Novel demand-controlled optimization of constant-air-volume mechanical ventilation for indoor air quality, durability and energy saving

Demand-controlled ventilation (DCV) is widely used for the energy-efficient provision of indoor air quality. However, existing DCV requires a continuously variable airflow rate, and is not applicable to the constant-air-volume mechanical ventilation (generally in buildings with room air conditioners and free-running buildings). This study proposes a novel DCV for constant-air-volume mechanical ventilation. To achieve high ventilation efficiency, the proposed DCV operates the constant-air-volume mechanical ventilation continuously and intermittently at full-load/quasi-full-load and partial-load conditions respectively, which is controlled by the upper and lower concentration limits of indoor airborne pollutants (indicated by indoor CO₂ concentration). The larger upper and lower concentration limits are preferred for energy saving, but could deteriorate indoor air quality, and cause durability problems due to frequent on-off operations. A genetic algorithm-based optimization is developed to determine the upper and lower concentration limits to maximize energy efficiency while satisfying the demand on indoor air quality and avoiding excessively frequent on-off operations. Case studies verify that the ventilation performance of the proposed DCV optimization is more sensitive to the lower concentration limit than the upper concentration limit. The conventional methods (the continuous ventilation and the intermittent ventilation) for the constant-air-volume mechanical ventilation risk low energy efficiency and deteriorated durability. The proposed DCV optimization improves energy efficiency by up to 88% while meeting demanded indoor air quality and durability.