Optimizing the Scheduled Operation of Window Opening and Blind to Enhance IAQ and Visual Comfort

High levels of carbon dioxide (CO₂) in classrooms can affect students’ ability to concentrate on academic tasks. CO₂ concentration in an indoor environment is commonly used as a metric for measuring air quality. Although this metric does not reflect all air containments, a high level of CO₂concentration can indicate towards insufficient ventilation of indoor space. In order to mitigate the impacts of climate change, governments in major economies have updated and/or developed building regulations to improve the thermal performance of building fabric, with a view to reduce heating and cooling energy consumption in buildings. With the sustained reduction in heating/cooling energy demand, the share of energy used for artificial lighting increases. For example, artificial lighting accounts for 25-40% of the total building energy consumption in the USA. In addition to the physical factors such as building form, orientation, glazing characteristics and location, energy use for artificial lighting depends on behavioural and psycho-physiological factors of occupants. Previous research suggests that sub-optimal operation of movable insulation such as blinds and curtains have an impact on artificial lighting use and occupant comfort (thermal and visual) with a resulting impact on energy use. This research is aimed at developing a method for optimising the operation of window opening to facilitate natural ventilation and window blinds to reduce energy consumption in a low energy educational building (rated BREEAM excellent ≈ LEED platinum). The research employs model-based optimization using daylight-coupled thermal model in EnergyPlus to model the interrelationships between blind positions; window opening; lighting and heating/cooling energy consumption; and thermal comfort.