Virtual cloud energy storage optimization operation method considering thermal inertia of building air conditioning system

王 宝; 张伟时; 何 川; 林哲敏; 江海龙; 杨 娜; 丁启耀; 周佳妮

doi:10.3969/j.issn.1009-1831.2025.03.008

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Virtual cloud energy storage optimization operation method considering thermal inertia of building air conditioning system

更新时间：2026-03-05

- Virtual cloud energy storage optimization operation method considering thermal inertia of building air conditioning system
- Vol. 27, Issue 3, (2025)
- 作者机构：
  
  1. 国网安徽省电力有限公司经济技术研究院,合肥,230022
  2. 安徽电力交易中心有限公司,合肥,230022
  3. 东南大学电气工程学院,南京,210096
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2025.03.008
  CLC：
- Published：2025
- 稿件说明：
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王宝, 张伟时, 何川, et al. Virtual cloud energy storage optimization operation method considering thermal inertia of building air conditioning system[J]. 2025, 27(3).
DOI：

王宝, 张伟时, 何川, et al. Virtual cloud energy storage optimization operation method considering thermal inertia of building air conditioning system[J]. 2025, 27(3). DOI： 10.3969/j.issn.1009-1831.2025.03.008.

摘要

为弥补实体储能前期投资高、利用率低等缺陷，云储能作为一种新型的储能投资运营模式受到了广泛关注。考虑到空调负荷在国民用电负荷中的高占比，充分挖掘定频空调的虚拟储能潜力，建立可供租赁的空调虚拟储能聚合模型；基于此，在考虑风光荷不确定性的情况下，以提升联盟总体经济性为目标对云储能优化运营方法展开研究，并对比分析固定定价与动态定价场景下各用户的经济收益情况。算例结果表明，基于建筑空调系统热惯性的虚拟云储能优化运营方法能够有效提升运营商与用户的总体收益，减少用户用电支出，并在一定程度上促进用户侧可再生能源的消纳。

Abstract

Faced with high upfront investment and low utilization rate of physical energy storage

cloud energy storage has received wide attention as a new type of energy storage investment and operation mode. Considering the high proportion of air-conditioning load in national electricity consumption

the virtual energy storage potential of fixed-frequency air-conditioners is fully exploited to establish an aggregated air- conditioner virtual energy storage model

which can be leased. Based on this

considering wind

photovoltaic and load uncertainty

cloud energy storage operators and users are taken as an alliance

and the research on the optimized operation method of cloud energy storage is carried out with the goal of improving the overall economic model of the alliance. The economic benefits of each user under the fixed pricing and dynamic pricing scenarios are compared and analyzed. Case study shows that the cloud energy storage optimization scheduling method based on the thermal inertia of scaled air conditioners can effectively improve the overall revenue of the operator and users

reduce the expenditure of users’electricity consumption

and promote the consumption of renewable energy on the users’side.

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