Methodology & Technical Documentation
This calculator models how large data center loads affect residential electricity bills, with particular attention to capacity market dynamics and the supply curve effects that can cause cost spillovers to existing ratepayers.
Endogenous Capacity Pricing
This calculator models how capacity prices respond dynamically to changes in reserve margin. When large data center loads consume available reserves, prices can spike non-linearly. The PJM 2025/26 auction provides a real-world example of this dynamic.
$269.92
PJM 2025/26 capacity price ($/MW-day)
10x
Increase from prior year ($28.92)
63%
Attributed to data center load growth
Our model projects residential electricity bills under four scenarios, each representing different data center operational strategies:
Baseline
Normal cost growth from infrastructure aging, inflation, and baseline system upgrades. No data center load added.
Typical Data Center (Firm Load)
Data center operates at 80% load factor, adding 100% of capacity to system peak. Maximum infrastructure and capacity market impact.
Flexible Data Center
Data center curtails 25% during peaks (validated by EPRI DCFlex). Runs at 95% load factor by shifting workloads to off-peak hours.
Optimized (Flex + Dispatchable)
Flexible operation plus onsite generation during peaks. Minimizes grid draw and can actually reduce system peak contribution.
About the 25% Flexibility Assumption
The 25% peak reduction capability is based on EPRI's DCFlex initiative—a 2024 field demonstration at a major data center that achieved 25% sustained power reduction during 3-hour peak events. While theoretical analysis suggests up to 42% is possible, we use the field-validated 25% as a conservative baseline. See the Workload Flexibility Model section for details.
Questions or Feedback?
If you have questions about the methodology, want to report an error, or have suggestions for improvement, we'd love to hear from you.
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