Quantifies how occupancy assumptions affect building performance in various climates, suggesting important policy refinements.
Building performance simulation (BPS) is an established method for informing building design and demonstrating compliance with building codes and certification programs. However, the accuracy of BPS models depends heavily on occupancy assumptions, which vary significantly across building codes and standards. This paper synthesizes and quantifies the impact of occupancy-related assumptions across 14 international building energy codes and standards on predicted building performance across different climates, covering energy, carbon, and comfort metrics. Four occupancy-based energy conservation measures (ECMs) are then evaluated to study their impact under the different occupancy assumptions: (i) occupancy-based lighting control, (ii) occupancy-based plug loads, (iii) occupancy-based temperature setpoints, and (iv) demand-controlled ventilation (DCV). An application to Canadian office-building archetypes demonstrates that different occupancy assumptions lead to performance variations up to 86% in electricity demand, 60% in natural gas consumption, and 100% in greenhouse gas emissions. Among the tested ECMs, occupancy-based thermostat setpoints significantly reduced peak energy loads and the number of unmet setpoint hours. More importantly, these controls also reduced the sensitivity of building performance to occupancy assumptions, highlighting the importance of aligning heating and cooling loads with actual occupancy patterns to mitigate performance risks. The findings underscore the need for regulators and standard-setting bodies to refine occupancy assumptions in performance-based compliance frameworks and consider a range of plausible occupancy scenarios to improve the reliability of policy outcomes under operational uncertainty. Finally, the study provides an open-access dataset and discusses policy implications.
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Markarian et al. (2026) studied this question.
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