The residential built environment in the Netherlands is on the verge of a transition of its thermal system. The Climate Agreement has suggested that municipalities will have to play a leading role in transitioning their neighborhoods' currently natural gas-driven heating systems towards sustainable alternatives. But changing the thermal systems of these neighborhoods will have consequences for the gas transmission system operator: Gasunie. Currently, no model captures this transition from the perspective of municipalities as key instigators while studying its implications on a transmission system operator. Therefore, this thesis presents a data-driven agent-based model representing the Dutch built environment consisting of municipalities, neighborhoods and energy sources to study the effect of municipal decisions in this transition on Gasunie's infrastructure. A novel municipal decision-making framework is designed that hypothesizes various factors contributing to municipal decisions in this transition. Aggregating peak gas demand to the level of Metering and Regulation stations in Gasunie's network captures the emergent behavior of interest from an infrastructural point of view. Simulation results show that the decisions of municipalities matter for the regionally required capacity in Gasunie's infrastructure, depending on the regional built environment characteristics, national transition goal, unfolding scenario, and municipal strategies. But the limited availability of renewable gas is a significant model driver and limits municipalities in what they can decide. It can be concluded that insight in the supply-side availability of the renewable gasses for the built environment in combination with multi-stakeholder coordination with the national policymaker and municipalities on the thermal transition can contribute to unraveling the uncertain character of this system and its implications for Gasunie's infrastructure. The agent-based model can expose the formulated theory of municipal decision-making and its effect on Gasunie's infrastructure while exploring and discovering what-if scenarios of interest for Gasunie and other stakeholders. It can potentially be used as a decision-support or debate starting tool by the involved stakeholders to show how their interests, characteristics, and decisions shape the change of this thermal system towards its sustainable future.

Gasunie Transport Services (GTS) is the operator of the natural gas transmission network in the Netherlands. This network is an entry-exit system where entry and exit capacities can be booked by parties called shippers. Variations in usage lead to an enormous number of possible entry-exit combinations. GTS must be able to accommodate all realistically possible gas transport scenarios that result from these entry-exit combinations. In principle, hydraulic testing of all these scenarios is required to see if the current network is optimally sized for this task. However, calculating all scenarios is extremely time consuming, so a smaller set of severe scenarios that also covers the less severe ones, is needed to represent the complete set.

Reduction of the complete set of transport scenarios is a mathematically challenging task. The current method to reduce the number of these scenarios is workable and probably meets the requirements of day-to-day planning calculations at GTS. This method makes use of the so-called end point representation, which describes transport scenarios by their capacities on entry and exit points only, while e.g. the flow pattern is unknown. The distance function for the current reduction method measures the difference between scenarios by comparing the capacities on end points, where the end points are correlated by their respective transport distances.

A new representation is introduced in this report: the flow representation. This representation makes use of the flow patterns that emerge from balanced combinations of entry and exit capacities. A flow pattern follows from an entry-exit combination by determining its minimum associated transport load. Compared to the end point representation, the flow representation is more intricate to obtain (more calculations are required to get flow patterns), but the result is a more accurate representation in terms of the transport physics of the network. The pay-off is that the distance function for the flow representation can be a lot simpler, e.g. a weighted norm which approximates the transport effort. It also turns out to be more adaptable. For example the diameter, pressure drop and other network information can easily be included in this weighted norm.

In this report both representations are compared. However, from the experiments no final conclusion can be given for which representation has a better performance. Future studies, e.g. involving hydraulic calculations, are recommended to conclude this matter.