AI infrastructure / power and cooling

What does a 100 MW AI data centre actually require?

AI may feel like software, but it runs inside physical buildings filled with computers. Those computers need a continuous supply of electricity. Almost all of that electricity becomes heat, which must be removed. A “100 MW data centre” therefore needs more than 100 MW from the grid, hundreds of high-power racks, industrial cooling equipment and enough backup power to survive an interruption.

01 / Computer load
100 MW
02 / Full building
120 MW in our middle case
03 / Electricity per year
946.1 GWh at 90% use

ConclusionA 100 MW computer load needs about 120 MW for the full building in our middle case. With planning headroom, the grid connection rises to about 138 MW.

01

What does “100 MW” mean?

A megawatt measures power at one moment. One hundred megawatts is the amount of electrical power used by the computers in this example.

The number usually refers to the information technology load: servers, processors, memory, storage and networking. It does not include all the equipment that keeps those computers running. Pumps move cooling water. Fans move air. Electrical equipment changes voltage and converts power. Lights, controls and security equipment also consume electricity.

This article follows the power from the grid to the computers, then follows the heat back out of the building. The central question is whether the electricity connection, cooling equipment and backup supply can support the promised computer load.

This matters because data-centre electricity use is growing quickly. The International Energy Agency estimates that data centres used 415 terawatt-hours (TWh) in 2024 and could use about 945 TWh in 2030. It also estimates that grid problems could delay around 20% of planned projects.[1]

The main test

Do not start with the building size or the number of processors. Start with the electricity the utility can deliver, the date it can arrive, and the heat that must leave the building every second.

02

How does 100 MW become a 138 MW grid request?

Data centres use a measure called power usage effectiveness, or PUE. It divides all electricity entering the building by the electricity used by the computers. A perfect building would have a PUE of 1.00, but real cooling and electrical equipment need power of their own.

In our middle example, PUE is 1.20. A 100 MW computer load therefore needs 120 MW for the full building. We then add 15% planning headroom for growth, operating limits and design uncertainty. That gives a grid request of about 138 MW.

StepCalculationResult
ComputersGiven design target100 MW
Full building100 MW × PUE 1.20120 MW
Grid planning figure120 MW × 1.15138 MW

The 15% headroom is our assumption, not a rule. The utility and electrical designer must set the real figure. The important point is that a 100 MW computer plan cannot be connected to a 100 MW supply.

03

How many high-power racks does that represent?

NVIDIA states that one GB200 NVL72 rack can use about 120 kW at full load. Each rack contains 18 compute nodes and 72 Blackwell graphics processors.[2]

Dividing 100,000 kW by 120 kW gives 833.3. We round up to 834 rack equivalents. This does not mean every real 100 MW data centre will use exactly 834 identical racks. It gives us a physical reference for the amount of equipment, electrical distribution and cooling involved.

ItemReference amountWhat the design must provide
AI racks834 at 120 kW eachPower, network connections, liquid cooling and service access.
Full building120 MW in the middle caseTransformers, switchgear, pumps, fans, controls and other support equipment.
Grid request138 MW with our headroomA firm utility offer, delivery date and agreed backup arrangement.

04

How much electricity does the building use in a year?

Power tells us the demand at one moment. Energy tells us how much power was used over time. One megawatt-hour, written MWh, means using one megawatt for one hour.

Annual energy = computer load × PUE × 8,760 hours × average use.

We assume the computers average 90% of their full load across the year. The table shows how much the cooling and electrical design changes the result.

PUEFull-building powerAnnual electricityCost at €100/MWh
1.10110 MW867.2 GWh€86.7M
1.20120 MW946.1 GWh€94.6M
1.40140 MW1,103.8 GWh€110.4M

The middle case uses about 946.1 GWh per year. At the example price of €100/MWh, that costs about €94.6M each year. Reducing PUE from 1.40 to 1.10 saves about 236.5 GWh, or €23.7 million at the same price.

The electricity price is a sensitivity, not a quoted tariff. Connection charges, taxes, demand charges and hedging would need a separate commercial model.

Download the full calculation

05

Where does the heat go?

Nearly all the electricity used by the computers becomes heat. A 100 MW computer load therefore creates roughly 100 MW of heat that must be moved from the chips to the outdoor air.

NVIDIA’s reference rack needs about 120 kW of cooling capacity and uses direct liquid cooling.[3] Water can carry much more heat than air, which is why modern AI racks use liquid close to the chips.

If water warms by 10°C while carrying away 100 MW, the basic heat equation gives a flow of about 2,388.9 litres per second. A real building divides this flow between many closed pipes, pumps and coolant distribution units.

ASHRAE reports that warm-water designs without chillers can approach PUE 1.10 and use very little cooling water in suitable climates.[4] The Open Compute Project recommends delivering coolant at 30°C or warmer as a durable design target.[5] Local weather still decides whether dry coolers can reject the heat throughout the year.

What the cooling design must state

Record how much heat goes into liquid, the water temperatures, the pump power, the hottest outdoor condition, the water treatment plan and what happens after a leak or failed pump.

06

What happens when the grid supply stops?

Computers cannot wait several minutes for a generator to start. Batteries or another fast supply must carry the building during the changeover or give the computers enough time to shut down safely.

At 120 MW, five minutes of full-building power equals 10 MWh of delivered energy. Our model assumes 90% discharge efficiency and uses only 80% of the battery capacity. That raises the installed battery to about 13.9 MWh.

Five minutes is only a bridge. The design still needs to say what happens after ten milliseconds, ten seconds, five minutes and four hours. It must also explain how the batteries recharge after an event and what happens when one part of the backup supply is unavailable.

07

What must be proven before construction?

A site is ready for detailed design only when the computer plan, grid supply, cooling equipment and backup sequence agree with one another. These are the minimum records we would ask to see.

QuestionEvidence required
What will the computers draw?Rack list, expected use, growth plan and power limits.
What will the utility deliver?Signed capacity, connection design, delivery date and expansion terms.
Can the building distribute the power?Electrical diagram, transformer and switchgear ratings, losses and protection study.
Can the building remove the heat?A complete heat calculation for the hottest weather and failed equipment.
What happens during an outage?Battery, generator or alternate-supply sequence with fuel and recharge requirements.
Can the owner afford to run it?Electricity, grid, cooling, water, maintenance and equipment-replacement costs.

If one of these answers is still an estimate with no owner or delivery date, the site is not ready for a 100 MW commitment.

08

Sources and assumptions

Sources were checked on 15 July 2026. The 100 MW computer load, 90% average use, PUE cases, 15% grid headroom, 10°C water-temperature rise, five-minute bridge and electricity prices are Lyon Industries assumptions. They are examples for testing the design, not measured data from a real building. The CSV contains the unrounded results.

  1. 1. IEA / Energy and AI / Executive summary / 2025

    Global electricity demand and the estimate for projects delayed by grid constraints.

  2. 2. NVIDIA / GB200 NVL72 power-budget documentation

    Rack power, compute-node count and processor count.

  3. 3. NVIDIA / GB200 NVL72 Open Compute Project design / 2024

    Liquid-cooling equipment and 120 kW rack cooling capacity.

  4. 4. ASHRAE / AI Data Center Energy Performance Framework

    PUE comparison and warm-water cooling guidance.

  5. 5. Open Compute Project / 30°C Coolant / Revision 1.0

    Industry guidance for coolant temperature delivered to AI equipment.