基于温度密度聚类的热泵负荷集群控制策略

孙毅; 陈一童; 李彬; 谢祥颖; 卢毓东

doi:10.7500/AEPS20190708002

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基于温度密度聚类的热泵负荷集群控制策略

学术研究 | 更新时间：2025-06-16

- 基于温度密度聚类的热泵负荷集群控制策略
- Control Strategy of Heat Pump Load Cluster Based on Temperature Density Clustering
- 电力系统自动化-方正平台 2020年44卷第7期页码：46-52
- 作者机构：
  
  1. 华北电力大学电气电子工程学院,北京市 102206
  2. 国网电子商务有限公司,北京市 100053
  3. 国网浙江省电力有限公司电力科学研究院，浙江省杭州市 310014
- 作者简介：
  
  孙毅(1972—)，男,博士，教授，博士生导师，主要研究方向：电力系统通信与信息处理、智能用电与需求响应等。
  陈一童(1995—)，男，通信作者，硕士研究生，主要研究方向：电力系统信息通信技术等。E-mail：18811315822@163.com
  李彬(1983—)，男，博士，副教授，主要研究方向：电气信息技术以及自动需求响应。
- 基金信息：
  
  国家自然科学基金资助项目(5177068);国家电网公司总部科技部项目(52110418001C)
- DOI：10.7500/AEPS20190708002
  中图分类号：
- 收稿日期：2019-07-08，
  
  修回日期：2019-10-08，
  
  网络出版日期：2020-02-28，
  
  纸质出版日期：2020-04-10
- 稿件说明：
移动端阅览
孙毅,陈一童,李彬等.基于温度密度聚类的热泵负荷集群控制策略[J].电力系统自动化,2020,44(7):46-52.

SUN Yi,CHEN Yitong,LI Bin,et al.Control Strategy of Heat Pump Load Cluster Based on Temperature Density Clustering[J].Automation of Electric Power Systems,2020,44(7):46-52.
孙毅,陈一童,李彬等.基于温度密度聚类的热泵负荷集群控制策略[J].电力系统自动化,2020,44(7):46-52. DOI： 10.7500/AEPS20190708002.

SUN Yi,CHEN Yitong,LI Bin,et al.Control Strategy of Heat Pump Load Cluster Based on Temperature Density Clustering[J].Automation of Electric Power Systems,2020,44(7):46-52. DOI： 10.7500/AEPS20190708002.

摘要

首先描述了典型温控负荷的热力学模型，并在此基础上讨论了常用温度设定控制策略下负荷温度分布变化及负荷开关状态变化。随后以温度队列为基础，提出了一种基于负荷温度的密度聚类集群控制策略。该策略考虑负荷在温度区间内的分布情况，通过密度聚类算法对负荷群进行聚类分析并确定密集区域与非密集区域；随后计算温度节点和补偿节点并确定设备响应群体和温度设定值；最后以温度设定值为响应信号对负荷群进行控制。以常用温控负荷电热泵为控制对象进行仿真分析，与常用温度设定控制下负荷群开关变化次数进行了对比。结果显示，负荷在控制中开关状态变化次数明显降低，负荷群中发生开关状态变化的负荷数目明显减少。

Abstract

Firstly

the thermodynamic model of typical temperature-controlled load is described. Based on this

the variation of load temperature distribution and the change of load switch states with the control strategy of common temperature setting are discussed. Then

based on the temperature queue

a cluster control strategy of density clustering based on load temperature (DCBLT) is proposed. This strategy considers the distribution of the loads in the temperature interval

clustering analysis of load cluster is made by DCBLT method and the dense region and non-dense region are determined. Temperature nodes and compensation nodes are calculated

and device response group and temperature setting value are determined. Finally

the load group is controlled by taking the set temperature as a response signal. The electric heat pump of common temperature-controlled load is used as the control object to make the simulation analysis. Compared with the switch changing times of the load group with the common temperature setting control

the results show that the changing times of switching states is obviously reduced during the control and the number of loads in which the switch state changes is significantly reduced.

关键词

Keywords

references

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