A Demand Response-Integrated Shared Energy Storage Planning Method for Data Center Clusters

To address low utilization and poor economic returns in standalone energy storage for data centers, this study proposes a shared energy storage planning method for data center clusters, integrating demand response. The approach leverages complementary storage demands across different operational scenarios to minimize investment costs while maximizing efficiency. It establishes a cluster-based framework with scenario-driven capacity allocation, cost-sharing. The method also develops a room-level energy management model coordinating batch loads and precision cooling in demand response, while aligning storage constraints with cluster-wide benefit maximization. A multi-timescale optimization architecture and scenario selection mechanism enhance robustness through temporal decoupling and critical scenario analysis. Case studies show a 10.2% reduction in investment costs, a 34.12% decrease in installed power and energy capacity, and a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{2 0 \% - 3 0 \%}$</tex> reduction in high-price period consumption <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(254.9-286.5 \text{kW})$</tex>. This solution supports coordinated energy infrastructure planning, especially for heterogeneous computing loads and renewable energy integration.