Data Center Energy Demand and Decarbonization: Pathways to Sustainability

With the US set to hit all-time highs in energy consumption in 2024 and 2025, global regulators and stakeholders continue to ramp up their demands that organizations “do the right thing” by the environment. And with that, businesses around the world are hard at work trying to find ways to satisfy expectations while also meeting energy demands. This is particularly true for one of the world’s fastest growing energy consumers: data centers. 

Accounting for up to 1.5% of global electricity consumption in 2022, with consumption set to jump  over 160% by 2030 – fueled by a boom in AI and cloud-based technology – the data center industry is quickly becoming one of the most talked about energy users. And with generative AI alone set to balloon from a $40 billion industry in 2022 to a $1.3 trillion industry by 2032, meeting energy demands while hitting sustainability targets will be no easy task for this already heavily scrutinized industry. 

Fortunately, while this is still an overwhelming prospect, thanks to innovations in data-driven energy intelligence, technology businesses are beginning to get a better grasp of their data center energy demands and consumption, and how to meet their sustainability expectations. More importantly, given the potential for electrically-powered assets – like data centers – to be zero carbon power thanks to renewables, businesses are looking at ways to lay the framework to achieve this exciting proposition in the medium-term. 

Related:Data Centers Lead the Charge Toward Net Zero Emissions

Here are a few considerations that businesses need to keep in mind as they try to solve this challenging energy conundrum. 

Understanding Their Energy Mix

To keep up with their energy demands, data centers rely on a diverse range of energy assets enabling them to take advantage of various resources in their immediate areas to balance cost and remain “online” without interruption. Due to how varied energy assets are, technology businesses often do not have the visibility into not only what future energy sources will provide, but how exactly each asset is feeding their organization today.

Therefore, before embarking on a full-fledged energy sourcing revamp, businesses need to take a step back and get a granular understanding of not just their current energy consumption needs and how they are being met, but also how they align with their stated decarbonization goals.  

Moreover, transmission capacity is often a bigger bottleneck than generation capacity. Transmission line approvals, particularly in the US, can take up to 10 years due to environmental, social, and regulatory hurdles. For example, even renewable projects with extensive investments may be delayed or canceled if transmission infrastructure cannot accommodate additional generation capacity. 

Related:Global Data Center Market Projected to Near $500 Billion by 2029

All too often, businesses jump into decarbonization projects without a full grasp of their actual energy consumption. By examining the bigger picture and adopting a scientific and data-centered approach to energy planning, data center companies can gain precise insights into their energy consumption, uncovering supply opportunities to optimize both sustainability and cost efficiency. This approach enables stakeholders to confidently make decisions that align with decarbonization goals while ensuring reliable operations. 

Incorporating Renewables 

As renewable energy has become one of the lowest cost sources of new energy, it isn’t surprising to see that renewables adoption at the commercial scale has also surged. In fact, over the last decade, commercial installations were a key driver of the solar industry’s 25% annual growth.

Offering significant cost savings and additional resilience and decarbonization boosts, technology companies have flooded the renewables market as a key energy source. Yet, while renewables are becoming more affordable, technology companies still face enormous pressure to make the right decisions when it comes to their renewable investments. Yes, renewables are a huge boon in reducing emissions. But with heavy upfront costs and increasingly stringent sustainability expectations, technology companies must ensure that their renewables investments provide maximum ROI.  

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What types of renewable projects are we going to invest in? How do we optimize our storage capacity?  Where will facilities be based to deliver the maximum overall benefits?  

Data center owners must also consider transmission congestion when siting facilities. Transmission congestion occurs when the grid lacks sufficient capacity to handle power flows, leading to bottlenecks. Nodal modeling allows businesses to simulate and identify transmission constraints at various points in the grid, helping them plan for the most cost-effective interconnection locations. 

One of the major challenges that technology businesses need to keep in mind when it comes to incorporating renewables is the mismatch between stable data center loads and intermittent renewable energy generation. Because renewable sources like wind and solar are variable, data centers need to be cognoscente of their renewables and storage mix so that they can meet their 24/7 energy demands without hiccups. 

Keeping One Eye on the Horizon

2050 – the year many organizations have set as their target net-zero date – will be here before we know it. And while optimizing existing assets and properly incorporating renewables will certainly help in this journey, it is only part of the battle. Regulators, in particular, are demanding more hard evidence that technology companies are making tangible sustainability strides.  

To meet ambitious internal and external climate goals, technology companies must have a strategic and measurable plan for their future data center energy consumption ecosystem. Fortunately, due to the surge in data science innovation, technology companies now have the ability to scientifically simulate their current and future energy needs and performance.

By tapping into data science and automation, companies can dynamically model their future needs and potential investments in real-time based on various scenarios to develop the scientific roadmap they need to demonstrably hit net-zero.