Research on load frequency control of interconnected power grid with wind power based on RL-MPC algorithm

Abstract

To address the frequency fluctuations in the power system caused by a high proportion of new energy integration, this paper proposes a load frequency control of interconnected power grid with wind power based on reinforcement learning model predictive control(RL-MPC) algorithm. Firstly, considering the dynamic parameters of the model caused by changes in wind speed output, a two region load frequency control model with wind power participation was constructed. Then, reinforcement learning is used to optimize the parameters of model predictive control in the system in real time, reducing the dependence of control schemes on accurate models and ensuring that the controller can adaptively adjust to changes in system parameters in the case of uncertain wind power output, to ensure the optimal frequency control effect. Finally, the effectiveness of the proposed control strategy was verified through algorithm simulation comparison.

Keywords

load frequency control / wind power uncertainty / model predictive control / reinforcement learning