The nighttime ventilation strategy uses the outdoor cold air during the night to cool the building mass. The cooled building mass then is used as a heat sink during the next hot day. Mechanical nighttime ventilation requires a fan for the outside air ventilation. The energy use by the fan reduces the potential cooling energy savings. Higher nighttime ventilation flow rate and its duration decrease required cooling energy during next hot day in the building, also they increase fan energy consumption. In an optimal nighttime ventilation operation, these parameters need to be optimized based on each day outdoor temperature variation.
We have developed an algorithm to optimize fan flow rate by integrating DOE2 (building energy simulation software) with MATLAB’s genetic algorithm (GA). In our developed algorithm MATLAB can send desired values of optimization variable for different hours to DOE2 to simulate building energy use, also MATLAB can receive building energy consumption and other data from DOE2 for the optimization. This online connection between DOE2 and MATLAB create powerful building optimization tool. This optimization tool can be used for finding optimal solution of nighttime ventilation fan flow rates and maximizing energy savings. Also, by using this tool nighttime optimization can be easily applied to different buildings and systems. Nighttime ventilation can be investigated in DOE2 by considering effective parameters such as: 1) nighttime ventilation duration, 2) nighttime ventilation fan flow rate, 3) outdoor temperature set-point, and 4) temperature difference between outdoor and indoor. Optimization results show outdoor temperature between 10 to 18 °C and temperature difference more than 8 °C are appropriate for nighttime ventilation.