中国电力 ›› 2022, Vol. 55 ›› Issue (10): 14-22.DOI: 10.11930/j.issn.1004-9649.202203042

• 多元负荷用能感知及友好互动 • 上一篇    下一篇

电力市场环境下虚拟电厂两阶段能量经济优化调度

赵力航1,2,3, 常伟光3, 杨敏1,2, 杨强3, 秦刚华1,2   

  1. 1. 浙江省太阳能利用及节能技术重点实验室,浙江 杭州 311121;
    2. 浙江浙能技术研究院有限公司,浙江 杭州 311121;
    3. 浙江大学 电气工程学院,浙江 杭州 310027
  • 收稿日期:2022-03-16 修回日期:2022-07-05 出版日期:2022-10-28 发布日期:2022-10-20
  • 作者简介:赵力航(1990—),男,博士,高级工程师,从事分布式微电网、虚拟电厂调控技术研究,E-mail:ethange_sp1@163.com;常伟光(1999—),男,博士研究生,从事虚拟电厂能量优化控制研究,E-mail:1791750041@qq.com;杨强(1979—),男,博士,教授,从事智慧能源系统、大型复杂网络建模、控制与优化研究,E-mail:qyang@zju.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(城市建筑群多能流端-边-云协同增效调控方法研究与应用,52177119);浙能集团科技项目(基于数据驱动的虚拟电厂-储能系统协同增效调控关键技术研究,ZERD-KJ- 2020-002)。

Two-Stage Energy Economic Optimal Dispatch of Virtual Power Plant in Deregulated Electricity Market

ZHAO Lihang1,2,3, CHANG Weiguang3, YANG Min1,2, YANG Qiang3, QIN Ganghua1,2   

  1. 1. Key Laboratory of Solar Energy Utilization & Energy Saving Technology of Zhejiang Province, Hangzhou 311121, China;
    2. Zhejiang Energy Research Institute Co., Ltd., Hangzhou 311121, China;
    3. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
  • Received:2022-03-16 Revised:2022-07-05 Online:2022-10-28 Published:2022-10-20
  • Supported by:
    This work is supported by National Natural Science Foundation of China (Research and Application of Multi-energy Flow-End-Edge-Cloud Synergistic Control Method for Urban Buildings, No.52177119) and Science & Technology Project of Zhejiang Energy Group Ltd. (Research on Key Technologies of Data-driven Virtual Power Plant-Energy Storage System Synergistic Efficiency Regulation, No.ZERD-KJ-2020-002).

摘要: 随着分布式可再生能源在电网中的渗透率不断增加,虚拟电厂作为一种高效管理分布式可再生能源的技术已经引起国内外学者的广泛关注。提出一种非管制电力市场环境下的虚拟电厂两阶段能量经济优化调度方法,该方法将虚拟电厂的调度分为日前和日内2个阶段。在日前阶段,基于预测信息制定次日的最优调度计划并与日前电力市场签订协议;在日内阶段,以日前计划为参考,采用模型预测控制策略调整日内的运行计划,以消除由于预测误差导致的净负荷波动,同时尽可能减少来自日内平衡市场的罚款,降低总体运行成本。所提出的模型均使用商业求解器Gurobi进行求解。仿真数值结果表明:所提出的算法通过日前计划和日内调控的手段提高了可再生能源设备的利用率,具备一定的经济性和实用性,为虚拟电厂的经济调度提供了新的思路和途径。

关键词: 虚拟电厂, 非管制电力市场, 日前计划, 日内调控, 模型预测控制

Abstract: With the increasing penetration of renewable distributed energy resources (DER) in power grids, virtual power plant (VPP) as an effective management technology of DERs has attracted widespread attentions. In this paper, a two-stage energy economic optimal scheduling method is proposed for VPP in a deregulated electricity market, which consists of day-ahead stage and intra-day stage. In the day-ahead stage, the optimal scheduling plan for the next day is formulated based on the forecasting information, and an agreement is signed with the day-ahead electricity market organizer. In the intra-day stage, on the basis of the day-ahead scheduling plan, the model predictive control (MPC) strategy is used to adjust the intra-day operation plan so as to eliminate net load variation caused by forecasting errors as well as to minimize penalties from the intra-day balancing market, thus reducing the overall operation costs. The proposed models are solved by the commercial solver Gurobi 9.1. Numerical simulation results show that the proposed method improves the utilization rate of DER and equipment inside VPP by means of day-ahead scheduling and intra-day redispatching, which is economical and practical, and provides a new approach for the economic dispatch of VPP.

Key words: virtual power plant (VPP), deregulated electricity market, day-ahead scheduling, intra-day dispatch, model predictive control (MPC)