Abstract
A novel strategy that combines separate probabilistic models developed by other researchers into a unified model for generating schedules of active occupancy, domestic hot water (DHW) use, and non-HVAC electricity use in multiple residences with a 10-min resolution for every day of the year is described. A variety of new model functions are introduced in order to generate stochastic predictions for each of numerous residences at once, to enforce appropriate variability of behaviors between dwellings and to ensure that domestic hot water and electricity use are coincident with occupancy. The separate models used in this paper were previously developed for the US and the UK; in the unified model, scaling factors were added to these models to adjust the predictions so as to better agree with national aggregated data for Canada. The unified model was validated with measurements of domestic hot water use and electricity consumption from the 40 residential units of a social housing building in Quebec City, Canada. The behavior of occupants in the case study building was simulated 100 times in order to validate the outputs of the unified model. Goodness-of-fit tests applied to each of these simulations showed that the fit between simulated and measured dwelling-per-dwelling distributions was acceptable for 97% of the DHW consumption profiles and for 92% of the electricity consumption profiles. However, there remain discrepancies between simulations and measurements, such as an overestimation of the DHW and electricity consumption in the morning.
Original language | English |
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Article number | 109375 |
Journal | Energy and Buildings |
Volume | 202 |
Early online date | 13 Aug 2019 |
DOIs | |
Publication status | Published - 1 Nov 2019 |
Funding
The authors are grateful to Natural Sciences and Engineering Research Council of Canada for the financial support through its IRC and CRD programs ( IRCPJ 461745-12 and RDCPJ 445200-12 ) as well as the industrial partners of the NSERC industrial chair on eco-responsible wood construction (CIRCERB). The first author is also supported by the Fonds de recherché du Québec – Nature et technologies ( FRQNT ). This work was possible thanks to a Canadian Queen Elizabeth II Diamond Jubilee Scholarship which allowed the first author to spent four months at the University of Bath (UK). The authors are also grateful to the Société d'Habitation du Québec (SHQ) for providing the data for the residential building presented in Section 4 . Ramallo-González would like to thank the program Saavedra Fajardo ( 20035/SF/16 ) funded by Consejería de Educación y Universidades of CARM , via Fundación Séneca-Agencia de Cinecia y Tecnología de la Región de Murcia and the Spanish Ministry of Economy and Competitiveness through PERSEIDES (ref. TIN2017-86885-R).
Keywords
- Domestic electricity consumption
- Domestic hot water use
- Energy modelling
- Occupant behavior
- Social housing
- Stochastic model
ASJC Scopus subject areas
- Civil and Structural Engineering
- Building and Construction
- Mechanical Engineering
- Electrical and Electronic Engineering
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Sukumar Natarajan
- Department of Architecture & Civil Engineering - Professor
- Centre for Regenerative Design & Engineering for a Net Positive World (RENEW) - Centre Director
- Centre for Digital, Manufacturing & Design (dMaDe)
- Centre for Climate Adaptation & Environment Research (CAER)
- Centre for Bioengineering & Biomedical Technologies (CBio)
- Centre for Sustainable Energy Systems (SES)
Person: Research & Teaching, Core staff, Affiliate staff