Data-center developers should plan power demand as a staged, scenario-based engineering and utility program—not as a single megawatt estimate. Build a site-level model from the planned IT equipment, cooling system, facility design and commissioning schedule; maintain lower, base and higher demand cases; then take those cases to the utility and regulators early enough to study interconnection, transmission and distribution upgrades, tariffs and cost responsibility. Revisit the model whenever server orders, accelerator mix, workload utilization or efficiency assumptions change.
The stakes are national, but the answer is always local. Lawrence Berkeley National Laboratory’s 2026 update puts data centers at a central estimate of 11.8% of total U.S. electricity use in 2030, with a modeled range of 9.5% to 15.3%. The International Energy Agency’s 2025 base case is about 945 TWh of global data-center consumption in 2030. Neither figure predicts what one campus will receive from its grid. Data-center demand is geographically concentrated, and feasibility depends on the site, network, utility queue and project schedule.
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Why a conventional load estimate is no longer enough
Compute plans can change faster than power infrastructure. The IEA notes that a data center may be operational in two to three years, while generation, transmission and distribution projects generally require longer planning and construction periods. A campus that waits for a final equipment list before opening an interconnection workstream can discover that a technically feasible design cannot be energized on the desired date.
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The practical implication is to separate three questions:
- How much instantaneous electrical capacity must be firm at the site?
- How much energy will the facility consume over a year and in each operating period?
- When will each increment be needed, and what network work must precede it?
Answering those questions with explicit assumptions gives the utility a usable study case and gives the developer options when demand, delivery dates or costs move.
Build a site-level load model from the equipment plan
Start with an equipment inventory
List each deployment wave rather than applying one utilization factor to the entire ultimate campus. Record server types, accelerators, storage, networking, rack density, expected shipment dates, utilization and retirement or refresh assumptions. LBNL’s bottom-up U.S. methodology illustrates why these details matter: its estimate uses planned IT-equipment shipments, device electricity use, cooling simulations, facility type and location. Those inputs are assumptions to expose and test, not a substitute for project engineering.
Convert IT demand into facility demand
Model the electrical path from the IT load through power-conversion losses, cooling, pumps, fans, lighting, controls and other building services. Use the design’s operating temperatures and cooling architecture, because overhead can vary by season and by workload. Calculate both a maximum coincident demand and an annual or hourly energy profile. A rack-level nameplate sum is not the same as the substation peak, and annual terawatt-hours cannot tell a utility whether a transformer must carry a particular evening or summer peak.
Represent commissioning and phasing
For every building or data hall, show construction completion, electrical energization, equipment delivery, testing and production service separately. Include temporary construction loads and a realistic ramp rather than assuming that the ultimate load appears on day one. The resulting model should produce a time series or defined operating blocks that the utility can study, plus a clearly identified ultimate requirement for long-lead upgrades.
Keep an assumptions register
Assign an owner and confidence level to each material input. At minimum, track:
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- Server and accelerator shipment dates and quantities.
- Utilization, workload mix and growth in AI-related processing.
- Device efficiency, refresh cycles and expected power-management improvements.
- Cooling technology, climate conditions and seasonal performance.
- Facility location, building phase and electrical topology.
- Required redundancy, testing regimes and maximum coincident operation.
When a procurement decision changes one of these entries, the model should automatically show the effects on peak capacity, annual energy, interconnection stage and commissioning date.
