Load Frequency Control of Power Systems Using a Combination of Kalman Filtering and PI Controller

In the load frequency control (LFC) systems that incorporate electric vehicles (EVs) for frequency regulation assistance, the integration of renewable energy sources increase the system's transmission noise, severely degrading the performance of the LFC under controllers designed in a traditional environment. Addressing these challenges, this study introduces a compensatory control strategy for the PI controller, utilizing a Kalman Filter(KF)-based approach for power systems that integrate wind farms and EVs. The proposed strategy employs a Kalman Filter-based feedback mechanism to refine the outcomes of the PI control. The system architecture is designed with a dual-loop control structure, and the globally optimal Kalman gain is derived through a stochastic differential optimal calculation method. The effectiveness of this approach is demonstrated within a closed-loop control framework that ensures mean square boundedness. Simulations on a one-area LFC system validate the strategy's efficacy in mitigating the impact of random disturbances. The results indicate that this compensatory control method not only enhances the system's control performance but also significantly improves its robustness, thereby reducing the detrimental effects of random noise on the system's control quality.