A stochastic energy-system optimization model

ADDRESSING UNCERTAINTY IN LONG-TERM ENERGY-SYSTEM OPTIMIZATION MODELS

In order to analyze the ongoing transitions in the energy sector energy system optimization models have been widely used. Based on a set of projections of critical input parameters (e.g., investment costs, renewable generation, demand levels, etc.), along with other model assumptions, a planning model provides a least-cost solution for the energy system planning problem at hand. However, our inability to predict the future introduces uncertainties that could affect the optimality of planning model outcomes. By taking into account multiple scenarios for the future, we can minimize for the expected system cost. As such, we are able to reach more robust planning model outcomes in light of these uncertainties.

Competences gained at VITO

Being able to do a PhD-project in collaboration with VITO has provided me with technical expertise that often is only accessible in academic circles to a limited extent. Furthermore, it has taught me to persevere in looking for practical and pragmatic solutions.

My added value

As a PhD candidate you have access to highlevel research in various fields of study. As such, during the past four years I have developed a broad knowledge about the multifaceted energy sector. Furthermore, doing a PhD stimulates you to constantly look for improvements to existing
methods and being able to present my work at international conferences helped improve my communication skills.

After finishing the PhD I would like to work in an environment that highly values a strong team effort, while still providing individual challenges.”

Tim Mertens