A novel online learning-based linear quadratic regulator for vanadium redox flow battery in DC microgrids

Abstract

This paper proposes a novel learning-based linear quadratic regulator (LQR) to overcome the long-lasting problem of model dependency in the existing vanadium redox flow battery (VRB) control approaches. Compared to the conventional model-dependent control methods, such as PI control and model predictive control (MPC), the proposed method automatically updates the optimal control policy through the online learning mechanism without any knowledge of the VRB system dynamics. The ability of the proposed method to handle uncertainties is verified by simulations under various scenarios.