A global model of hourly space heating and cooling demand at multiple spatial scales

Abstract Accurate modelling of the weather’s temporal and spatial impacts on building energy demand is critical to decarbonizing energy systems. Here we introduce a customizable model for hourly heating and cooling demand applicable globally at all spatial scales. We validate against demand from ~5,000 buildings and 43 regions across four continents. The model requires limited data inputs and shows better agreement with measured demand than existing models. We use it first to demonstrate that a 1 °C reduction in thermostat settings across all buildings could reduce Europe’s gas consumption by 240 TWh yr −1 , approximately one-sixth of historical imports from Russia. Second, we show that service demand for…

• EA
  Engineering and Physical Sciences Research Council

  Awards: EP/R045518/1, EP/T023031/1, EP/T023031/1, EP/R045518/1