Model-Based Extreme Weather Data for Predicting the Performance of Buildings Entirely Conditioned by Ambient Energy

Abstract

Abstract This study reports the development of extreme meteorological year (XMY) data for simulating buildings that are heated and cooled entirely by ambient energy in four climates varying in outdoor temperature and cloudiness. Electrification of conventional buildings is insufficient to meet climate goals since nearly half of U.S. electricity will still be produced from fossil fuels by 2050. Ambient-conditioned buildings depend on non-fossil sources such as the sun for heating and nighttime air or sky radiation for cooling. Such buildings are more susceptible to weather variability than conventional buildings, which simply use more auxiliary energy whenever weather conditions are challenging. On the other hand, ambient-conditioned buildings are more resilient to power outages so long as the design accounts for unusual weather during extreme years to consistently maintain indoor comfort. Ambient-conditioned buildings designed to remain comfortable with typical meteorological year (TMY2020) data produced up to over 1000 h per year of uncomfortable indoor temperature during the years (1998–2020) from which the TMY was derived. Parameters related to outdoor air temperature, sky temperature, and insolation were found to be unreliable for identifying the most challenging years. Rather, a whole-building model allowed the identification of the two most challenging years for heating and cooling, respectively. An XMY file concatenated from the most challenging summer and the most challenging winter provided a good match of indoor temperature predictions to those from the full individual years. This new XMY file facilitates the design of ambient-conditioned buildings for reliable indoor comfort.