Justin Starreveld

Mathematical optimisation under uncertainty with applications to hydrogen deployment in the Netherlands

This project is part of the broader “HyChain” research project, which investigates the deployment of hydrogen in the Netherlands. Hydrogen is a versatile energy carrier that can also be utilised as an industrial feedstock, and it may offer a viable path towards achieving a low-carbon economy. The Netherlands, as one of Europe’s largest hydrogen consumers and producers, is of particular interest due to its high demand, extensive natural gas infrastructure, and access to offshore wind resources. However, there are still many open questions regarding the deployment of hydrogen in the Netherlands.

Mathematical optimisation provides a systematic framework for answering such questions by modelling variables, objectives, and constraints in a transparent and quantitative manner. However, its application to real-world problems is complicated by uncertainty. This project focuses on two major types of uncertainty: parameter uncertainty, which arises when input data (such as costs or demand) cannot be predicted with certainty, and model uncertainty, which occurs when the mathematical formulation does not fully represent the real-world system.