Adaptive Control for Virtual Synchronous Generator Parameters Based on Soft Actor Critic
Chuang Lu,
Xiangtao Zhuan
Abstract:This paper introduces a model-free optimization method based on reinforcement learning (RL) aimed at resolving the issues of active power and frequency oscillations present in a traditional virtual synchronous generator (VSG). The RL agent utilizes the active power and frequency response of the VSG as state information inputs and generates actions to adjust the virtual inertia and damping coefficients for an optimal response. Distinctively, this study incorporates a setting-time term into the reward function d… Show more
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