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Analysis of customer profiles on an electrical distribution network.

Akperi, B.T. and Matthews, P.C. (2014) 'Analysis of customer profiles on an electrical distribution network.', in Proceedings of 2014 49th International Universities Power Engineering Conference (UPEC) : 2-5 September 2014, Cluj-Napoca, Romania. , pp. 1-6.


It has become increasingly important for electrical distribution companies to understand the drivers of demand. The maximum demand at any given substation can vary materially on an annual basis which means it is difficult to create a load related investment plan that is robust and stable. Currently, forecasts are based only on historical demand with little understanding about contributions to load profiles. In particular, the unique diversity of customers on any particular substation can affect load profile shape and future forecasts. Domestic and commercial customers can have very different behaviours generally and within these groups there is room for variation due to economic conditions and building types. This paper analyses customer types associated to substations on a distribution network by way of principal component analysis and identification of substations which deviate from the national demand trend. By examining the variance spread of this deviation, data points can be labelled in the principal component space. Groups of substations can then be categorised as having typical or atypical load profiles. This will support the need for further investigation into particular customer types and highlight the key factors of customer categorisation.

Item Type:Book chapter
Keywords:Clustering methods, Load modeling, Power distribution, Principal component analysis.
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 March 2014
Date deposited:05 November 2015
Date of first online publication:September 2014
Date first made open access:No date available

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