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

• Published in: International journal of energy research Vol. 46; no. 15; pp. 23927 - 23938
• Main Authors: Cheng, Shan, Zuo, Xianwang, Wei, Zhaobin, Ni, Kaixuan, Wang, Can
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Inc 01-12-2022; Hindawi Limited
• Subjects: alternating direction method of multipliers; Bargaining; Charging; charging‐swapping‐storage integrated station; Computation; cooperative game; Distributed generation; Economics; Equilibrium; Game theory; Iterative methods; Mathematical models; Mathematical problems; Maximization; microgrid; Nash bargaining game; Optimization; Profit; Scheduling; Storage; Theoretical analysis
• ISSN: 0363-907X; 1099-114X
• DOI: 10.1002/er.8689

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.
Procedure overview.