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We’re exploring where quantum can make the largest impact in energy with E.ON. https://ibm.co/4fobSGB E.ON serves over 47 million customers across 17 countries everyday, powering infrastructure through electricity and gas—and that is no easy task. In years past, E.ON could reasonably predict costs and consumption to ensure these customers would always have the lights on. Now, with changes in technology, sudden weather, and the differing ways we use electricity each day, small variables to supply and demand of energy can drastically impact predictability of costs, resource allocation, and energy delivery. It is a complex problem E.ON faces, but that’s exactly what quantum computing aims to solve—problems with many variables that might take millennia to solve on classical supercomputers might have much more straightforward solutions using quantum computing algorithms. E.ON is exploring how quantum could help them plan for coming fluctuations and predict patterns years into the future, which ultimately lower costs for their customers and keep the lights on for all. Head over to the link above for the full case study and watch the film on https://lnkd.in/exCbDYQ6 for more.
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E.ON is exploring how quantum could help them plan for coming fluctuations and predict patterns years into the future... That would be virtually impossible, wouldn't it? The longer the time frame, the larger the chance of unexpected things to happen. I see factors that could be calculated/predicted as weather, supply (how much power that comes from different power sources), energy consumption, energy import/export, grid & infrastructure (now and under construction), increased use of grid batteries for load balancing and keeping the frequency in the grid at the right level. This seems more like a big data job to me. Is it this big data job the quantum computers are going to handle in the future? The wild factors that makes it virtually impossible to calculate or predict: Global pandemics: Just imagine the impact the corona virus outbreak had on businesses, and peoples economy. Many have not even remotely recovered from this yet. War: Take the war between Ukraine and Russia (which was easier to see coming (build up of a proxy war), yet still unexpected due to all the bad consequences of a war), which affected energy, politics, supply chain disruptions and created a tragic local disaster affecting millions of people.