Jiao Wang ^1* Jinyan Hu ^1* Zhichao Bai ^1* Hao He ² Mingxin Tang ^2*

• ¹ State Grid Inner Mongolia East Electric Power Company Economic and Technological Research Institute, Hohhot, China
• ² School of Economics and Management, North China Electric Power University, Beijing, China

Large-scale new energy grid connection poses a challenge to the peak regulation of the power grid. User-side distributed energy storage and other resources help the efficient use of new energy.Compared to traditional resources, user-side resources are of various types and have more significant uncertainty about their regulatory capacity, leading to difficulties in coordinating decisions about their simultaneous participation in the electric energy and peaking ancillary services markets. This paper proposes a joint bidding decision-making method for the day-ahead electricity energy and peak shaving auxiliary service market based on distributed robust opportunity constraints, which addresses the problem of difficulty in using an accurate probability density distribution to represent the uncertainty process of user-side resources. Initially, this paper delves into a data-driven approach to characterizing the uncertainty inherent in load regulation capacity, constructing fuzzy sets without presupposing specific probability distributions for random variables. Subsequently, a bidding strategy that accounts for this uncertainty is proposed, with the aim of minimizing the expected risk of the joint bidding cost on the customer side. Finally, an illustrative simulation is conducted to validate the rationality and efficacy of the proposed joint bidding method. The outcomes demonstrate that the model developed here surpasses the robust model's issue of excessive conservatism and exhibits superior computational adaptability compared to the stochastic model, striking a more favorable balance between robustness and economic efficiency.