{"id":46855,"date":"2024-07-27T22:45:00","date_gmt":"2024-07-27T22:45:00","guid":{"rendered":"https:\/\/greenschoolsgreenfuture.org\/?p=46855"},"modified":"2025-08-14T20:42:33","modified_gmt":"2025-08-14T20:42:33","slug":"ai-demand-puts-more-pressure-on-data-centers-energy-use","status":"publish","type":"post","link":"https:\/\/greenschoolsgreenfuture.org\/fr\/ai-demand-puts-more-pressure-on-data-centers-energy-use\/","title":{"rendered":"AI Demand Puts More Pressure on Data Centers\u2019 Energy Use"},"content":{"rendered":"
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*This article is republished from<\/em>\u00a0The Conversation\u00a0under a Creative Commons license. Read the\u00a0original article<\/a>.*<\/em><\/p>

Written by Ayse Coskun<\/span><\/a><\/strong><\/p>

Here\u2019s how to make it sustainable<\/p>

Unfortunately, efficiency alone is not going to solve the sustainability problem.<\/p>

The artificial intelligence boom has had such a profound effect on big tech companies that\u00a0their energy consumption<\/a>, and with it their carbon emissions,\u00a0have surged<\/a>.<\/p>

The spectacular success of large language models such as ChatGPT has helped fuel this growth in energy demand. At 2.9 watt-hours per ChatGPT request, AI queries require about\u00a010 times the electricity of traditional Google queries<\/a>, according to the Electric Power Research Institute, a nonprofit research firm. Emerging AI capabilities such as audio and video generation are likely to add to this energy demand.<\/p>

The energy needs of AI are shifting the calculus of energy companies. They\u2019re now exploring previously untenable options, such as\u00a0restarting a nuclear reactor<\/a>\u00a0at the Three Mile Island power plant that has been dormant since the\u00a0infamous disaster<\/a>\u00a0in 1979.<\/p>

Data centers have had continuous growth for decades, but the magnitude of growth in the still-young era of large language models has been exceptional. AI requires\u00a0a lot more computational and data storage resources<\/a>\u00a0than the pre-AI rate of data center growth could provide.<\/p>

AI and the grid<\/strong><\/h3>

Thanks to AI, the electrical grid \u2013 in many places already near its capacity or\u00a0prone to stability challenges<\/a>\u00a0\u2013 is experiencing more pressure than before. There is also a substantial lag between computing growth and grid growth. Data centers take one to two years to build, while adding new power to the grid\u00a0requires over four years<\/a>.<\/p>

As a recent report from the Electric Power Research Institute lays out, just 15 states\u00a0contain 80% of the data centers in the U.S.<\/a>\u00a0Some states \u2013 such as Virginia, home to\u00a0Data Center Alley<\/a>\u00a0\u2013 astonishingly have over 25% of their electricity consumed by data centers. There are similar trends of clustered data center growth in other parts of the world.<\/p>

Along with the need to add more power generation to sustain this growth, nearly all countries have decarbonization goals. This means they are striving to integrate\u00a0more renewable energy sources into the grid<\/a>. Renewables such as wind and solar are intermittent: The wind doesn\u2019t always blow and the sun doesn\u2019t always shine. The\u00a0dearth of cheap, green and scalable energy storage<\/a> means the grid faces an even bigger problem matching supply with demand.<\/p>

Additional challenges to data center growth include\u00a0increasing use of water cooling for efficiency<\/a>, which strains limited fresh water sources. As a result, some communities are\u00a0pushing back<\/a>\u00a0against new data center investments.<\/p>

Better tech<\/strong><\/h3>

There are several ways the industry is addressing this energy crisis. First, computing hardware has gotten\u00a0substantially more energy efficient over the years<\/a>\u00a0in terms of the operations executed per watt consumed. Data centers\u2019 power use efficiency, a metric that shows the ratio of power consumed for computing versus for cooling and other infrastructure, has been reduced to\u00a01.5 on average<\/a>, and even to an impressive 1.2 in advanced facilities. New data centers have more efficient cooling by using water cooling and external cool air when it\u2019s available.<\/p>

Unfortunately, efficiency alone is not going to solve the sustainability problem. In fact,\u00a0Jevons paradox<\/a>\u00a0points to how efficiency may result in an\u00a0increase of energy consumption<\/a>\u00a0in the longer run. In addition, hardware efficiency gains have\u00a0slowed down substantially<\/a>, as the industry has hit the limits of chip technology scaling.<\/p>

To continue improving efficiency, researchers are designing\u00a0specialized hardware such as accelerators<\/a>, new integration technologies such as\u00a03D chips<\/a>, and new\u00a0chip cooling<\/a>\u00a0techniques.<\/p>

Similarly, researchers are increasingly studying and developing\u00a0data center cooling technologies<\/a>. The Electric Power Research Institute report endorses\u00a0new cooling methods<\/a>, such as air-assisted liquid cooling and immersion cooling. While liquid cooling has already made its way into data centers, only a\u00a0few new data centers<\/a>\u00a0have implemented the still-in-development immersion cooling.<\/p>

Data center operators can convert their facilities to be a flexible load on the grid.\u00a0Academia<\/a>\u00a0and\u00a0industry<\/a>\u00a0have provided early examples of data center demand response, where data centers regulate their power depending on power grid needs. For example, they can schedule certain computing tasks for off-peak hours.<\/p>

Implementing broader and larger scale flexibility in power consumption requires innovation in hardware, software and grid-data center coordination. Especially for AI, there is much room to develop new strategies to tune data centers\u2019 computational loads and therefore energy consumption. For example, data centers can scale back accuracy to reduce workloads when training AI models.<\/p>

Realizing this vision requires better modeling and forecasting. Data centers can try to better understand and predict their loads and conditions. It\u2019s also important to predict the grid load and growth.<\/p>

The Electric Power Research Institute\u2019s\u00a0load forecasting initiative<\/a>\u00a0involves activities to help with grid planning and operations. Comprehensive monitoring and intelligent analytics \u2013 possibly relying on AI \u2013 for both data centers and the grid are essential for accurate forecasting.<\/p>

On the edge<\/strong><\/h3>

The U.S. is at a critical juncture with the explosive growth of AI. It is immensely difficult to integrate hundreds of megawatts of electricity demand into already strained grids. It might be time to rethink how data centers use energy.<\/p>

One possibility is to sustainably build more edge data centers \u2013 smaller, widely distributed facilities \u2013 to bring computing to local communities. Edge data centers can also reliably add computing power to dense, urban regions without further stressing the grid. While these smaller centers currently make up 10% of data centers in the U.S., analysts project the market for smaller-scale edge data centers to grow by over\u00a020% in the next five years<\/a>.<\/p>

Along with converting data centers into flexible and controllable loads, innovating in the edge data center space may make AI\u2019s energy demands much more sustainable.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

As AI continues to advance and strain electric grids, it puts pressure on data centers to use energy more sustainably. Find out how.<\/p>","protected":false},"author":79,"featured_media":46863,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"give_campaign_id":0,"footnotes":""},"categories":[20],"tags":[],"class_list":["post-46855","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-articles"],"acf":[],"yoast_head":"\nAI Demand Puts More Pressure on Data Centers\u2019 Energy Use - Green Schools Green Future<\/title>\n<meta name=\"description\" content=\"As AI continues to advance and strain electric grids, it puts pressure on data centers to use energy more sustainably. 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