Nash bargaining‐based cooperative game for distributed economic scheduling of microgrid with charging‐swapping‐storage integrated station

Abstract

Summary To stimulate cooperative transaction between different stakeholders and optimize the economic profits of each entity in the microgrid (MG) with charging‐swapping‐storage integrated station (CSSIS), this article establishes a Nash bargaining‐based cooperative game model between MG and CSSIS, and proposes an alternating direction method of multipliers (ADMM) based distributed computation to reach Nash equilibrium. At first, MG and CSSIS are regarded as two different stakeholders, and their transactions are captured by the Nash bargaining framework, which takes the Stackelberg equilibrium solution as the initial bifurcation point of Nash negotiation, and constructs a bi‐level Nash bargaining game model for the microgrid and CSSIS. Then, theoretical analysis of the existence and uniqueness of Nash equilibrium is developed based on the proposed game property. Following that, with application of augmented Lagrange function and ADMM, the constraints coupled Nash bargaining mathematical problem is divided into two independent subproblems, namely, the economic profit maximization of MG and the economic operation maximization of CSSIS, whose solutions can be determined in a distributed iteration. Numerical simulation results indicate that, compared with Stackelberg equilibrium solution identified by the noncooperative game model, the model can further improve the benefits of both game participants and achieve win‐win results. At the same time, it can more reasonably schedule resources in the system to maximize the economic profit of the overall system.

Distributed Optimization of Multi-Microgrid Integrated Energy System with Coordinated Control of Energy Storage and Carbon Emissions

“…Compared with other methods, ADMM can deal with complex models effectively, and its convergence and convergence speed have been proven, providing the basic framework for MMIESs. In the basic ADMM scheduling framework, Mohiti M et al [17] took economic cost as the scheduling objective function, Chen L et al [18] established an optimal two-layer multi-timescale scheduling model based on short-term forecast data, and Cheng S et al [19] put more emphasis on price policy, establishing a Nash bargaining cooperative game model to minimize the operating cost of each microgrid.…”

Peer-to-Peer Energy Trading among Prosumers with Voltage Regulation Services Provision

“…The Shapley value method is not applicable for non-convex game models, and the complexity of the nucleolus-based solution increases exponentially with increasing numbers of prosumers. In [37,38], the general Nash bargaining model is utilized to settle the P2P transactions, and the settlement solution is formulated as a centralized optimization problem. This paper applies ADMM to solve the settlement model based on the asymmetric Nash bargaining model in a distributed manner.…”