期刊文献+

Electric Load Clustering in Smart Grid:Methodologies,Applications,and Future Trends 被引量:9

原文传递
导出
摘要 With the increasingly widespread of advanced metering infrastructure,electric load clustering is becoming more essential for its great potential in analytics of consumers’energy consumption patterns and preference through data mining.Moreover,a variety of electric load clustering techniques have been put into practice to obtain the distribution of load data,observe the characteristics of load clusters,and classify the components of the total load.This can give rise to the development of related techniques and research in the smart grid,such as demand-side response.This paper summarizes the basic concepts and the general process in electric load clustering.Several similarity measurements and five major categories in electric load clustering are then comprehensively summarized along with their advantages and disadvantages.Afterwards,eight indices widely used to evaluate the validity of electric load clustering are described.Finally,vital applications are discussed thoroughly along with future trends including the tariff design,anomaly detection,load forecasting,data security and big data,etc.
出处 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2021年第2期237-252,共16页 现代电力系统与清洁能源学报(英文)
基金 supported in part by the National Natural Science Foundation of China(No.51877189) National Natural Science Foundation of China Joint Program on Smart Grid(No.U2066601) Young Elite Scientists Sponsorship Program by China Association of Science and Technology(No.2018QNRC001)。
  • 相关文献

参考文献2

二级参考文献31

共引文献807

同被引文献129

引证文献9

二级引证文献64

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部