Data Centers Set to Surge: Power Demand Could Hit 12% of U.S. Grid—A Staggering 173% Increase from Today!

The Role of Cooling in Data Center Operations

Cooling systems are essential for maintaining optimal operating temperatures in servers, which generate significant heat. Failure to manage cooling effectively can result in overheating, equipment failure, and downtime, all compromising a data center’s ability to meet service level agreements (SLAs). SLAs typically require 99.99% uptime, or “four nines,” which translates to 52.6 minutes of allowable downtime annually.

Cooling Energy Demand by the Numbers

From the DOE report (see below)

• The current U.S. electricity use by data centers (2023)?is 176 TWh (4.4% of total consumption).
• Projected use by 2028: Between 325 TWh and 580 TWh (6.7% to 12% of total consumption).
• Cooling’s share of energy use: 30% to 70%, depending on the climate, technology, and facility design.

Data is king, and it will also account for most sector-specific energy growth over the next few years. But let's examine some more relatable, more granular numbers.

Data centers in the United States exhibit a wide range of power consumption levels, influenced by size, function, and technological infrastructure. Here's an overview:

• Small to Mid-Sized Data Centers?typically consume power from a few kilowatts (kW) to several hundred kW. For instance, a data center with a 1 megawatt (MW) capacity would have an IT load of approximately 1,000 kW.
• Larger Data Centers:?Facilities with higher power densities may consume power exceeding 10 megawatts (MW). Some hyperscale data centers, designed to support large-scale operations, can consume 100 MW or more.

Note: power consumption is not solely determined by the data center's size but also by factors such as the efficiency of the equipment, cooling systems, and the specific applications being supported. Advancements in energy-efficient technologies and best practices in data center management continue to play a crucial role in optimizing power usage across varying-sized facilities.

For a typical 1 MW data center:

• Cooling energy demand: 300–700 kW.
• Annual cooling energy cost ($0.07/kWh): $183,960 to $429,240.

Why the Range: 30% vs. 70%

The percentage of energy used for cooling varies based on several factors:

1. Climate: not the environmental climate but the region
2. Technology: how new is the plant and how well was the infrastructure built?
3. Facility Design: Modern or leading edge newer tech makes a difference

The percentage of energy used for cooling varies based on several factors:

1. Climate: Cooler Climates: Data centers in regions like the Pacific Northwest can use free-air cooling for much of the year, reducing reliance on mechanical HVAC systems. Facilities in these climates often fall toward the lower end of the range (~30%). Warmer Climates: Facilities in hotter or more humid areas, such as the southern U.S., need robust cooling systems that consume significant energy, often closer to 70% of total consumption.
2. Technology: Advanced Cooling Solutions: Implementations such as liquid cooling and AI-driven optimizations significantly enhance efficiency by directly targeting heat sources and dynamically adjusting cooling needs. Facilities adopting these technologies may achieve a cooling energy share closer to 30%. Traditional Systems: Older, air-based cooling systems are less efficient and often require more energy, pushing facilities toward the higher end of the range.
3. Facility Design: Optimized Layouts: Newer data centers incorporate innovative designs, such as hot and cold aisle containment, to improve airflow and reduce cooling energy needs. Legacy Designs: Older facilities, built without energy efficiency in mind, often suffer from inefficient airflow and higher cooling requirements.
4. Vintaging Models: Emerging Facilities: Hyperscale data centers and modern builds leverage state-of-the-art systems designed for sustainability and scalability, minimizing cooling energy consumption.

? ??Older Facilities:?Legacy data centers with aging infrastructure often lack efficiency upgrades, leading to disproportionate cooling energy use.Just so you know, understanding these factors can help you assess the state of your data center and identify opportunities for improvement.

The Maintenance Paradigm: Break-Fix vs. Preventative Maintenance

A key consideration in managing cooling systems is the maintenance strategy. Traditional break-fix maintenance—reacting to failures as they occur—is increasingly untenable in the high-stakes world of data centers. Instead, preventative maintenance offers a proactive approach that ensures reliability and efficiency.

The Pitfalls of Break-Fix Maintenance

• Unpredictable Costs: Reacting to failures leads to unplanned expenses and disrupts budgeting.
• Increased Downtime: Failures can result in extended outages, jeopardizing SLAs.
• Wear and Tear: Systems under strain fail faster, shortening equipment lifespan.

The Benefits of Preventative Maintenance

• Consistent Performance: Regular inspections and optimizations keep systems running smoothly.
• Cost Predictability: Planned maintenance reduces the financial impact of emergency repairs.
• Efficiency Gains: Proactively identifying and resolving issues, such as refrigerant leaks, can improve energy efficiency by 5–15%.

