面向需求响应应用的空调负荷建模及控制

SONG Meng

您当前的位置：

首页 >

文章列表页 >

面向需求响应应用的空调负荷建模及控制

更新时间：2025-08-13

- 面向需求响应应用的空调负荷建模及控制
- Automation of Electric Power Systems Vol. 40, Issue 14, Pages: 158-167(2016)
- 作者机构：
  
  江苏省智能电网技术与装备重点实验室(东南大学),江苏省,南京市,210096
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016
- 稿件说明：
移动端阅览
SONG Meng. [J]. Automation of electric power systems, 2016, 40(14): 158-167.
DOI：

SONG Meng. [J]. Automation of electric power systems, 2016, 40(14): 158-167. DOI：

摘要

空调负荷是一种优良的需求响应资源

对空调的合理调控能够有效缓解供需不平衡

提高电力系统综合运营效率

实现资源优化配置

但这需要建立在对空调负荷运行特性基础理论的深刻理解基础上。文中从空调系统热力学建模、聚合模型、控制模式、调控策略四个角度

讨论了空调负荷在需求响应中的研究现状

并针对目前国内外空调负荷研究的实际情况

对空调负荷进一步的研究方向进行了展望。

Abstract

As a good demand response resource

air-conditioning load can alleviate the power supply shortage

improve the whole power system operation efficiency and realize the resource optimal configuration

which depends on in-depth research of the basic theory of air-conditioning operating characteristics. Air-conditioning load application on demand response is reviewed in this paper including the air-conditioning system thermodynamic modeling

aggregation models

control pattern and control strategy in running of power systems. According to the actual situation of current domestic and foreign research on air-conditioning load

further research directions of air-conditioning load are discussed. This work is supported by National High Technology Research and Development Program of China(863 Program)(No. 2015AA050401)

National Natural Science Foundation of China(No. 51577029)and State Grid Corporation of China.

关键词

Keywords

references

Views

4022

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

基于负荷聚合商业务的空调服务运作模式及控制策略

考虑状态差异性聚类的空调负荷直接负荷控制动态优化方法

Trading Mechanism for Participation of Small- and Medium-sized Customers in Directrix Demand Response Considering Differentiated Incentives

Joint Bidding and Pricing Optimization Method for Aggregator Demand Response Considering Differences of User Response

Related Author

CHENG Lin

XU Qingshan

ZHENG Ran

LIU Baozhu

HU Junjie

XIE Dongliang

WANG Lei

PAN Tianyu

Related Institution

State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments, Tsinghua University

School of Electrical Engineering, Southeast University

State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University)

State Grid Electric Power Research Institute (NARI Group Corporation)

Anhui Provincial Key Laboratory of Renewable Energy Utilization and Energy Saving (Hefei University of Technology)

⁰