Cornell researchers have developed a powerful urban building energy model that simulates a small city’s energy dynamics within minutes on a standard laptop—no supercomputers required. In a case study of Ithaca, New York, the tool mapped energy use across over 5,000 residential and commercial buildings, then ran simulations to help policymakers prioritize the most cost-effective decarbonization strategies, says Cornell Chronicle.
By modeling scenarios such as weatherization, electric heat pump installation, and rooftop solar adoption—while incorporating financial incentives—the model revealed striking insights. For instance, installing heat pumps alone could raise operational costs unless paired with building envelope upgrades and solar generation. Moreover, considering incentive structures shifted the focus: multifamily residential buildings emerged as the highest-value targets for retrofits, even over large commercial structures.
The tool’s automated workflow, rapid execution, and use of easily accessible datasets—such as geospatial maps, tax records, building permits, census data, and local utility energy-use agreements—enable even small cities without dedicated sustainability staff to make data-driven decisions. “From a small city to a county or state, this can shape policies and how you prioritize them,” says associate professor Timur Dogan.
Ithaca’s sustainability director contrasted this accessible approach with expensive supercomputer-backed initiatives—such as Oak Ridge National Lab’s Model America—that are impractical for most municipalities. The Cornell model allows cities to flag the top ~100 buildings out of thousands as priority retrofit candidates—making policy action more precise and affordable.
Cornell’s urban building energy model offers a cost-effective, scalable pathway for cities to decarbonize. By simulating retrofit scenarios quickly using accessible data and highlighting high-impact targets like multifamily residences paired with energy efficiency and solar, it empowers smarter, budget-conscious climate strategies—even in resource-limited communities.