Redundancy and Neglect-Oriented Wear

While critical for reliability, redundant systems can become liabilities if not actively managed. Idle components that rarely operate may degrade over time due to neglect, compromising their effectiveness when needed. A preventative approach ensures that redundant systems are tested and maintained regularly.

Friendly Note: Redundancy is a safety net—it’s only effective if it’s intact and ready to catch you.

Operational Impacts of Cooling Efficiency

1. Enhanced System Reliability

Reducing cooling energy demand by 5–15% alleviates strain on HVAC systems, leading to:

• Fewer breakdowns: Less wear and tear reduces repair frequency and costs.
• Improved uptime: Stable cooling ensures data centers meet stringent SLA requirements, avoiding penalties and reputational damage.

2. Sustainability Integration

Efficient cooling aligns with sustainability goals by lowering greenhouse gas emissions. This is particularly important as companies increasingly prioritize ESG (Environmental, Social, and Governance) metrics to attract investors and customers.

Friendly Note: Reliable cooling is good for your operations and a great story to share with stakeholders who value sustainability.

Cost Implications

Key Takeaway: Scaling Efficiency for Greater Impact

Optimizing cooling systems for a?100,000 sq ft data center delivers dual benefits: significant energy cost savings and reduced maintenance expenses. Here's the breakdown:

1. Energy Savings:
2. Maintenance Savings:

Combined Impact: When adequately managed and strategically deployed:

• Energy Savings: $230,000 to $1.6M annually, depending on cooling loads and efficiency improvements.
• Maintenance Savings: An estimated 10–20% reduction in maintenance costs, freeing up another $20,000 to $60,000 annually.

These savings, totaling $250,000 to $1.66M annually, can be reinvested in:

• Advanced cooling technologies, such as AI-driven systems or liquid cooling.
• Capacity expansion, allowing data centers to add servers without grid upgrades.
• Sustainability initiatives, meeting ESG goals and attracting environmentally conscious clients.

Friendly Note: Every dollar saved in operations can be invested in growth, innovation, or simply bolstering financial health.

Profitability Boost

Lower cooling costs enhance profitability by improving margins in a competitive market. Colocation providers, for example, charge clients based on kilowatt usage. Reduced operational costs allow for:

• Competitive pricing: Lower costs can be passed on to clients, attracting more business.
• Higher profit margins: Providers retain more revenue per kW, allowing reinvestment in advanced technologies.

Example: A colocation provider charging $120/kW/month could increase its profitability by $6–$18 per kW/month by 5–15% through cooling cost reductions.

Friendly Note: Cutting costs doesn’t mean cutting corners—it means making more intelligent decisions that benefit your business and customers.

Supporting Future Expansion - getting more from less

1. Maximizing Grid Resources

Building or upgrading power grid infrastructure is expensive and time-consuming. Demand-side reductions in cooling energy allow existing infrastructure to support more capacity, enabling data centers to expand without waiting for costly upgrades.

2. Accelerating Deployment

Reduced cooling energy needs enable:

• Faster addition of servers and services.
• Scalability for AI applications without disproportionate increases in operational costs.

Example: A hyperscale data center saving 15 MW through cooling efficiency could accommodate an additional 15,000 servers within the same energy budget.

Friendly Note: With smart cooling strategies, your growth doesn’t need to be constrained by infrastructure limitations.

Real-World Examples

1. AI-Driven Cooling Optimization: AI dynamically adjusts airflow, temperature, and humidity in real-time, maximizing efficiency.
2. Liquid Cooling for High-Density Servers: Direct cooling of components reduces reliance on traditional HVAC systems.
3. Free-Air Cooling: Leveraging cooler climates for significant energy savings. However, this is getting harder and harder since cheaper land and growth us pushing Data Center growth deep into the south.
4. Proactive Leak Management: Automated detection and analytics prevent refrigerant leaks, adding 5–15% in annual energy savings.

Staying ahead with the right technology makes your operations efficient and future-proof.

Prudence to Profit: Managing Growth While Controlling Costs

Growth at the top line is exciting, but true success lies in controlling the bottom line. Cooling efficiency is a cornerstone for achieving growth and cost control objectives.

Balancing Reliability with Cost Control

Delivering 99.99% uptime doesn’t have to mean skyrocketing costs. Proactive maintenance, investment in efficient cooling technologies, and data-driven operations allow data centers to:

• Meet SLA commitments consistently.
• Control operational expenses without compromising service quality.

Enabling Sustainable and Strategic Growth

Every dollar saved through cooling efficiency can be reinvested into:

• Expanding server capacity without additional grid dependencies.
• Developing innovative services tailored to customer needs.
• Enhancing sustainability initiatives to attract eco-conscious clients.

