引用本文:李瑞,陈来军,梅生伟,薛小代.先进绝热压缩空气储能电站日前电力市场主从博弈竞标策略[J].控制理论与应用,2018,35(5):662~667.[点击复制]
LI Rui,Chen Lai-jun,MEI Sheng-wei,XUE Xiao-dai.Day-ahead strategic bidding for advanced adiabatic compressed air energy storage plant: a Stackelberg game approach[J].Control Theory and Technology,2018,35(5):662~667.[点击复制]
先进绝热压缩空气储能电站日前电力市场主从博弈竞标策略
Day-ahead strategic bidding for advanced adiabatic compressed air energy storage plant: a Stackelberg game approach
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DOI编号  10.7641/CTA.2018.70810
  2018,35(5):662-667
中文关键词  主从博弈  先进绝热压缩空气储能  日前电力市场  策略竞标  混合整数线性规划
英文关键词  Stackelberg game  advanced adiabatic compressed air energy storage  day-ahead electricity market  strategic bidding  mixed-integer linear programming
基金项目  国家自然科学基金创新群体项目(51621065), 青海省基础研究项目(2016-ZJ-742)
作者单位E-mail
李瑞 清华大学 eeairicky@gmail.com 
陈来军 清华大学  
梅生伟* 清华大学 meishengwei@mail.tsinghua.edu.cn 
薛小代 清华大学  
中文摘要
      先进绝热压缩空气储能(advanced adiabatic compressed air energy storage, AA–CAES)是支撑电力系统削峰填 谷、阻塞管理及可再生能源消纳的有效手段之一. 在储能产业商业化初期, 研究面向日前电力市场的竞标策略对实现 AA–CAES电站的经济运行大有裨益. 本文在计及压力动态的AA–CAES运行模型基础上, 采用主从博弈研究了AA– CAES电站竞标策略. 作为主从博弈Leader, AA–CAES电站运营商向日前电力市场上报竞标标的(储能功率、发电功 率、储能电价及发电电价); 作为主从博弈Follower, 市场交易机构以最大化社会福利出清电力市场. 为高效求解主从博 弈竞标模型, 采用Karush-Kuhn-Tucker(KKT)最优性条件及布尔展开法将双层主从博弈竞标模型转化为单层混合整数 线性规划. IEEE–24节点测试系统算例表明, AA–CAES电站可利用低谷电进行充电, 在高峰时刻再以高价售出, 实现套 利运行. 基于主从博弈的日前电力市场竞标策略, 可支撑AA–CAES电站的经济运行.
英文摘要
      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.