Energy poverty is a topic often neglected in the discussion about global climate change. Apocalyptic prophecies about the negative future effects of climate change ignore the suffering of people around the globe whose lives could be drastically improved with access to reliable sources of energy. Though energy poverty from a global perspective is much more serious than energy poverty from a domestic perspective, high home energy bills are a serious cause for concern for many Americans. This research examines the relationship between regulation, the prices of electricity and natural gas, and the household energy burden, which is the ratio of household energy expenditures to household income. Where the household energy burden exceeds six percent of household income, households are at the brink of living with a high household energy burden. High household energy burdens can become a generational poverty trap, so understanding what contributes to a high household energy burden may help decision makers determine how to proceed when shaping energy-related and poverty-related policy.

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<p>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. </p> <p><br></p> <p>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. </p>