Grocery Refrigeration: Reliability and Consistency Are Key

Like data centers, grocery stores have had to deliver reliability and consistency to meet operational demands and customer expectations. While SLAs measure data?centers with 99.99% uptime, grocery refrigeration systems require equivalent reliability to ensure food safety, compliance with regulatory standards, and preservation of perishable goods. Even a brief failure in refrigeration systems can result in:

• Product Loss: Spoiled inventory leads to direct financial losses and dissatisfied customers.
• Compliance Failures: Breaches of food safety standards can incur fines and reputational damage.
• Customer Trust Issues: Frequent system failures erode customer confidence in the store's ability to deliver high-quality products.

Achieving this level of reliability necessitates a strategic approach to refrigeration system design, energy efficiency, and maintenance—paralleling the same principles applied in data center cooling systems.

10 Key Attributes for Data Centers to Track and Manage for Improved Awareness and Efficiency - a series of results from lessons learned in Grocery

1. Refrigerant Leak Rates
2. Automatic Leak Detection Systems (ALDs)
3. BMS Anomaly Detection
4. Power Usage Effectiveness (PUE)
5. Cooling Energy Demand
6. Temperature and Humidity Trends
7. Redundant System Utilization
8. Energy Output and Carbon Footprint
9. Preventative Maintenance Metrics
10. Anomaly Alerts in Real-Time Operations

Advanced analytics platforms (like Bueno Analytics) detect and alert users in real time about irregular energy use, cooling inefficiencies, and system faults. These alerts allow immediate intervention, reducing operational risks and avoiding cascading failures.

How a Data Center Can Begin Reducing Energy Costs, Improving Performance, and Controlling Cooling Expenses

Cooling and energy costs are among the largest operational expenses for data centers, often comprising 30–70% of total energy use. To control this critical cost center while enhancing performance, data centers must adopt a proactive, strategic approach. Here are some real-world examples of success.

1. Conduct an Energy and Performance Assessment

Establishing a clear baseline is essential for understanding inefficiencies and areas for improvement:

• Energy Audit: Break down energy consumption into IT, cooling, and other auxiliary systems.
• Cooling System Performance Analysis: Identify inefficiencies in HVAC equipment, airflow management, and refrigerant usage.
• Operational Insights: Use Building Management Systems (BMS) and analytics platforms like Bueno to detect anomalies and trends in energy use.

Example:?Woolworths-Bueno Partnership?Woolworths, a leading grocery retailer, implemented?Bueno’s smart analytics?to monitor HVAC systems in its stores. Bueno's insights identified inefficiencies, enabling Woolworths to reduce refrigerant leaks and save energy across its locations. These same technologies can empower data centers to optimize their cooling systems and improve overall performance.

2. Invest in Advanced Monitoring and Detection Systems

Real-time energy and cooling performance visibility is vital for immediate corrective actions and long-term operational improvements. Advanced monitoring tools enable data centers to address inefficiencies proactively, reduce costs, and enhance reliability. Key approaches include:

• Automatic Leak Detection (ALD): Using solutions like those from AKO.com, data centers can identify refrigerant leaks early, minimizing energy waste, preventing costly equipment damage, and aligning with sustainability objectives.
• Energy Monitoring Solutions: Tools that track metrics such as Power Usage Effectiveness (PUE), cooling load ratios, and other KPIs help pinpoint areas of inefficiency and high energy consumption.
• Environmental Monitoring: Deploying temperature and humidity sensors ensures optimal conditions within server racks, reducing unnecessary cooling demand while protecting hardware.

Example: Walmart’s Cooling Transformation

Walmart applied advanced cooling technologies to address inefficiencies in its egg refrigeration systems. By leveraging sensors and monitoring tools, the company optimized storage temperatures, prevented product spoilage, and significantly reduced energy waste. This initiative enhanced product quality and shelf life and delivered substantial operational savings. Today, each shopping cart that rolls out of Walmart leaves the store 21% less costly than a competitor.

Relevance for Data Centers: Similarly, data centers can deploy ALDs, environmental sensors, and energy monitoring solutions to fine-tune cooling performance. By adopting this approach, facilities can achieve measurable savings, maintain equipment integrity, and ensure uptime consistency, all while contributing to broader sustainability goals.

3. Adopt Proactive Maintenance Practices

Transitioning from reactive break-fix models to preventative maintenance ensures reliability while controlling costs:

• Routine Equipment Inspections: Schedule regular checks to address potential issues like clogged filters, refrigerant leaks, or calibration errors.
• Redundancy Testing:?Actively manage and test backup systems to prevent neglect-oriented wear and ensure they’re ready when needed.
• Predictive Analytics: Use AI-powered platforms to forecast maintenance needs based on operational data, minimizing downtime and emergency repairs.

