4.7 Article

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

Journal

INTERNATIONAL JOURNAL OF ENERGY RESEARCH
Volume 46, Issue 15, Pages 23927-23938

Publisher

WILEY-HINDAWI
DOI: 10.1002/er.8689

Keywords

alternating direction method of multipliers; charging-swapping-storage integrated station; cooperative game; microgrid; Nash bargaining game

Funding

  1. National Natural Science Foundation of China [52107108]
  2. Yichang key experimental research project on intelligent operation and security defense of power system [2020DLXY01]

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This article establishes a cooperative game model based on Nash bargaining between MG and CSSIS, and proposes a distributed computation method based on ADMM to achieve Nash equilibrium. By applying augmented Lagrange function and ADMM, the coupled constrained mathematical problem is divided into two independent subproblems, achieving win-win results.
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.

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