operating conditions, including varying solar irradiance, load demand, and LPSP. The simulation results demonstrate that the proposed strategy can improve the performance and reduce the cost of operation of the PV system compared to other control techniques, such as conventional Fuzzy Logic Control (FLC) and Proportional- Integral-Derivative (PID) control. Overall, the proposed strategy provides a promising solution for optimizing the sizing and control of GCPVB systems with battery storage and can be used in real-world applications.