Example: Microsoft Data Center Maintenance Strategy Microsoft employs a robust preventative maintenance framework in its data centers, using predictive analytics to identify potential equipment failures before they occur. This approach has allowed Microsoft to maintain 99.99% uptime while reducing operational costs—a model that any data center can emulate for better performance and cost control.

4. Optimize Cooling Efficiency

Cooling efficiency directly impacts energy use and operational costs. Focus on strategies like:

• Upgrading to Advanced Cooling Systems: Consider liquid cooling, free-air cooling, or modular cooling designs tailored to facility needs. Check your compliance to make sure the equipment you are investing is allowed - chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.epa.gov/system/files/documents/2023-10/technology-transitions-final-rule-fact-sheet-2023.pdf
• Improving Airflow Management: Implement hot and cold aisle containment and improve rack layouts to reduce cooling loads.
• Leveraging Technology: Use AI and automation to dynamically adjust cooling systems based on real-time demand.

Example: Google’s Liquid Cooling Initiative Google deployed liquid cooling systems in its data centers to handle the high energy demands of AI workloads. This investment reduced energy use while maintaining optimal server performance. Data centers can adopt similar technologies to improve cooling efficiency and reduce energy costs.

5. Engage a Managed Service Provider

Cooling systems require constant monitoring, deep expertise, and the ability to respond quickly—capabilities that are often difficult to maintain solely in-house. This is where a managed service provider plays a pivotal role, offering:

1. Expertise in HVAC Optimization: Managed services specialize in identifying inefficiencies, implementing advanced solutions, and maintaining systems to ensure long-term performance and efficiency.
2. Round-the-Clock Monitoring and Proactive Action: Managed services provide continuous oversight with real-time anomaly alerts. Beyond monitoring, they tie maintenance directly to reliability and energy impact, ensuring that every intervention reduces downtime risk and optimizes energy consumption. They can analyze performance data, dispatch technicians when and where needed, and align maintenance activities with operational priorities.
3. Cost Savings: By outsourcing cooling system management, data centers can reduce operational overhead and focus their internal resources on core business functions like IT and service delivery.

Example: Woolworths as a Self-Managed Service Provider

Woolworths, a leading grocery retailer, exemplifies its ability to act as a managed service provider. By leveraging?Bueno’s advanced analytics platform, Woolworths monitors HVAC systems across its locations in real-time. This internal expertise allows them to review operational data accurately, identify inefficiencies, and dispatch technicians.

Through this approach, Woolworths ties maintenance directly to energy impact and equipment reliability, significantly reducing refrigerant leaks and operational costs. This model showcases how a company can internalize managed service capabilities, retaining control over critical infrastructure while driving measurable results. Woolworths has grown 30% over 7 years, driving energy spending down 37% during that period.

Relevance for Data Centers: Data centers can emulate this approach by investing in tools and capabilities that provide internal oversight. Whether leveraging in-house expertise or outsourcing to external managed service providers, the key is integrating real-time monitoring, data-driven insights, and proactive maintenance to enhance reliability and energy efficiency.

Getting Started: First Steps

1. Audit Your Systems: Work with a provider to analyze current energy use, cooling performance, and operational efficiency.
2. Set Benchmarks: Establish key performance indicators (KPIs) for energy use, maintenance schedules, and cost reductions.
3. Implement Monitoring Tools: Integrate systems like ALDs, BMS platforms, and real-time energy tracking.
4. Engage a Trusted Partner: Select a managed service provider experienced in data center cooling and energy optimization.

As the year ends and the new one begins, reports like those published by the DOE and Lawrence Livermore Labs teams (see references below) help us reflect on trends affecting our work and gauge our effectiveness. By reducing energy costs, improving cooling system performance, and engaging a managed service provider, data centers can transform a significant cost center into a source of operational control, reliability, and profitability. Let me know if you’d like further explanation of these examples or tools!

Cooling efficiency is a secret weapon for cutting costs and driving more competent, sustained growth.

References

1. U.S. Department of Energy (DOE), 2024 Report on U.S. Data Center Energy Use. Link to report.
2. Lawrence Berkeley National Laboratory, 2025 Data Center Energy Report. Link to report.
3. ARPA-E COOLERCHIPS Program. Link to program overview.
4. Industry insights from Data Center Knowledge, 2024. Link to article.

By embracing efficiency and sustainability, data centers can continue to thrive in an era of growing digital demand, ensuring that growth is not just fast but also smart and sustainable.