Revolutionary AI Weather Model Set to Transform Energy Trading Landscape

(Bloomberg) — At midnight every day in Bologna, Italy, rows of supercomputers inside a former tobacco factory start churning through millions of measurements to predict how the Earth’s weather will change. Six hours later, energy traders all over Europe rise and refresh their browsers to get the most updated outlook. Those mainframe-generated forecasts are often the biggest factor helping them make money by knowing where and when to move energy around the power grid — but a new model that runs on artificial intelligence is threatening to make them obsolete.

AI Weather Model Outperforms Traditional Methods

Unlike standard weather simulations, which only crunch information from satellites, sensors, and the like, the AI model from Europe’s intergovernmental forecasting center also feasts on historical data. Before its release late last month, the center tested the new method against its conventional model produced in Bologna and found the AI more accurately predicted temperature, precipitation, wind, and tropical cyclones, all with less computing energy.

Implications for Energy Traders

The model is poised to help traders in Europe and around the world make quicker moves in power and natural gas markets convulsed by extreme weather, geopolitics, and fluctuations in renewable sources. It’s a technology that could help minimize energy gluts and shortfalls in the world’s fastest-warming continent, as well as provide information key to deciding where wind and solar farms should be built.

“We can update our information set more often than we are used to” because of the advances in AI weather models, said Daniel Borup, chief executive officer of Danish trading firm InCommodities A/S. “That obviously leads to improvements in our predictions. It allows us to improve our job and distribute energy better.”

Enhanced Forecasting Capabilities

Like its traditional outlook, the European Centre for Medium-Range Weather Forecasts’ new system — the first AI model released by a major prediction center — estimates temperatures, wind speeds, and solar power two weeks in advance. But its improved accuracy means companies and policymakers can move faster on critical weather-related decisions, from canceling rail service to routing ships around storms and dispatching trucks to spread sand on icy roads, according to the center.

Managing Market Volatility

That degree of forecasting prowess could prove essential to managing market volatility. Earlier this month, robust generation from solar parks in Germany pushed power prices in several countries below zero. That was a reversal from earlier in the year, when a stretch of cloudy and windless weather known as a Dunkelflaute curbed renewable output and sent German electricity prices soaring.

A Shift in Weather Prediction

The upgrade is a radical shift away from the standard approach of using supercomputers to crunch millions of measurements to recreate a snapshot of the atmosphere’s physics, and then fast-forwarding the model to predict how the weather will change. Climate and weather datasets were already structured perfectly for AI and could use machine learning techniques developed for other scientific research approaches, Florian Pappenberger, the European center’s deputy director-general and lead forecaster, explained.

“Weather and climate is a Big Data problem,” he said. “We have huge amounts of data — humongous amounts — so it’s a perfect match.”

For more details, you can read the original article here.