Exploration of HVAC system sizing based on building performance simulation and Monte Carlo method

Abstract

This study uses the Monte Carlo method and building performance simulations to develop an additive model for rapid peak load forecasting at design phase that considers the effects of design parameters. The Monte Carlo method generates numerous of simulation cases and EnergyPlus software is used for the calculations. Specifically, a total of 20 parameters were considered for analysing the peak load calculations, including design day conditions, envelope performance, infiltration, etc. An office building was selected as the reference building. With the screening experiments and the standard regression coefficient, it was identified that there are 15 important parameters for peak cooling load in the perimeter zones and 7 in the core zone. Main effects and interactions for selected parameters were determined by factorial experiments of 40,000 runs for the perimeter zone and 1,287 runs for the core zone. Main effects and interactions were used to develop an additive model between design parameters and peak cooling loads. Finally, model validation by additional 1,000 cases shows a coefficient of determination of 0.995, with a mean bias error of 3.2%, and a coefficient of variation of 3.7%, which indicated that the developed additive model had high accuracy.