Low-carbon optimal scheduling of park-integrated energy system based on bidirectional Stackelberg-Nash game theory

被引:6
作者
Wang, Yi [1 ]
Jin, Zikang [1 ]
Liang, Jing [1 ]
Li, Zhongwen [1 ]
Dinavahi, Venkata [2 ]
Liang, Jun [3 ]
机构
[1] Zhengzhou Univ, Sch Elect & Informat Engn, Zhengzhou 450001, Peoples R China
[2] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2V4, Canada
[3] Cardiff Univ, Sch Engn, Cardiff CF24 3AA, Wales
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Tri-level model; Bidirectional Stackelberg-Nash game; P2P energy trading; Asymmetric Nash bargaining distributed; algorithm;
D O I
10.1016/j.energy.2024.132342
中图分类号
O414.1 [热力学];
学科分类号
摘要
Multi-stakeholder participation is crucial in facilitating the development of park-integrated energy systems (PIES). Balancing the diverse interests of various stakeholders, each with its distinct requirements presents a notable challenge. Concurrently, the model's complexity increases due to the engagement of various stakeholders, posing challenges to its resolution through traditional methods. In this context, this paper aims to investigate an optimal scheduling model that incorporates shared energy storage (SES) system, microgrids operator (MGO), electric vehicles station (EVS), and user aggregator (UA) with multiple prosumers. To comprehensively address the interests of all stakeholders, this study introduces a tri-level optimization model. The proposed model integrates a bidirectional Stackelberg-Nash game framework, in which the SES acts as the leader, the MGO acts as the secondary leader, and the UA-EVS acts as the followers while allocating benefits based on the asymmetric Nash bargaining theory. The Stackelberg game model between MGO and UA-EVS is analyzed using the Karush-Kuhn-Tucker (KKT) condition, while the Stackelberg game model between SES and MGO is resolved using the bisection method. Meanwhile, the Nash bargaining method among users is solved using the alternating direction method of multipliers (ADMM) technique. The analysis indicates that the proposed strategy can reduce PIES's costs and carbon emissions, yielding a win-win situation for all stakeholders.
引用
收藏
页数:21
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