Day-ahead Strategic Bidding of Renewable Energy Considering Output Uncertainty Based on Deep Reinforcement Learning

Uncertainty in the output of renewable energy sources can lead to fluctuations in the bidding revenue of their participation in the electricity market. To address this problem, a stochastic optimization model for strategic bidding of renewable energy unit considering output uncertainty is established. The conditional value-at-risk and Soft Actor-Critic algorithm are combined to form the CVaR-SAC strategic bidding algorithm that can control the risk of fluctuation in bidding revenue, and the effectiveness of the algorithm is verified through cases.