Research on user optimal aggregation based on demand response potential spectrum clustering analysis. Issue 13 (19th January 2018)

• Record Type: Journal Article
• Authors: Sun, Yanping; Gao, Yajing; Yang, Wenhai; Wang, Jingmin; Li, Hong
• Is Part Of: Journal of engineering. Volume 2017:Issue 13(2017)
• Page Start: 2152
• Page End: 2157
• Publication Date: 2018-01-19
• Subjects: demand side management -- optimisation -- power markets -- pattern clustering; demand response potential spectrum clustering analysis -- load aggregator -- response capacity -- electricity default rate -- market competitiveness -- resident users -- response potential curves -- time‐of‐use price -- user typical response curve -- spectral clustering -- dual‐scale similarities -- user response levels -- clustering centre -- user optimisation aggregation model; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2017.0711
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : Load aggregator (LA) needs to fully tap the demand response potential of the resources and aggregates the users with high response capacity and low electricity default rate. This can make LA to improve the market competitiveness and gain greater income. Firstly, the load data of resident users are analysed and compared. The summer typical daily response potential curves of users participating in time‐of‐use price are obtained. Secondly, the 24 h response values of the user's typical response curve are used as the data set of the spectral clustering based on dual‐scale similarities of distance and curve shape to classify the users, and the user's response levels are divided according to the clustering centre of each class. Next, the user optimisation aggregation model of LA considering risk is established. Finally, a practical case study is employed to verify the correctness and validity of the model.