考虑空调负荷虚拟储能的产消者鲁棒日前申报策略

殷爽睿; 艾芊; 王大鹏; 丁永清; 吴俊宏; 谢胤喆

doi:10.7500/AEPS20190115002

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考虑空调负荷虚拟储能的产消者鲁棒日前申报策略

学术研究 | 更新时间：2025-06-16

- 考虑空调负荷虚拟储能的产消者鲁棒日前申报策略
- Day-ahead Robust Bidding Strategy for Prosumer Considering Virtual Energy Storage of Air-conditioning Load
- 电力系统自动化-方正平台 2020年44卷第4期页码：24-34
- 作者机构：
  
  1. 电力传输与功率变换控制教育部重点实验室(上海交通大学),上海市 200240
  2. 国网安徽省电力有限公司池州供电公司,安徽省池州市 247000
  3. 华东电力设计院有限公司,上海市 200001
- 作者简介：
  
  殷爽睿(1995—),女,博士研究生,主要研究方向:虚拟电厂优化运行。E-mail:yinsr28@sjtu.edu.cn
  艾芊(1969—),男,通信作者,教授,博士生导师,主要研究方向:分布式发电、微电网、人工智能及其在电力系统中的应用。E-mail:aiqian@sjtu.edu.cn
  王大鹏(1969—),男,副教授级高级工程师,主要研究方向:电网规划。E-mail:33706559@qq.com
- 基金信息：
  
  国家自然科学基金资助项目(U1866206)
- DOI：10.7500/AEPS20190115002
  中图分类号：
- 收稿日期：2019-01-15，
  
  修回日期：2019-06-06，
  
  网络出版日期：2019-10-15，
  
  纸质出版日期：2020-02-25
- 稿件说明：
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殷爽睿,艾芊,王大鹏等.考虑空调负荷虚拟储能的产消者鲁棒日前申报策略[J].电力系统自动化,2020,44(04):24-34.

YIN Shuangrui,AI Qian,WANG Dapeng,et al.Day-ahead Robust Bidding Strategy for Prosumer Considering Virtual Energy Storage of Air-conditioning Load[J].Automation of Electric Power Systems,2020,44(04):24-34.
殷爽睿,艾芊,王大鹏等.考虑空调负荷虚拟储能的产消者鲁棒日前申报策略[J].电力系统自动化,2020,44(04):24-34. DOI： 10.7500/AEPS20190115002.

YIN Shuangrui,AI Qian,WANG Dapeng,et al.Day-ahead Robust Bidding Strategy for Prosumer Considering Virtual Energy Storage of Air-conditioning Load[J].Automation of Electric Power Systems,2020,44(04):24-34. DOI： 10.7500/AEPS20190115002.

摘要

在分布式可再生能源大力发展的背景下

产消者将成为新的重要利益主体参与电网运行。考虑到产消者中空调负荷具有良好的调控潜力

文中首先建立了空调负荷的虚拟储能模型

并在此基础上分析了虚拟储能与常规储能的不同之处。针对虚拟储能可参与日内调控的特点

考虑可再生能源出力不确定性

提出了产消者鲁棒日前申报策略

并进一步提出了将虚拟储能日前决策与实时调整相结合的产消者最优申报及调度策略

运用改进的列约束生成算法进行求解。最后对具体算例进行比较

证明了最优策略在产消者运行灵活性与经济性方面的优势

并分析了可再生能源出力不确定性、惩罚价格选取及室外温度对实际结果的影响。

Abstract

With the rapid development of distributed renewable energy

the prosumers will become new important stakeholders participating in the grid operation. Considering that the air-conditioning load of the prosumers has good regulation potential

the virtual energy storage (VES) model of air-conditioning load is first established

and the difference between VES and conventional energy storage is analyzed. Considering the characteristics of VES that can participate in intraday regulation and the uncertainty of renewable energy output

a day-ahead robust bidding strategy for prosumers is proposed. Furthermore

an optimal bidding and scheduling strategy combining day-ahead decision-making with real-time adjustment of VES is proposed. The improved column-and-constraint generation (C&CG) algorithm is used to solve the problem. Finally

the specific examples are compared and the results prove the advantages of optimal strategy in the flexible and economic operation of the prosumer. The impact of the uncertainty of renewable energy output

penalty price selection and outdoor temperature on actual results is further analyzed.

关键词

Keywords

references

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