Cubature Kalman filter and linear quadratic regulator for load frequency control

Abstract

Several controllers address Load Frequency Control (LFC) to minimize deviations in system frequency caused due to rapid disturbances in load demand and Renewable Energy Source (RES) penetration. However, large power systems' complexity and the significant frequency deviations observed often limit these controllers. In order to address these issues, a novel Cubature Kalman filter (CKF) and Linear Quadratic Regulator (LQR) based on combined state estimation and optimal control is proposed. LQR is an optimal controller that curbs the frequency deviations by calculating optimal feedback gain values. The CKF is a novel state estimator algorithm used to estimate the state variables by minimizing the error between actual and estimated states. The proposed control is tested on a small single-area power system and a large-scale power system based in Egypt. The results obtained are compared with the existing Extended Kalman filter (EKF) and LQR-based control, Virtual Synchronous Generator (VSG) based control, and conventional Proportional-Integral-Derivative (PID) control with over and under frequency protection circuit (OUPFC). The efficacy of CKF-LQR is emphasized through the analysis of various simulation cases of the power system. The findings suggested that the proposed controller's performance was robust under frequency measurement noise, low inertia, sudden change in RES, and load switching. The outcome shows that the proposed control is robust and can effectively regulate the system frequency compared to the other controllers.