Day-ahead strategic bidding for advanced adiabatic compressed air energy storage plant: a Stackelberg game approach

被引：0
|
作者：
Li R. [1 ,2 ]
Chen L.-J. [1 ,2 ,3 ]
Mei S.-W. [1 ,2 ,3 ]
Xue X.-D. [1 ,2 ,3 ]
机构：
[1] Department of Electrical Engineering, Tsinghua University, Beijing
[2] State Key Lab of Control and Simulation of Power Systems and Generation Equipments, Beijing
[3] School of QiDi(TUS)Renewable Energy, Qinghai University, Xining, 810016, Qinghai
来源：
Mei, Sheng-Wei (meishengwei@mail.tsinghua.edu.cn) | 2018年 / South China University of Technology卷 / 35期
基金：
中国国家自然科学基金;
关键词：
Advanced adiabatic compressed air energy storage; Day-ahead electricity market; Mixed-integer linear programming; Stackelberg game; Strategic bidding;
D O I：
10.7641/CTA.2018.70810
中图分类号：
学科分类号：
摘要：
Advanced adiabatic compressed air energy storage(AA-CAES)can support the peak-shaving and the renewable integration of power systems. At the early commercialization of energy storage facilities, the bidding strategy in the day-ahead electricity market is crucial for the economic operation of AA-CAES plants. We investigated the day-ahead bidding and offering strategies of the AA-CAES plant with a Stackelberg game theoretic approach based on an AA-CAES operation model considering the pressure dynamic. As the leader of the game, the AA-CAES owner submits electricity offers and bids regarding quantity and price, to the independent system operator, who acts as the follower and clears the electricity market to maximize social welfare. To solve the bi-level leader-follower bidding model efficiently, we leverage the KKT optimality condition, and the binary expansion method to approximate and transform it as mixed-integer linear programming. The experiments on a modified IEEE-24 bus system demonstrated the energy arbitrage behavior of AA-CAES by purchasing the off-peak low-price electricity and selling to balance the peak-load with a higher price. The leader-follower game based bidding and offering strategies in the day-ahead electricity market can benefit the economic operation of the AA-CAES plant. © 2018, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
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收藏
页码：662 / 667
页数：5
相关论文
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