OpenDSO delivers edge interoperability, multi-party integration, and application intelligence for advanced data center power operations — from peak load shaving to multi-site workload optimization.
What OpenDSO Delivers
Data center power demand is expected to grow at a 23% CAGR through 2030. AI workloads and cooling demands create peak loads that traditional DCIM tools — focused only on internal PUE — were never designed to handle.
Digitally model the data center electrical network, simulate performance, and test optimization strategies including HIL testing of energy management logic before deployment.
Monitor real-time loads at PDUs, utility meters, and transformers. Intelligently control generation, storage, and load resources to optimize the power footprint.
Dispatch onsite resources and schedule load shifting in response to utility constraints or wholesale market price signals.
Manage multiple data centers as networked microgrids, transferring workloads between sites based on grid conditions and pricing.
Use Case 1: Peak Load Shaving
Challenge: AI workloads and cooling demands create peak loads driving costly demand charges. Traditional DCPM focuses only on internal PUE.
Solution: OpenDSO monitors loads at PDUs, the utility meter, and the distribution transformer. When a rolling average peak load threshold is exceeded, available PV and ESS resources are dispatched automatically. AI training workloads can be deprioritized in real time. ESS units recharge during off-peak periods.
Value: Smooth peak loads, reduce electricity costs, increase site reliability, reduce exposure to market pricing volatility.
Use Case 2: Renewable Integration and Carbon Reduction
Challenge: On-site solar and storage offer clean power but variability and ramp rates challenge data center reliability.
Solution: OpenDSO monitors renewable output, intermittency, and ramp rate. When solar output drops or ramps unexpectedly, storage is dispatched to smooth the effect. Off-peak periods trigger automated recharge.
Value: Improve quality of supply while reducing carbon footprint. Reduce reliance on the utility grid and exposure to wholesale market pricing.
Use Case 3: Multi-Site Load Shifting
Challenge: Local price spikes or supply constraints at one site may require dynamic workload shifting across a portfolio of locations.
Solution: OpenDSO monitors PDU loads at each site, uses AI/ML and simulation to forecast compute load, develops an optimal combined schedule, and executes control actions to shift compute from higher-cost to lower-cost sites.
Value: Reduce load at higher-cost sites. Reduce overall carbon footprint. Improve portfolio efficiency.
Ready to modernize your Energy Network Operations?
OpenDSO is deployed and operational across utility and prosumer environments today. Whether you're evaluating platforms or ready to begin deployment, our team is available to walk you through the architecture, capabilities, and integration path for your environment.