A probabilistic approach toward achieving net-zero energy buildings using a stochastic office tenant model

Abstract

During the simulation-aided net-zero energy (NZE) building design process, there is major uncertainty related to occupancy schedules, occupant behavior, and the corresponding effect on thermal and electrical loads in buildings—particularly as building envelopes, lighting, and mechanical systems become more efficient. As a result, designers’ assumptions about occupant-related energy use may have a significant impact on equipment sizing and the associated capital cost. To demonstrate a design process that considers the relationship between uncertainty from occupants and corresponding costs, this paper used a stochastic office tenant model (occupancy, lighting, and plug loads) for photovoltaic (PV) system sizing of an NZE building. Using the medium Canadian office reference building model as a case study, it was found that uncertainty of occupants for sizing PV is very expensive if the objective is to be highly confident that the building will be NZE. The results revealed that each incremental percentage point of improved certainty toward achieving NZE becomes increasingly expensive.