Use scenarios instead of one forecast
Maintain at least three internally consistent cases: a lower-demand case, a base case and a higher-demand case. The cases should differ through explicit drivers, not arbitrary percentages. For example, a higher case might combine faster accelerator deployment, greater utilization and slower efficiency gains; a lower case might reflect delayed shipments, more efficient equipment or slower workload growth. Document which assumptions change and which remain fixed.
| Scenario | Purpose | Decisions it should inform |
|---|---|---|
| Lower demand | Tests whether the project remains economic and operable if deployment or utilization lags. | Minimum service commitment, staged contracts, temporary generation and deferral options. |
| Base demand | Represents the most supportable equipment, schedule and efficiency assumptions at the current design stage. | Utility study case, budget, permits and the commissioning plan. |
| Higher demand | Tests accelerated compute growth, denser equipment or weaker efficiency gains. | Reserved capacity, substation and feeder sizing, land for additional equipment and upgrade triggers. |
The IEA uses sensitivity cases because uncertainty is substantial. Apply the same discipline at the campus level. Re-run scenarios when a major accelerator order is placed, the workload mix changes, a cooling design is selected, a utility study returns new constraints or an efficiency assumption is no longer credible. A scenario is useful only if someone owns the trigger and has authority to change the plan.
Open the utility and regulatory workstream early
Request a capacity and schedule screen
Give the utility a phased load profile, required in-service dates, preferred voltage and reliability characteristics, site-control status and the three demand cases. Ask what capacity is available today, what portion is deliverable by each milestone and which studies are required before a commitment can be made. Distinguish an informal capacity indication from a binding interconnection agreement.
Understand the interconnection study
LBNL describes interconnection as central to identifying required transmission facilities and upgrades and determining cost allocation. Ask for the study sequence, assumptions, queue position, affected-system analysis, protection requirements, construction responsibilities and decision dates. Confirm whether an upgrade is needed for the base case only or for the higher case as well, and whether a staged service arrangement changes the scope.
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Clarify who pays and when
Obtain the utility’s rules for deposits, study fees, network upgrades, distribution extensions, land or easement work and refundable or nonrefundable contributions. A low quoted energy price does not mean a low delivered-power cost if the project bears major grid upgrades. Put every allowance and milestone in the financial model with an owner and a contingency.
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Include regulators and affected authorities
Permitting, resource adequacy, emissions rules, fuel approvals, water constraints and local reliability requirements can alter a supply option. Engage the relevant public utility commission, planning authority and environmental agencies on the schedule implied by each scenario. Early engagement is particularly important when a project proposes on-site generation, storage, unusual tariffs or load-curtailment arrangements.
Compare supply and flexibility options on the same basis
There is no universally preferred technology. Evaluate a utility-only design, staged utility service, on-site generation, storage and operational flexibility against the same criteria. DOE identifies proactive planning, innovative tariffs, grid optimization, alternative financing, supply-chain and workforce development, on-site generation and storage as possible planning levers. Those categories are options to assess, not a recommendation for one project design.
| Evaluation axis | Questions for the project team |
|---|---|
| Firm capacity and reliability | What load can be served continuously, under which contingencies, and with what testing or maintenance limits? |
| Time to service | What is the earliest dependable energization date, including studies, equipment orders, construction and commissioning? |
| Total delivered cost | What are energy, capacity, fuel, maintenance, financing and interconnection-upgrade costs, and which party bears each one? |
| Flexibility | Can the load ramp, pause, shift or curtail without violating service-level, equipment or contractual requirements? |
| Emissions and resources | What are the direct and grid emissions, fuel implications and water or other resource impacts under normal and emergency operation? |
| Delivery and operating risk | Are permits, fuel, transformers, switchgear, batteries, controls, skilled labor and replacement parts available on the required schedule? |
On-site generation
On-site generation can reduce dependence on a constrained network or provide a bridge while upgrades are built, but it introduces fuel, emissions, permitting, maintenance and operational obligations. Model whether it is firm capacity, emergency-only backup or a resource that can run during defined grid conditions. Do not count nameplate capacity as dependable service until fuel supply, maintenance outages, controls and environmental approvals are established.
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Storage can shift demand, support ramping and reduce a site’s grid peak for a defined duration. Its value depends on power rating, usable energy, recharge opportunity, degradation, safety requirements and the number of consecutive events it must cover. Treat storage as a specific flexibility service rather than an unlimited substitute for firm generation or network capacity.
