Soft Computing Based Performance Analysis of PV-Wind Hybrid System

This paper proposes a hybrid system that combines photovoltaic (PV), wind, and batteries. A PV system is built using mathematical analysis to optimize its performance, and a DC-DC boost converter is proposed. This study uses various maximum power point tracking (MPPT) approaches to get the most power out of the PV system. A doubly-fed induction generator (DFIG)-based wind simulator was utilized to create a wind energy system capable of operating at any speed. The DFIG system’s rotor-side and grid-side converters were both designed with appropriate control approaches. The needed reference signal for pulse width modulation (PWM) controllers is derived from system currents and transformed to two-phase coordinates, i.e. direct and quadrature axis models. An IGBT-based bidirectional converter incorporating a battery system is intended for energy storage. To ensure perfect synchronization between DG systems and the grid, a three-phase inverter is equipped with a PWM-based controller, which also helps to reduce power-quality distortion. The proposed hybrid system was realized in real-time hardware, using a 1 kW PV and a 1.5 kW wind system. MPPT approaches’ algorithms, such as perturb and observe (P&O) and incremental conductance (INC), were implemented in an FPGA controller. This paper provides a power management method for the suggested hybrid system that employs P&O and INC algorithms under varying load situations.