Day-ahead Robust Bidding Strategy for Prosumer Considering Virtual Energy Storage of Air-conditioning Load

Shuangrui YIN; Qian AI; Dapeng WANG; Yongqing DING; Junhong WU; Yinzhe XIE

doi:10.7500/AEPS20190115002

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Day-ahead Robust Bidding Strategy for Prosumer Considering Virtual Energy Storage of Air-conditioning Load

Basic Research | 更新时间：2025-06-16

- Day-ahead Robust Bidding Strategy for Prosumer Considering Virtual Energy Storage of Air-conditioning Load
- Automation of Electric Power Systems Vol. 44, Issue 4, Pages: 24-34(2020)
- 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：
- 基金信息：
  
  National Natural Science Foundation of China
- DOI：10.7500/AEPS20190115002
  CLC：
- Received：15 January 2019，
  
  Revised：2019-06-06，
  
  Published Online：15 October 2019，
  
  Published：25 February 2020
- 稿件说明：
移动端阅览
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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