Calibrated Model of an Experimental Building to Test Passive Thermal Comfort Solutions for the Global South
Amanda Thouanojam, Prasad Vaidya, Gurneet Singh, Sanjay Prakash | 2022
India is the third largest carbon emitter in the Global South, with millions of people facing the threat of climate related impacts. Buildings currently account for about a third of its energy consumption, and the anticipated new construction presents a huge opportunity not just for climate mitigation but also to provide comfort and shelter in a rapidly changing climate. Designers and builders are innovating in several net-zero buildings, but beyond the annual or monthly energy consumption, detailed performance studies of such buildings are often not available. This paper presents the findings from a model calibration exercise for an experimental building in India that uses passive design techniques and has been built as a prototype to test several technologies and operation practices where the learning can be applied to a larger campus effort. Hourly data for one entire month with significant diurnal variation were used in the calibration of the Energy Plus model. While the ASHRAE Guideline 14 thresholds for Mean Bias Error (MBE) and Root Mean Squared Error (RMSE) were met (at 9% and 14% respectively) through the calibration process, several issues were uncovered during the calibration. These included: challenges with using the pyranometer radiation data in the Actual Meteorological Year (AMY) weather, because changing the Global Horizontal Radiation had no impact on the results; the importance of window operation for calibrating a model of a passive building; the inability of the MBE and RMSE to capture significant errors in the shape of the indoor temperature profiles; and the usefulness of the calibrated model in uncovering problems with the measured data. Beyond this, the rigor of the modelling effort instilled confidence in the executives who were making investment decisions for the larger campus, which enabled discussion on the Life Cycle Cost of the proposed systems against several baseline scenarios.