Under the background of dual carbon, China is actively building a new power system with renewable energy as the main body, and vigorously promoting the reform of power marketization. The disorderly access of a large number of renewable energy power plants will bring enormous pressure to the safe and stable operation of the power system, and will not be conducive to their participation in market competition as independent entities. This paper first takes "renewable energy + energy storage" power plants as price receivers, participates in the spot electricity transactions in the form of "quote volume without quotation". Secondly, the stochastic optimization method is used to construct renewable energy output scenarios, day-ahead and real-time clearing electricity price scenarios, and the K-medoids method is used to convert a large number of scenarios into a limited number of probabilistic deterministic scenarios. Then, with the goal of maximizing the day-ahead benefits, considering the conditional value-at-risk and taking into account the unbalanced penalty costs, an optimal bidding strategy model of "renewable energy + energy storage" power plants participating in the day-ahead market is established and solved. Finally, a numerical simulation is carried out with the historical output data of a wind power plant and the electricity price data in the spot market, and the simulation results verify the effectiveness of the proposed bidding strategy model. This work is supported by the National Natural Science Foundation of China (No. 51777126).