State-dependent Riccati equation and fuzzy sliding mode control for maximum power point tracking in partially shaded conditions in PV systems

Abstract

This study suggests an adaptive and optimal control method to achieve the maximum power point tracking (MPPT) in the photovoltaic (PV) systems. For the maximum power transmission under varying the environmental conditions and partially shaded conditions, MPPT technologies are utilized in PV systems. For the improvement of functioning MPPT, a new four-level control structure which decreases difficulty in the control process and efficiently deals with the uncertainties in the PV systems is introduced. The first one is a novel mechanism to estimate the reference voltage at a global maximum power point (GMPP) and an optimal and intelligent GMPP tracker (GMPPT) is employed as the last one. An extended state-dependent Riccati equation (ESDRE) approach and fuzzy sliding mode control (FMSC) are selected as a GMPPT. The FMSC generates the duty cycle for the boost converter, and the ESDRE removes the underdamped and oscillatory response of PV systems. To verify the proposed method, several irradiation profiles that create several peaks (five peaks) in the P-V curve are used. The simulation results show that the proposed method causes PV systems to track the GMPP immediately so that no oscillation around the GMPP is observed. Therefore, maximum efficiency can be derived from the PV system