电力需求侧管理2025，Vol.27Issue(3)：82-86,5.DOI:10.3969/j.issn.1009-1831.2025.03.013
基于数据驱动的中央空调系统多状态互动能力研究
Research on multi state interaction capability of central air conditioning system based on data driven approach
摘要
Abstract
Air conditioning load is a kind of flexible resources with fast response speed and large adjustable capacity.Through the analysis and modeling of the interaction potential of air conditioning load under multiple demand response time states,it can quickly respond to the grid side dispatch with little impact on user comfort,reduce the power demand in peak hours,and alleviate the contradiction between pow-er supply and demand.In order to better reveal the various factors that affect air-conditioning participation in demand response,firstly,based on the thermodynamic model of air-conditioning,air-conditioning load is decomposed into static load and dynamic load.The concept of data-driven is different from the classical model-driven,which uses massive data acquired by collection or simulation.The deep feature relationships are mined and explored,and the problem architecture and solution ideas under the data-driven algorithm are established.Then,the constrained regression method and the data-driven temporal convolutional network-bidirectional gated recurrent unit-attention(TCN-BiGRU-Attention)neural network are used to estimate the adjustable interaction ability under different time states when the air conditioner participates in the demand response.The simulation results show that there is a significant correlation between the setting tem-perature and other factors and the static load of air conditioning,and there is a huge difference in the interaction ability between air condi-tioning load and the grid side under different demand response time scales.This method can effectively reduce the total cost of system calls and greatly improve the efficiency of air conditioning load participating in peak load shaving.The validity and accuracy of the method are verified based on the data of real users.关键词
数据驱动/需求响应/BiGRU神经网络/热力学模型/互动能力Key words
data-driven/demand response/BiGRU neural network/thermodynamic model/ability to interact分类
动力与电气工程引用本文复制引用
石坤,罗鑫宇,李彬,陈宋宋,樊其锋,焦利敏,刘颖..基于数据驱动的中央空调系统多状态互动能力研究[J].电力需求侧管理,2025,27(3):82-86,5.基金项目
国家电网有限公司科技项目(5400-202355570A-3-2-ZN) （5400-202355570A-3-2-ZN）
