The building clusterability index: A scalable framework for spatially coordinated DER deployment in urban building stocks

Buildings are central to urban energy transitions, particularly as hosts of distributed energy resources (DERs). Yet large-scale deployment across city building stocks remains fragmented and reactive. Existing tools typically emphasize system design after candidate sites are selected, offering limited guidance on where DERs should be installed to maximize impact. This paper introduces a spatial planning framework that ranks buildings by their potential to form DER-enabled, energy-sharing clusters, using a novel performance-informed geospatial metric–the Building Clusterability Index (BCI). The BCI integrates energy performance indicators with each building’s local spatial context (feasible neighbors within a defined radius and obstacle-weighted connectivity) to score place-specific clusterability. This shifts the focus from optimizing individual DER sites to evaluating building clusterability–i.e., composition and feasibility of energy-sharing clusters at city scale–then zooming in to select implementable cluster portfolios. We model cluster selection as a weighted set packing problem and solve it using a scalable greedy algorithm. Applied to over 76,000 non-residential buildings in New York City, the framework identifies high-potential deployment zones while accounting for real-world spatial constraints, paving the way for subsequent project-level design, interconnection, and financial analysis. Comparative analysis against Pareto solutions–representing trade-offs between system performance and cost–demonstrates that our algorithm achieves near-optimal outcomes with practical efficiency. This approach enables planners to prioritize DER investments more strategically, supporting deliberate, system-aware energy transitions across complex urban building stocks.