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.


  • Aleksander Grochowicz, Koen van Greevenbroek, Fred Espen Benth, Marianne Zeyringer :
    Intersecting near-optimal spaces: European power systems with more resilience to weather variability
    Energy Economics 2023 ARKIV / DOI
  • Desen Kirli, Johannes Hampp, Koen van Greevenbroek, Rebecca Grant, Matin Mahmood, Maximilian Parzen et al.:
    PyPSA meets Africa: Developing an open source electricity network model of the African continent
    IEEE (Institute of Electrical and Electronics Engineers) 2021 ARKIV / DOI
  • Koen van Greevenbroek, Jonathan Jedwab :
    A new structure for difference matrices over abelian p-groups
    Walter de Gruyter (De Gruyter) 2019 DOI
  • Koen van Greevenbroek :
    Design flexibility in energy systems planning: near-optimal feasible spaces
    2023
  • Koen van Greevenbroek, Aleksander Grochowicz, Marianne Zeyringer, Josef Noll, Oskar Vågerö :
    Vi treng uavhengig forsking, ikkje drøymetenking om kjernekraft
    Aftenposten (morgenutg. : trykt utg.) 26. June 2023 FULLTEKST
  • Koen van Greevenbroek, Marianne Zeyringer, Josef Noll, Aleksander Grochowicz, Oskar Vågerö :
    Kjernekraft er ikkje naudsynt for Noreg. Det vil heller ikkje lønna seg.
    Aftenposten (morgenutg. : trykt utg.) 07. June 2023 FULLTEKST
  • Koen van Greevenbroek :
    Does Norway need wind power?
    2023
  • Koen van Greevenbroek :
    Enabling agency: trade-offs between regional and European design flexibility in renewable energy systems
    2023
  • Koen van Greevenbroek :
    Matte møter miljø: modellering av vindkraft i Noreg
    2023
  • Koen van Greevenbroek, Aleksander Grochowicz, Hannah C. Bloomfield :
    Identifying Weather Stress Events from Power System Optimisation Outputs
    2023
  • Koen van Greevenbroek :
    Treng Noreg vindkraft?
    2023
  • Aleksander Grochowicz, Koen van Greevenbroek, Fred Espen Benth, Marianne Zeyringer :
    Intersecting Near-Optimal Spaces for Policy Information
    2023
  • Aleksander Grochowicz, Koen van Greevenbroek, Hannah C. Bloomfield :
    Identifying weather stress events from power system optimisation outputs
    2023
  • Koen van Greevenbroek, Aleksander Grochowicz :
    Effect of different weather years on policymakers’ decision space
    2022
  • Aleksander Grochowicz, Koen van Greevenbroek, Fred Espen Benth, Marianne Zeyringer :
    Intersecting near-optimal spaces for robust energy systems
    2022
  • Koen van Greevenbroek :
    Intersecting near-optimal feasible spaces: robust energy system designs over multiple decades of weather data
    2022
  • Koen van Greevenbroek, Lars-Stephan Klein :
    Opportunities for thermal energy storage in Longyearbyen
    Universitetssenteret på Svalbard 2021 FULLTEKST / ARKIV
  • Koen van Greevenbroek, Chiara Bordin, Sambeet Mishra :
    Flexible time aggregation for energy systems modelling
    Energy Informatics 2021 ARKIV / DOI
  • Koen van Greevenbroek :
    Averaging curves under the dynamic time warping distance
    2020 FULLTEKST

  • The 50 latest publications is shown on this page. See all publications in Cristin here →


    Research interests

    Keywords: energy systems modelling, energy infrastructure planning, the green transition, renewable energy systems, European integration, mathematical modelling and optimisation, design space and near-optimal solutions, effect of climate and weather on renewable energy systems.

    My research is about mapping out what our energy system could look like by 2050, at which time we aim to have reduced greenhouse gas emissions to net zero. What kinds of plans are technologically feasible and not too expensive? To answer these questions I use large mathematical optimisation models to gain the best possible overview of the solution space.

    It turns out that the solution space is quite large. While traditional energy research has focussed much on cost-optimal solutions, the search for near-optimal solutions shows that we have many choices and possibilities. Some technologies such as on- and off-shore wind power can easily be exchanged to some extent, and there are many sources of flexibility (transmission, storage, reserve capacity) enabling a high penetration of variable renewables.

    A particular area I work in is how to take climate change and variations in weather into account when planning renewables-based energy systems, and how to develop maximum robustness to extreme weather. (See doi.org/jcgm)

    Another project touches on regional interests, and how energy infrastructure decisions in our region can affect the rest of the system. For example, how could (low of) investments in renewable technologies in continental Europe affect the Nordic agenda and choices?

    I care about open research (open data, open code and open results); it contributes to better collaboration and more trustworthy conclusions. See also my Github profile (github.com/koen-vg)

    Teaching

    • Spring 2021: tutor for INF-1101 - Data Structures and Algorithms.
    • Autumn 2021: tutor for INF-3210 - Green Computing.
    • Spring 2022: tutor for INF-1101 - Data Structures and Algorithms.
    • Spring 2023: development of course material and lectures in INF-1101 - Data Structures and Algorithms.

    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