Bidding Decision and Clearing Optimization for Pumped-Storage Clusters Under Multi-Coupled Market Conditions

Under the background of China’s unified national power market, pumped-storage power stations are transforming from the traditional passive scheduling mode to the role of market entities and are showing a clustered development trend. However, at present, the clustered operation of pumped-storage power stations lacks a systematic decision-making method under the condition of multiple coupled markets. Therefore, this paper proposes an optimization method for the joint participation of pumped-storage clusters in inter-provincial and intra-provincial multi-coupled market transactions. Firstly, with the goal of maximizing the total revenue of the pumped-storage cluster in multiple markets across the province and within the province, combined with the quantity-reporting and price-offering constraints of the pumped-storage cluster and the operation constraints of each pumped-storage station, an upper-level pumped-storage cluster bidding decision-making model is constructed. Secondly, with the goal of maximizing the social welfare in inter-provincial and provincial intra-provincial markets, a lower-level joint clearing model for inter-provincial electricity energy–peak-shaving auxiliary service markets and provincial intra-provincial electricity energy–peak-shaving auxiliary service markets is established. Finally, the Karush–Kuhn–Tucker (KKT) theorem and McCormick envelope method are adopted to solve the model. Simulation case analysis reveals that the revenue of the pumped-storage cluster from the peak-regulation ancillary service market accounts for 57.98% of its total revenue, while the revenue generated in the inter-provincial market accounts for 66.54% of the total revenue. Compared with the traditional independent operation mode of single pumped-storage power stations, the clustered operation mode can increase the total revenue of all pumped-storage power stations in the region by 25.37% and raise the revenue of each individual pumped-storage plant within the cluster. The above results verify the feasibility and superiority of the proposed strategy and model.