Flexible operations and tariffs
Some workloads can be scheduled, paused or moved geographically; others cannot. Identify the latency, data-transfer, security and service-level limits before offering curtailment. Ask the utility whether an innovative tariff or managed-load arrangement changes the cost or timing of service, and model the operational revenue or penalty terms rather than assuming flexibility is free.
Align the project schedule with infrastructure lead times
Use one integrated schedule owned jointly by development, engineering, procurement, utility-relations, finance and permitting teams. A practical sequence is:
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- Secure site control and define the envelope. Record the ultimate land, cooling, water, fuel, substation and generation requirements before selecting a final phase boundary.
- Issue a preliminary load package. Provide lower, base and higher cases, phase dates, peak and annual demand, reliability requirements and known equipment assumptions to the utility.
- Launch studies and permitting. Track interconnection, transmission, distribution, environmental, air, water, fuel-storage and building approvals as separate critical paths.
- Reserve long-lead equipment. Coordinate transformers, switchgear, protection systems, generators, storage and controls with the study results and the phased energization plan.
- Set commissioning gates. Do not release a building or equipment wave until the corresponding service, protection, fuel, controls and testing milestones are contractually and technically achievable.
- Reconcile the model at every gate. Replace estimates with purchase orders, utility study outputs and tested performance, then decide whether to advance, defer or redesign the next phase.
The schedule should show a latest decision date for each irreversible commitment. If the higher case requires a larger substation but the utility cannot confirm it by that date, the team needs a documented fallback rather than an unexamined assumption.
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Create a power-demand control board with named decision owners. A useful cadence is monthly during design and procurement, then at each equipment-order, utility-study and commissioning milestone. Maintain a single version-controlled model and an assumptions log that records the previous value, new value, reason for change, affected scenario and approver.
Track a compact set of indicators:
- Forecast peak demand by phase versus contracted and physically available capacity.
- Annual energy by scenario and the assumptions driving the difference.
- Interconnection-study status, upgrade scope, cost estimate and required-in-service date.
- Orders and delivery dates for critical electrical and generation equipment.
- Actual commissioning load, utilization and cooling performance versus the model.
- Remaining schedule float before each utility or permitting milestone becomes critical.
Define escalation thresholds in advance. A missed accelerator shipment, a material change in rack density, a utility finding that adds network work or a cooling result outside the design envelope should trigger a scenario review, not an informal spreadsheet edit.
Common planning failures and their fixes
Using a national forecast as a site commitment
Failure: Treating a U.S. or global percentage as proof that a particular location will receive the required power.
Fix: Use national figures to frame uncertainty, then rely on site-specific load cases, utility studies and enforceable milestones.
Reporting only nameplate megawatts
Failure: Giving the utility an ultimate IT number without coincidence, cooling, phase or annual-energy information.
Fix: Submit peak, hourly or block energy, commissioning stages and the assumptions that produce each value.
Waiting for final equipment selections
Failure: Delaying interconnection until procurement is complete.
Fix: Start with bounded scenarios and update the study case as equipment matures; the utility can then identify long-lead upgrades sooner.
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Counting flexibility without proving it
Failure: Treating storage, backup generation or curtailment as firm capacity without duration, fuel, maintenance, permitting or workload constraints.
Fix: Assign each resource a tested operating limit, availability assumption and contractual obligation, then count only the service it can reliably deliver.
Ignoring cost allocation
Failure: Comparing energy prices while omitting network upgrades, deposits, extensions and construction risk.
Fix: Put every grid and on-site cost in a delivered-power comparison and identify who pays, when payment is due and what happens if the project is delayed.
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Advance a design only when its required service is credible in the base case and survivable in the higher case. If the higher case needs infrastructure that cannot be delivered on schedule, preserve optionality: phase the campus, reserve land and electrical pathways, negotiate staged service, redesign the workload mix or procure qualified flexibility. The objective is not to predict one perfect number. It is to make uncertainty visible early enough that the developer, utility and regulators can still change the outcome.
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