IMPACT OF PARAMETERS ON THE CALIBRATION OF A NET-ZERO ENERGY BUILDING

Abstract

Building energy has always been a major topic in Singapore, due to the uncertainty in energy sources and climate change on occupant’s comfort. Creating a building model that can effectively represent energy consumption and generation is crucial in evaluating the relative importance of building parameters in model calibration. These will aid in energy optimisation, prediction of future trends and scheduling of asset enhancement initiatives.

In the context of Singapore, a Net-zero Energy Building (ZEB) is modelled and evidence-based calibration is conducted on the model. Model parameters changed in each iteration follow the order of customising weather files; solar panels; plug loads and lighting systems; and the HVAC system. Measured data was used for day typing and the creation of diversity schedules. After each round of model change, the model is simulated and error checks are calculated to ensure that the calibration satisfies ASHRAE’s recommended threshold limit.

The model was successfully calibrated, with -1.965% and 12.266% for Normalised Mean Bias Error (NMBE) and Coefficient of Variation of the Root Mean Square Error [CV(RMSE)] respectively, for the monthly electricity generated by the solar panels. Hourly electricity consumption by the other model parameters is less than ±11% for NMBE and ±20% for CV(RMSE).

Key findings for this study is that occupancy-related parameters, especially the HVAC parameter, are more impactful and influential on the calibration process. Also, results showed an opportunity for energy savings in the HVAC parameter. The main limitation of this study is the lack of model validation.