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考虑多重因素的空调虚拟储能响应潜力评估与分层优先排序控制策略OA

Assessment of Virtual Energy Storage Response Potential and Hierarchical Prioritization Control Strategy for Air Conditioners Considering Multiple Factors

中文摘要英文摘要

随着社会发展,空调负荷已成为需求响应中不可或缺的资源,对空调的合理调控可缓解电力资源紧张的局面.为此提出一种考虑多重因素的空调控制策略.首先,基于变频空调的电热参数模型,结合用户满意度、热舒适度和负荷可控度等多个因素,建立空调负荷集群的响应潜力评估模型.其次,引入微元法分解电网调度的需求响应时长,结合虚拟储能的思想提出微元虚拟储能优先排序策略(priority sorting of micro element virtual energy storage,PSME-VESS).最后,构建考虑多重因素的两阶段空调负荷优先排序调控模型.算例仿真结果表明,所提出的控制策略能够切合跟踪电网调度的需求,提高用户意愿度的同时减少用户的受控制频率,在满足电力系统的功率需求下有效提升用户参与需求响应的满意度.

With the development of society,air conditioning load becomes an indispensable resource in demand response,and reason-able regulation and control of air conditioning can alleviate the shortage of power resources.Therefore,an air conditioning control strategy is proposed considering multiple factors.Firstly,based on the electric heating parameter model of inverter air conditioner,combined with multiple factors such as user satisfaction,thermal comfort and load controllability,the response potential evaluation model of air conditioning load cluster is established.Secondly,the micro-element method is introduced to decompose the demand response time of grid dispatching,and the micro-element virtual energy storage prioritization strategy is proposed based on the idea of virtual energy storage.Finally,a two-stage air conditioning load prioritization control model considering multiple factors is constructed.The simulation results show that the control strategy proposed in this paper can meet the needs of tracking power grid dispatching,improve the user's willingness and reduce the user's controlled frequency.In this way,under the condition of meeting the power demand of the power system,the satisfaction of users in participating in demand response can be effectively improved.

黄如玉;程若发;吕翔龙

南昌航空大学信息工程学院,南昌 330000南昌航空大学信息工程学院,南昌 330000南昌航空大学信息工程学院,南昌 330000

信息技术与安全科学

空调负荷需求响应潜力虚拟储能优先排序策略多因素

air conditioning loaddemand response potentialvirtual energy storageprioritization strategymulti-factor

《南方电网技术》 2026 (7)

80-89,10

国家自然科学基金资助项目(52367011)江西省自然科学基金资助项目(20232ACB204023). Supported by the National Natural Science Foundation of China(52367011)the Natural Science Foundation of Jiangxi Province(20232ACB204023).

10.13648/j.cnki.issn1674-0629.2026.07.008

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