Reinforcement Learning based multi-agent LFC design concerning the integration of wind farms

Frequency regulation in interconnected networks is one of the main challenges posed by wind turbines in modern power systems. The wind power fluctuation negatively contributes to the power imbalance and frequency deviation. This paper presents an intelligent agent based load frequency control (LFC) for a multi-area power system in the presence of a high penetration of wind farms, using multi-agent reinforcement learning (MARL). Nonlinear time-domain simulations on a 39-bus test power system are used to demonstrate the capability of the proposed control scheme.