Backstepping Based Real Twisting Sliding Mode Control for Photovoltaic System

Abstract

The renewable energy sources tied to a utility grid require non-linear control algorithms to provide an efficient and stable output under different operating conditions. The maximum power point tracking (MPPT) approach is necessary for power generation due to weather condition at photovoltaic (PV). In changing environmental and partial shading conditions, the standard MPPT methods may lead to variations in output results. The scheme considered in this thesis is nonlinear MPPT control of standalone PV-BES system to supply power to the load. The considered system consists of photovoltaic system, battery storage system, non-inverting buck boost unidirectional converter, buck boost bidirectional converter, and resistive load. The unidirectional buck boost converter tracks the maximum power point of the photovoltaic system by controlling the duty cycle of the buck boost converter. The role of the battery in this scenario is to regulate the DC link voltage. In PV-BES system, the proposed scheme is flexible in terms of convergence, robustness, and DC bus regulation. In addition to this a nonlinear robust, fast convergent a control scheme is proposed in this study for PV-BES system. A backstepping based real twisting sliding mode (MPPT) control is proposed for the PV-BES system where maximum available power is extracted by tracking PV voltage. Moreover, a direct sliding mode control is proposed for battery-integrated buck boost converter for voltage regulation. Reference sliding surface is generated through linear interpolation based on predicted maximum power point PV voltage. The proposed MPPT strategy is tested against variations of irradiance, temperature, and load. Simulation results highlight superior tracking performance, reduced chattering, and oscillations of this technique over existing models