Watts vs. Bytes: Turning Data Centers into Grid Assets via Storage Compute Co-Optimization

Data center interconnections increasingly face tighter peak-demand and ramp-rate limits while being expected to support grid operations. Satisfying these requirements calls for coordinated computing and energy controls, yet their joint operational and economic implications remain poorly understood. To tackle this problem, we formulate a robust day-ahead co-optimization of computing load scheduling, server dynamic voltage and frequency scaling (DVFS), and co-located battery energy storage system (BESS) dispatch. The resulting mixed-integer linear program hedges against uncertainty in fixed load and ancillary service deployment while enforcing interconnection limits on peak demand and ramp rate, ancillary service capacity commitments in reserve and flexible ramping, and workload execution constraints. Case studies using CAISO and PJM market data of a 100~MW data center with a 36~MWh/12~MW BESS show that workload scheduling, DVFS, and storage provide complementary flexibility. Under binding peak-load limits, increasing the schedulable workload share reduces mean daily operating cost by up to 20.7%, and the daily value of storage more than doubles relative to operation under less restrictive limits. Under normal conditions, optimal BESS sizing is driven more by capital cost and cycling allowance than by energy duration alone. An 8~MW aggregate ancillary service commitment increases operational cost by only 0.4%, whereas reserve-only requirements become infeasible at commitments as small as 4~MW. These findings show that coordinated computing and storage controls can support grid services economically under binding interconnection constraints while protecting workload delivery.