A Novel Solution for Solving the Frequency Regulation Problem of Renewable Interlinked Power System Using Fusion of AI

The requirement for clean energy has increased drastically over the years due to the emission of CO₂ and the degrading of the environment by introducing Renewable Energy Systems (RES) into the existing power grid. While these systems are a positive change, they come at a cost, with some issues relating to the stability of the grid and feasibility. Hence, this research paper closely investigates the modeling and interlinking of photovoltaic (PV)-based solar power and Double-Fed Induction Generator (DFIG)-based wind turbines with the conventional power systems. RES has been known to contribute to a highly non-linear system and complexity. To return the power systems to their original state after a load disturbance, a novel control technique based on the fractional-order Type-2 Fuzzy logic system, well developed via particle swarm optimization (PSO), has been utilized for solving the frequency control problem of a renewable interlinked power system. The efficacy of the proposed technique is validated for various possible operating conditions and the system results are compared with some of the recent methods with and without including non-linearity, and the performance of the controllers is superimposed on frequency/time graphs for ease of understanding to show the benefits of the proposed research work.