A review on clustering of residential electricity customers and its applications

Rajabi, A; Li, L; Zhang, J; Zhu, J; Ghavidel, S; Ghadi, MJ

A review on clustering of residential electricity customers and its applications

Rajabi, A

Li, L

Zhang, J

Zhu, J

Ghavidel, S Ghadi, MJ

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Publication Type:: Conference Proceeding
Citation:: 2017 20th International Conference on Electrical Machines and Systems, ICEMS 2017, 2017
Issue Date:: 2017-10-02

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Field	Value	Language
dc.contributor.author	Rajabi, A https://orcid.org/0000-0002-3203-9861	en_US
dc.contributor.author	Li, L https://orcid.org/0000-0001-8485-2216	en_US
dc.contributor.author	Zhang, J https://orcid.org/0000-0003-2616-6722	en_US
dc.contributor.author	Zhu, J https://orcid.org/0000-0002-9763-4047	en_US
dc.contributor.author	Ghavidel, S	en_US
dc.contributor.author	Ghadi, MJ https://orcid.org/0000-0002-5564-5055	en_US
dc.date.available	2020-05-25T19:27:42Z
dc.date.issued	2017-10-02	en_US
dc.identifier.citation	2017 20th International Conference on Electrical Machines and Systems, ICEMS 2017, 2017	en_US
dc.identifier.isbn	9781538632468	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126316
dc.description.abstract	© 2017 IEEE. Clustering is a well-recognized data mining technique which enables the determination of underlying patterns in datasets. In electric power systems, it has been traditionally utilized for different purposes like defining customer load profiles, tariff designs and improving load forecasting. Some surveys summarized different clustering techniques which were traditionally used for customer segmentation and load profiling. The recent changes in power system structure and introduction of new technologies necessitate the new investigation of applications and benefits of clustering methods for power systems. In this regard, this paper aims at reviewing the new research for clustering techniques for residential customers.	en_US
dc.relation.ispartof	2017 20th International Conference on Electrical Machines and Systems, ICEMS 2017	en_US
dc.relation.isbasedon	10.1109/ICEMS.2017.8056062	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	A review on clustering of residential electricity customers and its applications	en_US
dc.type	Conference Proceeding
utslib.for	090607 Power and Energy Systems Engineering (excl. Renewable Power)	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. Clustering is a well-recognized data mining technique which enables the determination of underlying patterns in datasets. In electric power systems, it has been traditionally utilized for different purposes like defining customer load profiles, tariff designs and improving load forecasting. Some surveys summarized different clustering techniques which were traditionally used for customer segmentation and load profiling. The recent changes in power system structure and introduction of new technologies necessitate the new investigation of applications and benefits of clustering methods for power systems. In this regard, this paper aims at reviewing the new research for clustering techniques for residential customers.

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http://hdl.handle.net/10453/126316