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Development of a stochastic virtual smart meter data set for a residential building stock - methodology and sample data

Adam Neale, Michaël Kummert and Michel Bernier

Article (2020)

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Cite this document: Neale, A., Kummert, M. & Bernier, M. (2020). Development of a stochastic virtual smart meter data set for a residential building stock - methodology and sample data. Journal of Building Performance Simulation, 13(5), p. 583-605. doi:10.1080/19401493.2020.1800096
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Abstract

Existing electricity smart meter data sets lack sufficient details on building parameters to evaluate the impact that home characteristics can have on electricity consumption. An extensive, open-source virtual smart meter (VSM) data set with corresponding building characteristics is provided. The methodology used to develop the VSM data is presented in detail. The data set consists of a variety of homes representative of a subset of the Canadian single-family home building stock. The building characteristics cover a wide range of values that are based on probability distributions developed using a segmentation and characterization process. The resulting framework and VSM data set can be used by researchers to develop classification models, verify load disaggregation algorithms, and for a variety of other purposes.

Uncontrolled Keywords

smart meter data; building energy simulation; residential

Open Access document in PolyPublie
Subjects: 2100 Génie mécanique > 2100 Génie mécanique
2100 Génie mécanique > 2107 Modélisation, simulation et méthodes des éléments finis
Department: Département de génie mécanique
Research Center: IVADO - Institut de valorisation des données
Funders: IVADO
Grant number: PRF-2017-12
Date Deposited: 14 Dec 2020 10:40
Last Modified: 01 Sep 2021 01:15
PolyPublie URL: https://publications.polymtl.ca/5510/
Document issued by the official publisher
Journal Title: Journal of Building Performance Simulation (vol. 13, no. 5)
Publisher: Taylor & Francis
Official URL: https://doi.org/10.1080/19401493.2020.1800096

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