AI in meteorology helps advance the energy sector
Thanks to AI, we can predict the weather more accurately, enabling the energy market to anticipate.
Published on April 29, 2025
Our DATA+ expert, Elcke Vels, explores AI, cyber security, and Dutch innovation. Her "What if..." column imagines bold scenarios beyond the norm.
The energy system of the future will mainly run on solar and wind energy. An additional disadvantage is that there are quite a few fluctuations in supply and demand on the power grid. Thanks to AI, we can predict the weather more accurately, allowing the energy market to anticipate better. Dutch startups Beyond Weather and Whiffle recently explained how they use AI in their weather forecasts at the Dutch AI Congress.
Our increasing use of renewable energy is good news for the energy transition. However, fluctuations in supply and demand make it more difficult for grid operators and energy companies to guarantee the security of electricity supply. The increasing variability on the grid also exacerbates the problem of grid congestion.
Accurate weather forecasts are therefore essential for the energy system. Currently, the weather is mainly predicted using mathematical equations that describe the atmosphere, such as Newton's laws. Observations, such as satellite data, weather balloons, and ground stations, also collect data to determine the current state of the atmosphere. However, a disadvantage is that this data is often scarce. As a result, forecasts are often inaccurate.
Remco Verzijlbergh, co-founder and CEO of Whiffle: “With AI, we can predict the weather much better, from the smallest clouds to local turbulence. We can map the weather in detail well in advance. And we can do this faster and faster.”
Hyperlocal forecasts
TU Delft spin-off Whiffle is developing a weather model that predicts the weather at a local level up to a hundred times more accurately than traditional models. According to Verzijlbergh, this is essential for the energy market. “An incorrect weather forecast can lead to unjustifiably high prices because energy markets react to predictions of extreme weather conditions that ultimately do not materialize. This leads to unnecessary preparations, for example, which drives up costs."
Verzijlbergh explains how his company uses AI for super-resolution, among other things. Scientists have developed algorithms that make it possible to go from a coarse, low-resolution image to a much more detailed image. You may be familiar with a technique whereby a pixelated photo is supplemented by AI to ultimately produce a sharp image. “This technology works in a similar way,” explains Verzijlbergh. “AI uses the available data to generate missing details and thus achieve a higher resolution. We use this technique to predict local wind speeds, for example.”
Whiffle's predictions can be applied in many areas. For example, fossil fuel-fired power plants need to be used less, which results in significant environmental benefits. The model also provides a detailed analysis of air quality. This is relevant for various sectors, from aviation and shipping to logistics and agriculture.
Long-term predictions
Beyond Weather, based in Amsterdam, specializes in long-term weather forecasts. Using AI, the startup can look more than two weeks ahead. Sem Vijverberg, CTO of the company: “We use AI, for example, to predict whether a severe winter is coming, so that parties active in the energy sector can prepare for this in good time.” The startup also assists with humanitarian efforts, especially in the severely affected Global South, by providing useful data that can help alleviate the effects of climate change.
At the end of last year, Beyond Weather raised €250,000 in a funding round from LUMO Labs, says Vijverberg. This amount is currently being used for the further development of their AI technology.
