Informing deep GHG emission reduction strategies through integrated energy system modelling: development and demonstration of a national scale harmonized integrated modelling framework

In this PhD thesis we explore the Dutch energy transition towards carbon neutrality. For this, we enhance an integrated modelling framework which allows us to take into account sectoral integration, the effect of novel technologies, and the intricate temporal dynamics required to work with intermittent renewable energy sources. To contribute to this modelling framework we develop two integrated energy system models, which use harmonized optimization and simulation methodologies (IESA-Opt and IESA-Sim, respectively). Chapter 1 describes the linear programming behind IESA-Opt, while in chapter 2 we implement this model for the Dutch energy system, and in chapter 3 we measure the effect of enabling or disabling key modelling capabilities. The formulation behind the IESA-Sim model is presented in chapter 5. We also use this framework to identify optimal pathways to decarbonize the Dutch energy system, so after the first implementation in chapter 2 we performed a thorough analysis on the decarbonization of the industrial sector in chapter 4. Here, we produce 4 pathways around CCUS, bio-based, electrified and hydrogen based solutions and compare them against the optimal mix of solutions. One of the results of this analysis is the need for biogenic carbon capture and storage to achieve carbon neutrality. The last goal of this work is to provide insights to design better policies for the transition. For this, in chapter 5 we use a Pareto front provided by IESA-Opt and simulations from IESA-Sim to quantify the effectiveness and efficiency of different policies to reach the emission reduction targets.