全球能源互联网（英文）2024，Vol.7Issue(3)：313-323,11.DOI:10.1016/j.gloei.2024.06.004
区域大规模可调负荷聚合特征在线辨识与提取方法
Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics
摘要
Abstract
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
负荷聚合/区域大规模/在线辨识/特征提取方法Key words
Load aggregation/Regional large-scale/Online recognition/Feature extraction method引用本文复制引用
李思维,岳靓,孔祥玉,王成山..区域大规模可调负荷聚合特征在线辨识与提取方法[J].全球能源互联网（英文）,2024,7(3):313-323,11.基金项目
This work was supported by the State Grid Science&Technology Project(5100-202114296A-0-0-00). （5100-202114296A-0-0-00）
