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Mathematician Sven Karbach deals with the financial risks surrounding renewable energy. 'What I do is called renewable energy finance. That may sound like a niche, but it touches on big questions: how to make sure we can invest in renewable energy, despite uncertainty about production and prices?'
Sven Karbach, foto: Melisa Can
Sven Karbach

Karbach works at the University of Amsterdam. After earning his PhD in stochastics at the Korteweg-de Vries Institute in Amsterdam, he did postdoctoral research in Hamburg. In 2023, he returned to Amsterdam, where he now works combining positions at the Informatics Institute, within the Computational Science Lab, and Korteweg-de Vries Institute as part of the cross-faculty program AI4Fintech. Today, he combines his background in mathematics and statistics with applications in the energy and financial sectors. More specifically, Karbach deals with the financial risks surrounding renewable energy.  

  

What does your project involve?   

Karbach's project (and PhD student Konstantinos Chatziandreou) revolves around developing an AI-driven system that can smartly deal with the uncertainty of renewable energy, such as solar and wind. Because weather is difficult to predict, especially in the long term, energy production is also uncertain. And that carries risks, especially if you want to buy or sell energy through contracts on the market.  

'We don't so much want to predict better - meteorologists already do that - but to better understand and manage the risks that come with uncertainty. We can't change the weather, but we can be smarter about it.'  The solution? Strategically placed batteries in the power grid that automatically charge, and discharge based on data. The system Karbach envisions combines weather forecasts with market information to make optimal decisions about energy storage and sales.   

'You don't want to put one smart person next to a battery deciding when to charge. You want a smart system that does that automatically, based on all available information. It's not just about forecasting, but about being wise about what you don't know,' he explains.    

  

Why did you apply for the Impact Call?  

For this ambitious project, Karbach depends on additional help and computing power. With funding from the Impact Call, he plans to hire students as research assistants as well as use powerful computers to train his models.   

'We don't just want to develop theory but really build a working system. You need programmers and a lot of computing power for that.' He also plans to connect with experts from both the energy sector and the world of AI to make the project as relevant and robust in practice as possible.   

'I see this grant as a way to build a proof of concept. Something working, with which I can apply for larger grants or even generate interest from industry.'

'I see this grant as a way to build a proof of concept. Something working, with which I can apply for larger grants or even generate interest from industry.'  

  

What do you hope for your project?  

 What drives Karbach is not just the academic challenge. He wants to contribute to a future where our energy system is resilient, fair and sustainable - despite the uncertainties of the weather. His project shows how abstract mathematics and practical technology can reinforce each other.   

'I hope this project inspires others to also bridge the gap between thinking and doing. And that people do see: with smart systems we can really make a difference.'  But first he wants to show that his approach works. The Impact Call helps him do that: 'It would be great if this grant could lay the foundation for something bigger – like a tech start-up that starts small and then grows fast.'