Analysing Domestic Electricity Smart Metering Data Using Self Organising Maps

Authors

Fintan McLoughlin, Technological University DublinFollow
Aidan Duffy, Technological University DublinFollow
Michael Conlon, Technological University DublinFollow

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Applied mathematics, Statistics, Probability, Electrical and electronic engineering, Energy and fuels

Publication Details

CIRED Workshop, 29-30 May 2012, Lisbon, Portugal

Abstract

This paper investigates a method of classifying domestic electricity load profiles through Self Organising Maps (SOMs). Approximately four thousand customers are divided into groups based on their electricity demand patterns. Dwelling and occupant characteristics are then investigated for each group. The results show that SOMs are an effective way of classifying customers into groups in terms of their electrical load profile and that certain dwelling and occupant characteristics are significant factors in determining which group they end up in.

Recommended Citation

McLoughlin, F., Duffy, A. & Conlon, M. (2012). Analysing domestic electricity smart metering data using self-organising maps. CIRED Workshop, Lisbon, Portugal, 29-30 May.