Investigation of multiple indoor air quality and energy use tradeoffs to inform the development of next-generation ventilation strategies for office buildings

Adams Edwin Rackes

doi:10.17918/D8JM2B

In commercial buildings, ventilation, or air exchange between an indoor environment and the outdoors, is necessary for controlling contaminants emitted by indoor sources such as occupants, cleaning and personal care products, and building materials. In offices, increased ventilation has also been shown to significantly increase worker productivity and reduce sick leave. At the same time, increasing ventilation introduces more outdoor air pollutants, including ones with known public health consequences like particulate matter and ozone. Furthermore, ventilation accounts for about one-fourth of U.S. commercial heating, ventilation, and air-conditioning (HVAC) energy use and changes can have significant effects on building energy consumption. This research project aims to quantify, compare, and optimally or nearly optimally balance these multiple impacts for office buildings, while remaining alert to the fact that outcomes differ significantly by building, operating conditions, and user preference. The project had three objectives. The first was to use Monte Carlo analysis over a wide range of climates and office building characteristics to evaluate combinations of mature existing technologies including demand-controlled ventilation (DCV), economizing, supply air temperature reset, and increased ventilation rate (VR). Some combinations were 'win-win,' reducing HVAC energy consumption by 12-27% while increasing work performance by 0.5% and eliminating 5 hours of absenteeism per year. Annually, such strategies could save U.S. $1.25 billion in energy costs and generate $28-55 billion in total net benefits. The second objective was to develop an outcome-based ventilation (OBV) decision-making framework, using a loss function to combine scientific knowledge, uncertainty, and parameters to express user preferences. The OBV framework confirmed that human-related outcomes are much more valuable than energy use. For example, we evaluated an intervention that increased the VR by ~10 L/s/occ on a dataset representing the office sector. With "best estimate" user parameters, the average loss impact of every other outcome was greater than the one related to HVAC energy costs-by a factor of 47 for work performance, 25 for excess absence, 3.9 for particle exposure, and 1.1 for ozone exposure. Even the most ventilation-adverse user preferences still produced VRs that were very often as high as 30 L/s/occ and only rarely lower than 15 L/s/occ. The third objective was to use optimization with the OBV framework to minimize loss over a daylong horizon and take advantage of weather, pollution, occupancy, and other transient dynamics. An optimal control problem was formulated, then translated to a nonlinear optimization problem, and solved by interior point methods. Results showed that, contrary to our hypothesis, numerically optimizing ventilation control for a single day did not provide substantial Pareto improvements over existing control methods. In fact, a strategy with economizer and DCV was very close to Pareto optimal on most days. Neither time-of-use pricing nor any factor in a sensitivity analysis revealed opportunities in which optimizing ventilation within each day of the year saved more than 5% of annual HVAC energy costs. In concluding, we used the insights of this research to outline a procedure for next-generation ventilation that takes advantage of opportunities to optimize over an annual horizon and adjust for the influential climate and building parameters identified by sensitivity analysis. For daily control, it would employ existing successful technology components, like DCV and economizer controls, that we have shown to be capable of significant energy savings and, on a daily timescale, nearly optimal. These methods would be embedded in and guided by a more conscious annual strategy that includes an initial preference elicitation step and an offline annual optimization to intelligently allocate ventilation resources across the year. Such an approach could help make ventilation more effective and reliable, and allow users to make informed decisions about ventilation tradeoffs and understand their consequences.

Investigation of multiple indoor air quality and energy use tradeoffs to inform the development of next-generation ventilation strategies for office buildings

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Investigation of multiple indoor air quality and energy use tradeoffs to inform the development of next-generation ventilation strategies for office buildings

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