E.ON\u2019s job is to keep the lights on. As one of Europe\u2019s largest energy companies, it operates a 1.6-million-kilometer energy network to serve 47 million customers with electricity and gas across 17 European countries. E.ON\u00a0 powers homes, hospitals, factories, transit and other critical infrastructure essential to 21st-century life. And that job is only getting more complicated.<\/p>\n
As E.ON supports Europe\u2019s transition to renewable energy, the demands on the grid become increasingly complex. The old ways of distributing energy were predictable. Given a big power plant and a steady supply of fuel, it was not too difficult to know how much it would cost to generate a megawatt of electricity tomorrow or a year from now. As demand changed during a heat wave or a cold snap, it was relatively straightforward to ramp production up and down.<\/p>\n
Now power comes from smaller, more dynamic sources, including solar and wind. At the same time, electric vehicles and intelligent systems in homes are dramatically changing consumption patterns, and more sectors are becoming electrified, such as mobility and heating. E.ON, responsible for providing power 24×7 year round, has to prepare well in advance to account for complex dynamic changes in both supply and demand. The company is now exploring quantum computing, a tool for conquering complexity, as a solution to this problem.<\/p>\n
\u201cWe are becoming a digital company,\u201d said Dr. Giorgio Cortiana, Head of Data & AI, Energy Intelligence at E.ON. \u201cData technology will be essential to help us master the complexity of these systems.\u201d<\/p>\n
One large piece of this effort boils down to a pricing problem.<\/p>\n
\u201cWe need to procure power before customers ask for it,\u201d said Dr. Piergiacomo Sabino, Quantitative Risk Expert at E.ON Energy Markets.<\/p>\n
E.ON\u2019s contracts require the company to provide energy to customers at a fixed price, even though consumption rates and delivery costs go up and down. Often there will be some mismatch between the amount of energy bought in advance and the actual demand. So different players in the market insure each other against those risks\u2014buying and selling energy derivatives and keeping the lights on.<\/p>\n
On E.ON\u2019s trading floor, experts like Dr. Sabino work to efficiently price those derivatives. They use Monte Carlo simulations for this task\u2014a way of predicting outcomes to uncertain events using today\u2019s computing technology. These methods account for volatility from weather, usage patterns and other factors. But even the world\u2019s largest supercomputers struggle with these kinds of problems.<\/p>\n
\u201cThis requires us to be smart and forward-looking, years in advance,\u201d said Dr. Cortiana. \u201cClimate change and black swan events must be part of our model. The ultimate goal is to provide energy affordability to our customers.\u201d<\/p>\n
During a recent energy crisis that led to dramatic spikes in prices across Europe, E.ON was able to protect customers and keep price increases under control due to this planning. If E.ON hadn’t handled this crisis correctly, customers could have been left in the dark.
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