Assessing the Mass Adoption of Demand Flexibility Strategies Across the U.S. Commercial Building Stock

Demand flexibility (DF) is a promising strategy to balance energy supply and demand, reduce electricity costs, and enhance grid reliability, but its large-scale potential in buildings across the United States remains underexplored. This study addresses this gap by applying the ComStock model's workflow with DF measures to conduct physics-based energy simulations for representative commercial buildings across U.S. climate zones to quantify state- and stock-level benefits of DF adoption. We evaluate two widely applicable DF strategies (thermostat setpoint adjustments and lighting dimming) under scenarios targeting peak reduction in buildings and peak relief for the grid. Depending on the specific design controls-such as determining daily dispatch windows-each DF measure may differently influence grid-level peak demand, individual building-level peak demand, and individual building-level electricity bill costs. Results reveal a fundamental trade-off: building-centric objective reduce individual building peaks by ~7% daily but provide little grid relief, whereas grid-oriented controls achieve 13%-20% grid-level peak reduction with limited benefit for individual buildings. Energy and utility bill cost savings are modest. Impacts vary across building types, U.S. climates, and grid characteristics. These findings underscore the potential and limitations of DF, highlighting the importance of aligning building and grid objectives through incentives and coordinated control strategies. By providing one of the first stock-level quantitative assessments of DF adoption in the U.S. commercial sector, this study offers actionable insights for utilities and other demand-intense entities to foster a more reliable and cost-efficient electricity ecosystem. The resulting dataset is publicly released to support future research and program design.