Designing cost–robustness tradeoffs in urban building cluster networks for distributed energy coordination

Urban deployment of distributed energy resources (DERs) increasingly relies on coordinated building clusters capable of sharing energy and improving grid flexibility. A key design challenge is determining how buildings should be interconnected to balance infrastructure cost with robustness to link failures. While redundant interconnections can enhance robustness by preserving energy-sharing capability under failure conditions, the number of feasible network configurations grows rapidly with cluster size, making exhaustive evaluation impractical. This study introduces a cluster configuration selection framework that approximates the cost–robustness tradeoff while evaluating only a small subset of configurations. The approach integrates cooperative game theory and network science by quantifying building importance using Shapley values derived from cluster performance simulations and aligning these values with node centrality across a library of connected graph typologies. For each typology, candidate configurations are generated by minimizing the mismatch between performance-based importance and structural centrality, then evaluated under link failure scenarios to estimate expected performance and construct an approximate Pareto frontier. The framework is validated across 86 five-building clusters derived from geographically screened New York City building stock. After filtering clusters with no robustness benefit from redundant interconnections, the method recovers on average 95.32% of the true Pareto hypervolume and 83.36% of the dominated solution space while evaluating only 21–22 configurations per cluster (vs. 728 feasible). Results show that robust designs consistently emerge when high-contribution buildings occupy more central network positions, providing both a scalable evaluation approach and practical design insight for urban DER systems.