Robust Control Strategy for an Interconnected Power System with Electric Vehicle SOC Estimation

The recent widespread installation of renewable energy sources in place of fossil fuel sources and the replacement of gasoline-powered cars with electric vehicles have created several challenges. Now, reducing variation in frequency and tie-line power fluctuations must be given top priority in the control architecture of connected power networks. Renewable energy sources (RESs) represent continuously varying power generators because of their makeup and reliance on the environment. This work proposes a novel advanced Fuzzy Proportional Integral Derivative with Filter (PIDF) controller in this regard for managing load frequency and electric vehicles (EVs) in integrated power networks. Additionally, a novel application of the Pelican optimization algorithm technique for simultaneously determining the appropriate controller parameters has been carried out in the present research. Taking into account the fundamental characteristics of the sources, EVs, and load variations, the proposed controller and optimization approach is evaluated on two interconnected power systems with different RESs categories. The simulation outcomes obtained attest to the suggested controller’s and optimization method’s superior performance in terms of frequency fluctuation and tie-line power deviation mitigation, elevated robustness, and improved system stability over an extensive spectrum of parameter unpredictability.