Weather & Energy: Leveraging Real-Time Localized Weather Observations to Better Model Home Energy Efficiency

In conjunction with researchers at The University of Maryland, WeatherBug Home has developed an energy simulation model leveraging the WeatherBug weather observation network and data from internet connected thermostats. This presentation will start with the basics of the modeling process, simulation performance, and its use in energy efficiency recommendations and forecasted demand response capacity. The inverse model correlates thermostat temperature and HVAC operation data to historical weather observations (temperature, relative humidity, wind velocity, and solar irradiance). We will then focus on the value of data from the WeatherBug network, which has higher spatial and temporal resolution, versus data from the standard weather network. We will share the quantifiable modeling benefit of real-time, hyper-local weather data with unique parameters such as solar irradiance.