Geospatial Factors Affecting Equitable US Residential Heating Electrification

The heating sector accounts for almost half of total global energy consumption, with only 1/10th of heat produced from renewables. The adoption and technological advancement of heat pumps is key to electrifying heating, introducing more renewable sources, and decreasing energy expenditure. However, a range of complex barriers–including upfront costs, electricity costs, outdoor temperature, and building characteristics–hinder widespread heat pump adoption. High- resolution temporal and geospatial analysis is a powerful tool for understanding the patterns of such barriers, improving discernment of issues specific to certain populations. This project characterizes different heat pump technologies’ effects on residential energy use and expenditure with a high-resolution linear regression model of energy demand. We constructed linear regression efficiency models for two types of market-available heat pumps, characterized by refrigerant type and compressor type. With the thermal comfort energy demand estimates and estimated heat pump efficiency, we calculated the census tract, hourly-level energy demand in a 100% heat pump adoption case. We obtained these energy demand estimates for the states of Colorado and California–chosen due to their diverse climates and demographics–and used these energy demand estimates to calculate heat pump cost, electricity grid emissions, and energy burden. We also performed a case study comparison with actual heat pump energy consumption data for a household in West Lafayette, Indiana. 

We found that heat pumps reduce total heating energy consumption and overall energy consumption for nearly all census tracts in both Colorado and California. In addition, for heating and overall energy consumption, our market average R410A heat pump model has the lower total variable cost in all census tracts relative to our R32 heat pump model. For cooling energy consumption, the R32 heat pump operates at a lower total variable cost than the R410A heat pump in most census tracts. Heat pumps tend to decrease average energy burden—percentage of household income dedicated to energy expenditure—in the less population-dense areas of both states. However, heat pump adoption leads to increased energy burden within cities. In comparison to our case study West Lafayette household, we obtained a relative root mean squared error for daily energy consumption of 28%, which is higher than studies using detailed engineering models at a single household-level but lower than studies using building simulation models.