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preferences . If your company had a net zero commitment , this would allow you to select the most sustainable source that was available and combine this with the software to better manage the other sources .
Combining that , emerging technologies like energy storage , using lithium-ion battery technology , offer the ability to store excess renewable power onsite . This can be used when the utility is strapped , charging more , or when there ’ s no sustainable power available . The fact that you can discharge those batteries is also interesting .
There are a lot of big developments happening with grid management and energy storage versus sustainability .
Can you share insights into the role of software platforms and end-to-end solutions in effectively deploying AI in data centres and ensuring responsible and efficient operations ?
During the design and procurement , software is used to specify a body carbon for many components . The procurement process is becoming more digital and the design process involves Digital Twins . Simulations can be run to see the effects on the operation side .
Software for complete power training allows you to examine transformers , switchgear , breakers , busway and monitor temperature . Operation software is critical and covers all power and IT room systems , including cooling systems .
Different types of AI can be used to adjust parameters like temperature and flow to the water , optimising efficiency . For example , when you are in a big data centre , hundreds of variables can be at play . It is hard for a human to change all the variables and see what the effect is , but a computer running AI can zero in on the most efficient operation .
Schneider Electric ’ s AI-Ready Data Centre Guide addresses critical intersections of AI and data centre infrastructure . Can you provide more details on the guidance it offers ?
AI is broken up into two distinct versions . There are the training models , the high-density , high capacity GPU models and the working models deployed as inference servers at the Edge or AGI closer to the loads . Depending on the required response speed , accuracy and comprehensiveness , these models are deployed close to the load . Predictive analytics in manufacturing and supply chain co-ordination are examples . Deploying these working models closer to users and applications is for more traditional data centres . They may run GPU accelerators but at much less than 100kW per rack .
Schneider offers solutions for all sizes of data centres , including pre-configured options like micro data centre solutions that can be rolled into place and selfconfigured by software . The larger projects are more custom and each one is different . The inference and working AI models use more standardised solutions familiar from Schneider .
Looking at future technologies for seamless AI integration , what does this mean for the future of data centre design ?
AI is going to be used for predicting the weather to assist workload migration , utility power delivery optimisation , cooling and predictive maintenance . AI has the capacity to look at the history of your data centre and what is being supplied through the grid . AI will impact various phases , dynamically adapting to sustainable power sources and supporting workload migration . It will be used in maintenance , predictive analytics and grid management .
How will the growth of AI impact data centre sustainability and what steps can CIOs take to minimise their environmental impact ?
CIOs need to understand and measure the environmental footprint , especially with distributed or campus-based data centres . Schneider ’ s free tool like the Life Cycle Carbon Footprint for Data Centres can assist in modelling and predicting carbon emissions . This tool allows you to model what your current data centre looks like and change parameters like IT refresh , the carbon intensity of your power and usage of generators .
It offers a multitude of options that can be changed and will give you a detailed output on scope one , scope two and scope three carbon of the data centre . It cannot be used for reporting , but you can use it to get an idea of where the carbon is being emitted for a specific +–. Hence this is a fantastic tool to use , whether you have the centre in existence , or you ’ re looking at the point one to get an idea of what it ’ s going to look like . �
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