Advanced Control Strategies for Mitigating Frequency Deviations in Electric Vehicle Connected Power Systems

he rising demand for electric vehicles (EVs) is driving up the demand for electrical charging stations, which presents serious threats to the stability of the power system, including frequency variations that go beyond allowable bounds. In response, this paper proposes advanced control techniques to regulate the governor of generators and mitigate frequency deviations in EV-connected power systems. Specifically, the utilization of Proportional-Integral (PI) controllers for governor control and the integration of Artificial Neural Networks (ANN) with fuzzy logic are explored to develop a robust control strategy. The proposed control system dynamically adjusts generator parameters in response to varying EV charging demands, leveraging ANN's adaptive learning capabilities and fuzzy logic's linguistic reasoning to enhance grid stability and ensure frequency within acceptable limits. Through simulation studies and performance evaluations using MATLAB/SIMULINK tools, the efficacy of the proposed approach is demonstrated, offering a promising solution to mitigate adverse effects of EV-induced power imbalances on power system frequency.