Climate change is here, and it’s set to get much worse, experts say – and as a result, many industries have pledged to reduce their carbon footprints in the coming decades.
Enterprise, employees, governments, and consumers all demand it. Now, the recent jump in energy prices due mainly to the war in Ukraine, also emphasizes the need for development of c****, renewable forms of energy from freely available sources, like the sun and wind – as opposed to reliance on fossil fuels controlled by nation-states.
But going green is easier for some industries than for others,- and one area where it is likely to be a significant challenge is in data centers, which require huge amounts of electricity to cool off, in some cases, the millions of computers deployed.
Growing consumer demand to reduce carbon output, along with rules that regulators are likely to impose in the near future, require companies that run data centers to take immediate steps to go green. And artificial intelligence, machine learning, neural networks, and other related technologies can help enterprises of all kinds achieve that goal, without having to spend huge sums to accomplish it.
Data centers currently use about 1% of all electricity generated; but with our society’s growing reliance on data – further exacerbated by the sharp increase in remote working – that could rise to over 10% by 2030, even reaching nearly a third of all power used in some places.
While renewable energy is a good option for many, AI-related technologies need to be in the mix – both to reduce energy requirements in existing facilities, and to help with the design of new ones.
AI leads to data-driven decisions
By leveraging big data collected by a myriad of sensors that monitor energy usage, temperature and humidity, data usage at different times of the day, data loads on specific servers, and hundreds of other items, AI-based analytic systems can provide data center companies with specific recommendations that will significantly cut energy use. With those recommendations, companies can determine the most efficient, and inexpensive, ways to slash energy use, whether that energy comes from fossil fuels, sun, wind or water. This will help organizations meet regulations, or ultimately to develop plans that will enable the adoption of zero-carbon energy systems as inexpensively as possible.
A good example of this is a data center energy management solution installed by Huawei in its existing Linyi Big Data Center. According to the company, its AI-based solution reduced UPS energy consumption alone by 40%, “enjoying a system efficiency of 97 percent and a module efficiency of 97.5 percent.” In addition, the center implemented a special cooling system that uses deep learning to correlate IT loads, environmental variables, and equipment capabilities.
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Combining AI with renewable energy sources to stay ahead of regulations
Many data centers that are leading the way in cutting carbon output are combining AI with alternative sources of energy. Microsoft has been experimenting with underwater data centers, which use the force of water to power cooling systems, with the help of AI. Google, which as one of the world’s largest data brokers has numerous large data center and cloud installations, was able to cut some of its facility cooling bills by about 40%, thanks to systems designed by its DeepMind AI partner. And Amazon, which has data and cloud centers around the world, is well on its way to its goal of 100% renewable energy to power its facilities by 2025 – again, using AI and deep learning.
Indeed, these companies, along with dozens of other top cloud service providers, have committed themselves to completely power their installations with carbon-free energy by the end of 2030. As signatories to the Climate Neutral Data Centre Pact Self-Regulatory Initiative Policy, they pledge to “meet a high standard for energy efficiency,” in line with the European Green Deal.
Many see the steps of these big players as a bid to stave off regulation. But regulation is likely to come anyway. And if European governments do proceed with proposals and implement energy regulations for data centers, the US is likely to follow – just as some US states followed Europe on privacy regulations.
Those regulations will apply to all organizations, including those that don’t have the resources of an Amazon or a Google. These organizations – many of them enterprises – also need to get on board with the regulation – formal or otherwise – that will drive the standard of renewable energy use in data centers.
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Smart systems to cut and track energy use are often less expensive than complete overhauls of their energy infrastructure and are available now from companies specializing in AI and advanced data technology, making them a viable option for joining the green trend in data centers.
Harnessing AI in the building process
In addition to making existing data centers as energy efficient as possible, AI can help when an organization decides to build a new facility. Such AI systems can save on the additional energy use and materials for the construction process, further contributing to the environmental impact.
Whether they are constrained by budget, seeking a temporary solution before a complete switch to renewable energy, or wanting to maximize use of renewable forms of energy they have already adopted, companies can act now by adopting this technology. This will also put them ahead of likely regulations to reduce energy consumption and help meet customer demand for greener processes.
Why wait?
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