LAUSR

Abstract Ventilation affects building energy use and indoor air quality, with minimum rates prescribed by standards. However, research has demonstrated positive outcomes associated with increasing ventilation, including occupant productivity from increased work performance and reduced absenteeism. Herein, a novel ventilation strategy was proposed and simulated for offices, which optimized day-averaged ventilation rates over an annual time horizon to provide maximal amounts of outdoor air and so maximize occupant productive work hours, within varying energy use constraints. Energy use and productivity were often influenced by ventilation oppositely, so results were Pareto optimal. This optimization methodology was simulated in three locations for an average- and high-performance small office building, considering users with varying levels of confidence in ventilation-productivity relationships. To contextualize potential optimization impacts, four annual energy budgets were first determined for a typical year at constant ventilation rates of 8.5, 10, 20, and 30 L/s/occupant, and then for those four cases, day-averaged ventilation rates were optimized over annual trajectories considering the constrained energy budgets. Among all simulated cases, lost productive hours due to lower ventilation at constant rates were halved when using the optimized higher annual rates, with a gain of ~20 h/year per occupant on average, amounting to approximately $48/m2 at standard occupant density and mean wage. Offline optimization results were used to develop heuristic rules to predict a ventilation rate for any single day based on weather forecast that would adhere to a building- and climate-specific Pareto optimization, opening avenues for future control strategies that use this framework in real buildings.