Stochastic bottom-up load profile generator for Canadian households’ electricity demand

Mohamed Osman, Mohamed Ouf, Elie Azar, Bing Dong

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


The residential energy demand timing and magnitude are highly impacted by occupants' behaviors and activities. However, acquiring a reliable data source for these activities is a vital challenge, especially on an urban scale. In this context, this paper presents a stochastic bottom-up model for generating electrical loads for residential buildings in Canada. The proposed model is developed to investigate the impact of different household characteristics, appliance stock, and energy behaviors on the timing and magnitude of non-HVAC energy loads at individual or multiple houses. The proposed tool includes four main modules for generating stochastic profiles of occupancy, lighting demand, appliance load, and domestic hot water demand (DWH). The model is calibrated using the Canadian time use survey (TUS), energy use statistics, and appliance ownership surveys. The model is scalable and can be extended to serve various applications by adding new modules and data sources in the future. This paper presents the model development methodology, generated high-resolution load profiles, and validation in comparison with actual measurements. Finally, the model is used for studying the impact of household characteristics on total energy use. Future work will include incorporating this model into a comprehensive agent-based model for designing and testing effective demand response programs.

Original languageEnglish (US)
Article number110490
JournalBuilding and Environment
StatePublished - Aug 1 2023


  • Bottom-up model
  • Load modeling
  • Markov chain
  • Occupant behavior
  • Stochastic modeling
  • Time use survey

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Building and Construction


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