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Analysis of clustering techniques on load profiles for electrical distribution.

Akperi, B.T. and Matthews, P.C. (2014) 'Analysis of clustering techniques on load profiles for electrical distribution.', in POWERCON 2014 Chengdu : 2014 International Conference on Power System Technology : Towards green, efficient and smart power system. Proceedings of a meeting held 20-22 October 2014, Chengdu, China. , pp. 1142-1149.


The classification of electrical load profiles has become increasingly important as a driver for distribution companies in understanding substation data. The daily load profile can often give great insight into the types of customers connected to the substation and can assist with developing a long-term forecast. The literature in this area often uses data mining and clustering techniques to determine a load diagram representative for a subset of customers or substations. The type of technique used can often lead to representative load diagrams of unique shapes with differing numbers of customers belonging to each group. This paper analyses clustering techniques on representative load diagrams for primary substations at the distribution level. In particular, this paper will analyse clustering techniques in terms of their performance and effect on load profile groupings. The results show that K-means clustering showed the best performance in generating unique, well-populated cluster groups. This gives a greater understanding of the divisions between substations which can be used for future forecasting.

Item Type:Book chapter
Keywords:Clustering methods, Load modeling, Power distribution.
Full text:(AM) Accepted Manuscript
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Publisher statement:© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Date accepted:01 April 2014
Date deposited:05 November 2015
Date of first online publication:October 2014
Date first made open access:No date available

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