Abstract
This thesis aims to act as a catalyst for research at the intersection of energy transition and industrial transformation by providing a modelling toolbox suited for the application to industrial energy systems. The modelling work in this thesis is based on mixed-integer linear programming. It uses a framework designed to
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optimise multi-energy systems at different scales for cost and emissions using hourly resolved data. It does so by deciding the installation, size, and operation of a set of energy conversion and storage technologies to supply specific energy demands. The modelling toolbox's contributions can be grouped into two categories: technology models compatible with the optimisation framework and methodological improvements. For the first category, this work presents a linear model of a monoethanolamine-based post-combustion carbon capture process that considers the effects of CO2 concentration, plant size, and part-load operation. Moreover, a gas turbine model was developed at different levels of detail to suit the user's needs and preferences. For the second category, a novel solution method for time-resolved energy-system optimisation problems was derived, called the time-hierarchical solution method. Besides the obvious advantage of saving computation time, the method's added value lies in its simplicity and suitability for energy systems with a high penetration of non-dispatchable renewable energy sources. Especially the latter is a feature that most solution methods are lacking. Furthermore, this thesis also presents a method to deal with large portfolios of existing wind turbines. While this is not required for greenfield designs, it is crucial when the existing infrastructure is considered and replacement decisions are optimised. This thesis also studied the role of hydrogen and carbon capture using two extensive case studies. Hydrogen was studied on a national level, and the effect of industrial hydrogen demands on the Dutch national energy system was assessed. It was found that the role of hydrogen as a storage medium for electricity decreases with increasing (industrial) demand. Beyond a certain tipping point, the cost of hydrogen increases due to increasingly costly system expansion. This finding puts the notion of cheap green hydrogen in the future - at least if produced nationally – into question. The role of carbon capture was studied for the decarbonisation of the steel industry in combination with process changes. In the long term, carbon capture will not be necessary but beneficial, nevertheless. In the short term, however, carbon capture can significantly boost the CO2 reduction at a cost that is compensated by the savings in costs of emitting CO2. The study also shows that the risk of technology lock-in can be mitigated if the system is properly designed with a forward-looking perspective. To summarise, this thesis provides (i) the technology models to simulate and optimise industrial energy systems, (ii) the methodologies to do so in a computationally efficient manner, (iii) exemplary case studies with a detailed description of the methodology as a guideline for other case studies, and (iv) insights into the role of hydrogen and carbon capture.
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