Low-carbon operation pricing model of shared energy storage station-multiple integrated energy systems considering multiple uncertainties

With the proposal of ‘Dual Carbon Goals’, shared energy storage stations (SESS) are emerging as critical infrastructure for enhancing renewable energy integration capacity and grid flexibility, gradually integrating into regional multiple integrated energy systems (MIES). However, the interactive pricing mechanisms between SESS and MIES face multiple challenges: the intermittency of wind turbine (WT) and photovoltaic (PV) output combined with spot market price volatility complicates the dynamic alignment of transactive prices with real-time supply-demand balance; the coupling of electricity and carbon markets requires electricity pricing designs to balance economic efficiency and low-carbon sustainability; and conflicts in interest distribution weaken transaction incentives. To address these issues, this study proposes a two-layer Wasserstein distributionally robust-Nash bargaining game pricing model incorporating carbon quotas and carbon trading mechanisms. First, three differentiated integrated energy system (IES) models were established based on regional resource endowments; second, a Nash bargaining framework was used to construct a transaction pricing model between shared energy storage and multi-integrated energy systems; Third, the Wasserstein distributionally robust method was employed to quantify the uncertainty of renewable energy output and electricity price fluctuations, and the model was linearized using the duality theory for solution; finally, the adaptive dynamic step-size Alternating Direction Method of Multipliers (ADMM) algorithm was used to accelerate convergence. The results indicate that the model achieves reasonable differentiated pricing and revenue distribution for SESS and MIES under uncertainty, with a total benefit increase of 13.74% (4789.32 yuan). Additionally, through Carbon Capture and Storage (CCS), power to gas (P2G) equipment and the energy-sharing method, carbon emissions were reduced by 18.54% (5823.75 kg) and 10.57% (3379.53 kg), respectively. This pricing model effectively promotes carbon reduction and efficiency improvements, providing important support for achieving the ‘Dual Carbon Goals’.