Optimisation of night-time ventilation parameters to reduce building's energy consumption by integrating DOE2 and MATLAB

Abstract

We have developed an algorithm to optimise the fan flow rate by integrating DOE2 (building's energy simulation software) with MATLAB's genetic algorithm. In our developed algorithm, MATLAB can send desired values of optimisation variables for different hours to DOE2 to simulate building's energy use, and it can also receive building's energy consumption and other data from DOE2 for the optimisation. This powerful optimisation tool can be used for finding optimal solution of night-time ventilation fan flow rates and maximising energy savings. Results of optimisation are used to train a neural network to predict fan flow rates for different conditions. Night-time ventilation investigated in DOE2 considers parameters such as (1) night-time ventilation duration, (2) ventilation fan flow rate, (3) outdoor temperature, and (4) temperature difference between outdoor and indoor. Optimisation results show outdoor temperature between 10°C and 18°C and the temperature difference of more than 8°C are appropriate for night-time ventilation.