Open AccessIdentification classification of power user demand response effect based on electricity acquisition data
Author(s) -
Rui Ge,
Yiding Jin,
Changyou Feng,
Zhao Zhao,
Nan Wang,
Pengfei Li
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/371/5/052053
Subject(s) - demand response , identification (biology) , response time , load management , computer science , demand side , cluster analysis , electricity , dynamic demand , feature (linguistics) , power (physics) , electric power system , on demand , engineering , environmental economics , machine learning , economics , electrical engineering , linguistics , botany , computer graphics (images) , physics , philosophy , multimedia , quantum mechanics , biology
In recent years, the great potential of power demand-side resources in the power system has been gradually recognized and exploited, especially the demand response of power users. Demand-side management has received more and more attention. In order to clarify the rationality of the requirements response project design and the degree of implementation of the expected effect, this paper studies the demand response characteristics of powerusers’ electricity load. Based on the processing of load data using the analysis technology, the demand response feature indicator is proposed, taking into account the response capacity, response speed, response cycle, and using K-means clustering method to realize the identification and classification to the effect load response of users, and finally give power users demand response interactive Policy.