Residential rooftop solar adoption can paradoxically lead to higher total electricity consumption than expected because “free” PV electricity lowers household energy costs, prompting some additional usage. EPIcenter affiliate Oliver and his Georgia Tech colleague Toroghi propose an innovative method that pairs economic demand modeling with high-resolution GIS PV potential analysis to estimate this “direct rebound effect” (DRE) at the census block-group level. Using Fulton County, GA, as a case study, they predict that under a moderate PV diffusion scenario (20% rooftop coverage), households on average offset only about 94 kWh of grid electricity for each 100 kWh generated by PV—i.e., a 5.8% rebound. This rebound is notably higher in lower-income, dense neighborhoods (nearly 28% in extreme cases) and much lower in affluent suburbs (often < 1 %). The framework’s spatial granularity allows utilities to forecast net residual demand more accurately and helps policymakers design tailored incentives—e.g., coupling PV subsidies with energy-efficiency measures—particularly in high-rebound areas. By revealing how economic and spatial factors interact to shape real-world PV savings, this approach equips engineers, regulators, and entrepreneurs with actionable insights to integrate solar into the grid while minimizing unintended demand growth.
This summary was written with the assistance of Microsoft Copilot on June 25th, 2025. Its content was edited and verified by EPIcenter staff and affiliates.
Read the full paper: https://www.sciencedirect.com/science/article/abs/pii/S0306261919310657