Event Description

Rapid retrofitting of America’s existing building stock is of urgent national interest to improve energy efficiency and resilience. But how can cities plan for this significant transition with limited funding, data, resources, and time?

This session introduces a practical and scalable Urban Building stock digital twin for energy modeling developed by the Environmental Systems Lab at Cornell University. Designed to operate on widely available data, the model delivers robust, city-scale building physics models for predicting building energy use and thermal response in power outages. The digital twin platform analyzes existing energy consumption patterns. It predicts future energy consumption trends, allowing users to evaluate the impact of electrification, building retrofits, and extreme weather events on energy demand and emissions. It also enables cost and incentive modeling, helping cities and utilities assess financial feasibility and prioritize retrofit strategies. The session features a real-world case study from Ithaca, NY, the first U.S. city to commit to 100% building decarbonization and community-wide carbon neutrality. Within the session, we will provide pointers on how to scale this work to other communities.

Learning Objectives:

• Identify key public data required to build city-scale energy simulation models and recognize how these models can be improved using city-specific or private datasets.
• Understand how Urban Building Energy Modeling (UBEM) serves as an effective tool to analyze existing energy consumption patterns and predict future energy trends.
• Explore how UBEMs could inform energy policy, guide decarbonization planning, and prioritize retrofit interventions by providing detailed and accurate information about building retrofit potential, upgrade costs, and incentives eligibility.

Learn from real-world UBEM applications based on a case study from Ithaca, NY, the first U.S. city to commit to full building decarbonization.

Image: US General Accounting Office (GAO)