Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics  

作　　者：Siwei Li Liang Yue Xiangyu Kong Chengshan Wang 

机构地区：[1]Key Laboratory of Smart Grid of Ministry of Education,Tianjin University,Tianjin 300072,P.R.China [2]Beijing Fibrlink Communications Co.,Ltd.,Beijing 100071,P.R.China

出　　处：《Global Energy Interconnection》2024年第3期313-323,共11页全球能源互联网（英文版）

基　　金：supported by the State Grid Science&Technology Project(5100-202114296A-0-0-00).

摘　　要：This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

关 键 词：Load aggregation Regional large-scale Online recognition Feature extraction method 

分 类 号：TM714[电气工程—电力系统及自动化]