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Load profile segmentation using residential energy consumption data

conference contribution
posted on 2020-01-01, 00:00 authored by Shama IslamShama Islam, A Rahman, L Robinson
In this paper, a new approach for load profile segmentation is investigated for residential energy consumption. The proposed approach considers the daily level granularity and identifies dominant patterns of energy consumption for individual participants. The analysis uses adaptive k-means clustering to determine the number of clusters that improve the distances between data points and cluster centroids. The proposed method is applied to Ausgrid Solar Home Electricity Dataset for energy consumption data of 300 houses over 1 year. The results demonstrate distinctive features including peak energy consumption, time of peak energy use, as well as seasonal variations. The findings can help utilities to optimise demand response and pricing strategies.

History

Event

Smart Grids and Energy Systems. Conference (2020 : Online)

Pagination

600 - 605

Publisher

IEEE

Location

Online

Place of publication

Piscataway, N.J.

Start date

2020-11-23

End date

2020-11-26

ISBN-13

9781728185507

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

SGES 2020 : Proceedings of the 2020 International Conference on Smart Grids and Energy Systems

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