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Building simulation tools are increasingly used during design of new as well as refurbishment of residential buildings. However, reliability of simulation is highly dependent on its inputs. The project investigated application of sensitivity analysis on input parameters for simulation of ten different residential ventilation control strategies. Nine strategies comprised demand control (DCV) one used constant air volume. Demand was represented by operative temperature, CO2, relative humidity or their combinations. They were measured either in ventilation exhaust or in particular rooms. Primary energy consumption and quality of indoor environment were evaluated. A low-energy apartment of 93.8 m2 placed in Nordhavn, Copenhagen, Denmark was used as a case study. Investigated input parameters were: heating set-point, occupancy schedule, window opening, internal heat and moisture gains, glazing area, g-value, solar shading and night ventilation. The control strategy capable of providing the best indoor climate (DCV with combination of sensors in individual rooms) was at the same time the most energy demanding. The sensitivity analysis revealed that heating setpoint and window opening were the most crucial input parameters with respect to primary energy consumption. Window opening was also the most influential factor with respect to overheating and moisture. Occupancy had a strongest effect on CO2.

Sensitivity analysis of control strategies for mechanical ventilation in a low-energy apartment building