To promote the active participation of data centers (DCs) in electricity–carbon coupling (ECC) trading and to achieve coordinated multi-entity emission reduction and cost optimization, this study proposes a cooperative game (CG)-based optimal scheduling method for multiple DCs under an ECC trading framework. First, a comprehensive trading framework is developed, in which DCs participate simultaneously in electricity and carbon markets, capturing the coupling relationship between energy prices and carbon quotas while establishing a low-carbon operational model for each DC. Second, based on CG theory, a multi-DC alliance optimization model is formulated, enabling coordinated management of multiple resources and fair benefit sharing through workload migration, energy storage and gas turbine management, and carbon allowance trading. Finally, leveraging Nash bargaining theory, the CG model is decomposed into a cost minimization problem and a benefit allocation problem, which are solved using an alternating direction method of multipliers algorithm, thereby preserving the privacy of each DC. Simulation results demonstrate that the proposed approach effectively reduces both operational costs and carbon emissions, providing theoretical and technical support for low-carbon and economically efficient operation of multi-DC systems.
Ma et al. (Thu,) studied this question.