Deep Reinforcement Learning-Based Cooperative Frequency Controller for Hydropower Dominated Systems
Xiong Hu, Xiaoyun Yang, Xing Nie, Chi Yao, Zhi‐Wei Liu · IEEE Transactions on Industrial Informatics · 2025
Hydropower dominated systems often experience negative damping and severe power flow oscillations due to improperly tuned governor parameters, even with power system stabilizers. Conventional methods optimize these parameters in a single-machine infinite bus model, neglecting interactions between generations during primary frequency control. This article proposes a deep reinforcement learning based cooperative primary frequency controller using a goal representation heuristic dynamic programming model to address this challenge. The controller minimizes power flow oscillations and frequency deviation through cooperative action among hydrogenerations. Case studies on an IEEE 9 bus system demonstrate that the proposed method achieves superior damping of power oscillations and achieves a much shorter regulation time in the primary frequency control compared to the traditional PID controllers.