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Seasonal variation in household electricity demand: A comparison of monitored and synthetic daily load profiles
journal contribution
posted on 2018-10-02, 13:46 authored by Matthew Li, David AllinsonDavid Allinson, Miaomiao HeAbstract This paper examines seasonal variation in household electricity demand through analysis of two sets of half-hourly electricity demand data: a monitored dataset gathered from 58 English households between July and December 2011; and a synthetic dataset generated using a time-of-use-based load modelling tool. Analysis of variance (ANOVA) tests were used to identify statistically significant between-months differences in four metrics describing the shape of household-level daily load profiles: mean electrical load; peak load; load factor; and timing of peak load. For the monitored dataset, all four metrics exhibited significant monthly variation. With the exception of peak load time, significant between-months differences were also present for all metrics calculated for the synthetic dataset. However, monthly variability was generally under-represented in the synthetic data, and the predicted between-months differences in load factors and peak load timing were inconsistent with those exhibited by the monitored data. The study demonstrates that the shapes of household daily electrical load profiles can vary significantly between months, and that limited treatment of seasonal variation in load modelling can lead to inaccurate predictions of its effects.
Funding
This research was made possible by Engineering and Physical Sciences Research Council (EPSRC) support for the London- Loughborough Centre for Doctoral Research in Energy Demand [grant number EP/L01517X/1].
History
School
- Architecture, Building and Civil Engineering
Published in
Energy and BuildingsCitation
LI, M., ALLINSON, D. and HE, M., 2018. Seasonal variation in household electricity demand: A comparison of monitored and synthetic daily load profiles. Energy and Buildings, 179, pp. 292-300.Publisher
© The Authors. Published by ElsevierVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/Acceptance date
2018-09-10Publication date
2018Notes
This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/ISSN
0378-7788eISSN
1872-6178Publisher version
Language
- en