Control strategies for grid-connected hybrid renewable energy systems: Integrating modified direct torque control based doubly fed induction generator and ANFIS based maximum power point tracking for solar PV generation
Mihir Mehta, Bhinal Mehta
Abstract
This research article introduces advanced control strategies for grid-connected hybrid renewable energy systems, focusing on a doubly fed induction machine (DFIM) based wind power plant and a photovoltaic based solar power plant. The proposed approach integrates Direct Torque Control (DTC) with modified filters and a fractional Proportional-Integral (PI) controller for the DFIM wind power plant. The modified DTC utilizes estimated torque and flux, employing a modified filter to minimize deviations, and a fractional PI controller for improved vector selection. This results in an enhanced duty cycle for the rotor side converter, optimizing power output to the grid. Additionally, an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Maximum Power Point Tracking (MPPT) algorithm is implemented for the solar power plant, dynamically adjusting the duty cycle for increased power output compared to conventional MPPT methods. Simulation results in MATLAB and experimental verification demonstrates the stability and feasibility of the proposed controllers, showcasing superior performance compared to conventional counterparts under various operating conditions.