Koen van Greevenbroek


PhD fellow

Job description

I am in a 4-year research position (2020-2024) leading to a PhD in computer science. My research is on energy systems modelling (see the research & education tab) with a focus on mathematical optimisation. The position also includes 25% teaching duties.


  • Kirli, Desen; Hampp, Johannes; van Greevenbroek, Koen; Grant, Rebecca; Mahmood, Matin; Parzen, Maximilian; Kiprakis, Aristides. PyPSA meets Africa: Developing an open source electricity network model of the African continent. IEEE 2021 ISBN 9781665419833.s doi: 10.1109/AFRICON51333.2021.
  • van Greevenbroek, Koen; Jedwab, Jonathan. A new structure for difference matrices over abelian p-groups. Walter de Gruyter (De Gruyter) 2019 ISBN 9783110642094. ISSN 1865-3707.s doi: 10.1515/9783110642094.
  • van Greevenbroek, Koen; Klein, Lars-Stephan. Opportunities for thermal energy storage in Longyearbyen. (fulltekst) 2021.
  • van Greevenbroek, Koen; Bordin, Chiara; Mishra, Sambeet. Flexible time aggregation for energy systems modelling. Energy Informatics 2021; Volum 4 (1). ISSN 2520-8942.s P3 - .s doi: 10.1186/s42162-021-00145-9.
  • van Greevenbroek, Koen. Averaging curves under the dynamic time warping distance. (fulltekst) 2020.
  • Look at all works in CRIStin →


    Research interests

    My research is in energy informatics, a broad field which is about smart, efficient energy systems and the transition to renewable energy. I have a background in optimisation and discrete mathematics.

    I focus on mathematical modelling and optimisation of renewable energy systems. What mix of technologies is needed in energy systems with zero carbon emissions? How flexible are economically optimal solutions? How sensitive are the energy systems of the future to changes in technology, costs, politics and other factors?

    A large share of solar and wind power leads to novel challenges in energy systems modelling, and requires a higher resolution in space and time. As a result, current models push the limits of our computing power. A central question in my research is how to get the best possible results with the computing power we have. Right now, I am investigating modelling individual components at different levels of detail.

    Finally, I am excited about recent developments in open energy system models and open energy data. At the moment I am working with PyPSA, and I value cooperation over isolated experiments. This way we can build a solid and effective platform for relevant research.

    My supervisor is Chiara Bordin.

    Teaching

    • Spring 2021: tutor for INF-1101 - Data Structures and Algorithms.
    • Autumn 2021: tutor for INF-3210 - Green Computing.

    Member of research group


    CV

    • 2020 - 2024: PhD in energy informatics, UiT The Arctic University of Norway
    • 2018 - 2020: Master's in mathematics, Universität Bonn, Germany
    • 2014 - 2017: Bachelor's in mathematics, Simon Fraser University, Canada

    REALF A 238

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