负荷模型辨识中广域电网负荷空间分类  

Wide Area Grid Load Space Classification in Load Model Identification

作　　者：戴嘉祺[1] 郝丽丽[1] 

机构地区：[1]南京工业大学电气工程与控制科学学院,江苏南京211816

出　　处：《电网与清洁能源》2016年第1期36-41,共6页Power System and Clean Energy

基　　金：国家自然科学基金资助项目(51307078)~~

摘　　要：提出了负荷模型辨识中广域电网负荷的空间分类方法,基于工业、商业、农业、居民及其他负荷的典型值数据,通过模糊均值聚类(FCM)算法对负荷按负荷性质空间分类,辅以灵敏度计算公式确定重点辨识参数,进而以遗传优化算法并结合暂态过程各种扰动设置中电压响应曲线的交互计算,以全网母线电压跌落最为严重的母线作为观察变量,辨识修正负荷模型参数,并以不分类、区域分类两种方法与文中所提出方法作对比,仿真结果表明,按负荷性质分类具有合理性与有效性。This paper proposes the space classification method of the wide area grid load in load model identification.Based on typical values of the industrial,commercial,agricu-ltural and residential loads and other loads,the fuzzy means clustering（FCM）algorithm is used for the space classification of loads according to the load nature,and for the determination of key identification parameters with help of the sensitivity calculation formula. Furthermore,the genetic optimization algorithm combined with the interactive computing of the voltage response curve in setting the various disturbances in the transient process is used to identify and correct the load model parameters,with the bus of the largest voltage drop in the whole grid as the observation variable. The method proposed is compared respectively with no-classification and regional classification methods and the simulation result shows that the classification by the load nature is both reasonable and effective.

关 键 词：负荷模型 空间分类 模糊均值聚类 负荷性质 

分 类 号：TM743[电气工程—电力系统及自动化]