Tunable and computationally efficient framework for retrofitting: Budget allocation using income and spatial equity

Area of Science:

• Energy Policy
• Computational Social Science
• Sustainable Housing

Background:

• The residential sector is a major consumer of electricity (35% in the US).
• Home retrofitting is key to reducing energy costs and improving quality of life.
• Equitable distribution of retrofit funding is challenging, risking skewed benefits.

Purpose of the Study:

• To introduce RAISE (Retrofitting Allocation using Income & Spatial Equity), a novel framework for budget allocation.
• To maximize total energy savings from retrofits while ensuring fair distribution across geographic and income levels.
• To provide policymakers with a tool to balance energy efficiency goals with equity.

Main Methods:

• Developed hourly household consumption models (pre- and post-retrofit).
• Integrated diverse data: demographics, weather, solar irradiance, appliances, surveys.
• Introduced an income-weighted epsilon (IWϵ) index for two-tiered equity constraints (intercounty and intracounty).

Main Results:

• RAISE demonstrated 60-101% greater energy savings in a Virginia case study compared to current methods.
• The framework significantly reduced the proportion of low-income households receiving minimal retrofit cost benefits.
• The IWϵ index allows tunable trade-offs between energy savings and equity.

Conclusions:

• RAISE offers a computationally efficient and precise method for equitable allocation of retrofit budgets.
• The framework empowers policymakers to achieve both maximum energy savings and social equity.
• This approach addresses critical disparities in energy efficiency program benefits.