Cooperative operation of multiple low-carbon microgrids: An optimization study addressing gaming fraud and multiple uncertainties.

To achieve efficient utilization of renewable energy and facilitate the development of a more equitable and harmonious power market, an optimization study is conducted focusing on peer-to-peer (P2P) power sharing within multiple low-carbon microgrids (LCMGs). Firstly, the coordinated operation mechanism of a LCMG is proposed involving a step-type carbon trading scheme as well as flexible supply and demand. Then, an optimization model of multi-LCMG cooperative operation is formulated based on the Nash bargaining theory. The original Nash bargaining problem is equivalently transformed into a subproblem of maximizing alliance benefits and a subproblem of maximizing the benefits of power trading. In the first subproblem, a combination of opportunity constraints and robust optimization method is employed to address these multiple uncertainties from renewable generation and electricity prices. The second subproblem addresses the issue of gaming fraud among LCMGs with a third-party intermediary model applied to achieve a fraud equilibrium. Further, to solve these problems efficiently, an improved adaptive parametric alternating direction method of multipliers (AP-ADMM) algorithm is used to protect the privacy of each party. Finally, a case study was conducted to validate the efficacy of the proposed method in enhancing the stability and cost-effectiveness of cooperative optimization within multi-LCMG systems. • Constructing a low-carbon microgrid with a flexible dual response while considering multiple uncertainties. • Developing a cooperative operation model for multiple low-carbon microgrids based on Nash bargaining theory. • Introducing an intermediary transaction model, thereby reducing game-fraudulent negotiations among the participants. • Enhancing the adaptive parameter ADMM algorithm to solve the cooperative game model. [ABSTRACT FROM AUTHOR]