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Data centers reduce avoidable energy use by managing two connected sources of demand: the heat created by IT equipment and the timing or location of flexible computing work. Operators can improve airflow, match cooling output to measured thermal conditions, and shift eligible workloads when service requirements permit. The right mix depends on each facility’s equipment, layout, climate, reliability needs, and workload commitments.
Why cooling and workload management belong together
Servers and other IT equipment consume electricity and release heat. Cooling systems then use additional electricity to keep equipment within acceptable operating conditions. Better IT efficiency and environmental controls can therefore reduce both the direct load and the mechanical and electrical demand needed to support it. The U.S. Department of Energy (DOE) treats IT efficiency, environmental conditions, air management, cooling and electrical systems, heat recovery, and benchmarking as connected parts of data-center design and operation in its 2024 Best Practices Guide.
The scale of cooling demand varies substantially by facility. The International Energy Agency (IEA), in its 2025 Energy and AI analysis, attributes about 7% of electricity use to cooling in efficient hyperscale data centers and more than 30% in less-efficient enterprise data centers. These are examples of different facility types, not a universal range for an individual site. Operators need their own metering to establish how much electricity cooling uses at their facility.
The broader electricity context is also growing: the IEA estimated data-center electricity use at 415 TWh in 2024, about 1.5% of global electricity consumption. Its Base Case projects about 945 TWh in 2030; that figure is a projection, not a measured outcome.
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Reduce heat and airflow losses before adding cooling
Cooling efficiency starts with the heat produced by IT equipment and the path air takes through the room. Poor airflow management can make cooling systems work harder than necessary or leave some equipment warmer than others. The DOE guide covers air management alongside cooling and electrical systems, but does not name one most-efficient layout for every data center. Rack arrangement, inlet temperatures, containment, fans, pumps, cooling plant, and reliability limits all affect what is appropriate.
What operators should examine
- IT equipment and operating conditions: Identify avoidable IT energy use and confirm that environmental settings suit the equipment and facility requirements.
- Air path through the room: Review how air moves between cooling equipment and rack inlets, and look for mixing or circulation patterns that prevent cooled air from reaching equipment effectively.
- Cooling and electrical systems together: Consider fans, pumps, cooling plant, and electrical losses as parts of the same system rather than optimizing one component in isolation.
- Performance and risk: Track energy and thermal performance while maintaining safe operating conditions and the required reliability. A change that saves power but raises over-temperature risk is not an acceptable efficiency gain.
- Heat recovery: Evaluate whether recovered heat has a useful destination at the site; its value depends on local conditions and demand.
For design and operations, ASHRAE Standard 90.4-2022 provides a framework that includes mechanical load and electrical-loss components. Its fact sheet defines the maximum mechanical load component using cooling, fans, pumps, and heat-rejection equipment relative to data-center power, and allows credits for heat recovery and shared-space economizers. The stated scope is conditioned floor space above 20 W/ft² and IT equipment loads greater than 10 kW. Check the applicable edition, project scope, and local code adoption before relying on it for compliance decisions.
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Use thermal data to match cooling to actual conditions
Cooling controls can use thermal measurements to adapt equipment operation rather than relying only on fixed settings. A DOE profile of Vigilent describes wireless sensors and system hardware and software that monitor thermal conditions, show the effect of HVAC and air-handling unit (AHU) operation across a facility, and support adaptive cooling control and load balancing. The profile identifies AHUs and computer-room air conditioners (CRACs) as equipment the system can control. DOE describes the approach as something that “Can be used to monitor and control data center cooling in real time.”
The profile reports annual savings of more than 2.3 million kWh at California data-center sites using the technology, but the page does not state the year for that case-study figure. It is a historical example, not a current or typical benchmark, and should not be treated as a prediction for another facility. See the DOE cooling-management profile.
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In practice, controls are useful only when measurements, setpoints, and equipment behavior can be evaluated against site requirements. Operators should assess thermal conditions and energy use together and verify that adaptive changes preserve equipment operating limits and reliability.
Shift only workloads that can move
Workload management can reduce demand peaks, improve utilization, or move eligible work to a different time or location. It is not a blanket instruction to delay computing: user-facing services and jobs with strict service-level requirements may need to run immediately, while some batch processing or simulations may tolerate a defined delay.
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Carbon-aware scheduling is not automatically an energy reduction
Carbon-aware scheduling moves flexible computing toward hours or locations with lower forecast grid carbon intensity. A 2021 Google-authored paper documents one approach using day-ahead carbon-intensity forecasts and hourly capacity limits for temporally flexible jobs. Those limits preserve daily capacity and account for service and infrastructure constraints. This is an example of an operational method, not evidence that total compute energy falls or that the same system is deployed throughout the industry. The paper is available at arXiv.
Flexibility has operational and economic limits
The IEA 4E EDNA’s July 2026 review considers workload flexibility, supporting infrastructure, and additional flexibility assets. It distinguishes market-, grid-, and system-serving flexibility and notes that operational and economic barriers vary by data-center type. Scheduling is therefore useful only when workloads are permitted to move, systems can support the change, and the operating or commercial incentives make it worthwhile. See the IEA 4E EDNA publications.
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Compare options against facility and service constraints
Cooling projects and workload programs have different measures of success. A facility should assess its starting conditions rather than assume a technique will deliver the same result elsewhere.
Quick Recap
Cooling and airflow options
- Establish the facility’s actual cooling share and baseline thermal performance through site measurements.
- Account for retrofit or capital needs and compatibility with existing racks, controls, fans, pumps, and cooling equipment.
- Measure both electricity use and thermal outcomes, including reliability and over-temperature risk.
- Consider water use and heat rejection where relevant data is available.
- Keep the design specific to the facility; DOE cautions that its guide cannot identify one most-efficient design for every scenario.
Workload-management options
- Identify which jobs are genuinely delay-tolerant and specify permissible delay and completion windows.
- Protect service-level objectives and other commitments for workloads that cannot be shifted.
- Determine whether work can move across time, location, or both, and which electricity or carbon-intensity signals are available.
- Check infrastructure, operational, and contractual limits that constrain dispatch.
- Assess the desired outcome separately: peak reduction, utilization, energy use, or grid-carbon alignment are not interchangeable measures.
