Coupling building performance simulations with mathematical optimization offers a promising solution to minimize energy use in buildings by identifying optimal design alternatives. However, uncertainties due to occupant behaviour and building operations are rarely considered in this process. To address this issue, we combined stochastic occupant behaviour modelling with building performance optimization. A single-story office building model was simulated in EnergyPlus using two occupant modelling approaches: (1) deterministic schedules as specified in the National Energy Code of Canada for Buildings, and (2) stochastic occupant behaviour and building operation models. The genetic algorithm was then applied to minimize electricity use following each approach, and later to simultaneously increase design robustness by minimizing variations in electricity use when stochastic models were used. Results highlighted the differences between optimal design alternatives for these two simulation approaches, especially when design robustness was added to the optimization objectives.

Additional Metadata
Keywords Building performance optimization, design robustness, occupant behaviour, stochastic occupant modelling
Persistent URL dx.doi.org/10.1080/19401493.2019.1680733
Journal Journal of Building Performance Simulation
Citation
Ouf, M.M. (Mohamed M.), O'Brien, W, & Gunay, H.B. (2020). Optimization of electricity use in office buildings under occupant uncertainty. Journal of Building Performance Simulation, 13(1), 13–25. doi:10.1080/19401493.2019.1680733