Quantifying the impact of uncertainty in human actions on the energy performance of educational buildings

Actions taken by building occupants and facility managers can have significant impacts on building energy performance. Despite the growing interesting in understanding human drivers of energy consumption, literature on the topic remains limited and is mostly focused on studying individual occupancy actions (e.g., changing thermostat set point temperatures). Consequently, the impact of uncertainty in human actions on overall building performance remains unclear. This paper proposes a novel method to quantify the impact of potential uncertainty in various operation actions on building performance, using a combination of Monte Carlo and Fractional Factorial analyses. The framework is illustrated in a case study on educational buildings, where deviations from base case energy intensity levels exceed 50 kWh/m2/year in some cases. The main contributors to this variation are the thermostat temperature set point settings, followed by the consumption patterns of equipment and lighting systems by occupants during unoccupied periods.