综合智慧能源 ›› 2023, Vol. 45 ›› Issue (11): 1-9.doi: 10.3969/j.issn.2097-0706.2023.11.001

• 规划与调度决策 •    下一篇

基于主从博弈的储能电站协同源荷消纳新能源调控策略

杜预则(), 董海鹰()   

  1. 兰州交通大学 新能源与动力工程学院 兰州 730070
  • 收稿日期:2023-04-05 修回日期:2023-04-14 出版日期:2023-11-25
  • 作者简介:杜预则(1997),男,在读硕士研究生,从事新能源电力系统优化调度研究,duyuzelanzhou@163.com
    董海鹰(1966),男,教授,博士生导师,博士,从事电力系统优化调度、新能源发电等方面的研究,hydong@mail.lzjtu.cn
  • 基金资助:
    甘肃省科技重大专项计划项目(23ZDGA005);国网甘肃省电力公司临夏供电公司科技项目(W22KJ2714016)

Research on the source-load-storage collaborative scheduling strategy for new energy accommodation based on Stackelberg game

DU Yuze(), DONG Haiying()   

  1. School of New Energy and Power Engineering, Lanzhou Jiaotong University,Lanzhou 730070,China
  • Received:2023-04-05 Revised:2023-04-14 Published:2023-11-25
  • Supported by:
    Gansu Provincial Science and Technology Major Project(23ZDGA005);Science and Technology Project of Linxia Power Supply Company,State Grid Gansu Electric Power Company(W22KJ2714016)

摘要:

随着我国“双碳”目标的提出,新能源发电量大幅提升,为提高风光消纳率,引入虚拟电厂(VPP)运营商、负荷聚合商(LA)和储能电站(ESS),提出了一种基于主从博弈的储能电站协同源荷消纳新能源调控策略。将独立运行的VPP运营商作为上层领导者,具备需求响应能力的双向产消LA作为下层跟随者,通过上下层间价格和用能策略的博弈,实现新能源消纳和源荷储收益共赢。算例分析表明:源荷储三方在实时电、热价博弈机制下能够实现共赢并有效提高新能源消纳水平;引入ESS平抑了负荷和新能源出力波动,既提高了源侧VPP供能收益,又在保证荷侧用能满意度的前提下降低了LA的用电成本,提高了用户的需求响应能力和系统的风光上网空间。模型采用分布式遗传联合二次规划(GA-QP)算法进行求解,具有良好的收敛速度和效果,同时能够保护博弈各方的数据隐私。

关键词: “双碳”目标, 新能源, 风光消纳, 主从博弈, 储能电站, 虚拟电厂, 优化调度, 分布式遗传联合二次规划算法

Abstract:

China's dual carbon target requires an increasing share of new energy in the power grid. To enhance the new energy consumption rate, a source-load-storage collaborative scheduling strategy based on Stackelberg game is proposed for the power system consisting of virtual power plants (VPPs), load aggregators (LAs), and energy storage systems (ESSs). The autonomous VPP serves as a leader at the upper level, while the LA with demand response capability, both a power purchaser and a consumer, acts as the follower at the lower level. A win-win situation can be achieved by new energy consumers and the source-load-storage system through a game of pricing and energy usage strategies between the upper and lower levels. The results of the case study on the proposed strategy show that it is possible to create the win-win situation between source, load and storage by taking time-of-use pricing and game theory, and to increase the new energy accommodation capacity. And ESSs can alleviate fluctuations of loads and new energy outputs, rise the return of VPPs at source end, lower the electricity costs of LAs with the premise of ensuring energy uses' satisfaction, ensure energy consumption at the load end, enhance the demand responsiveness of customers, and expand the room for new energy's grid connection. Taking distributed Genetic Algorithm and Quadratic Programming (GA-QP) in solving process is of good convergence speed and effectiveness,and able to protect the privacy of all parties in the game.

Key words: "dual carbon" target, new energy, new energy consumption, Stackelberg game, energy storage station, virtual power plant, optimal scheduling, GA-QP

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