Project summary: In light of the crucial challenges in decarbonizing the energy system, action is required by actors from the local to the global level. A recent report of the UK government argues in particular with respect to heat decarbonization for the importance of local action and strategies, which align with regional and national policies and planning. This requires coordination to ensure decarbonization strategies, which are often interlinked and dependent on actions on other levels, are aligned and mutually reinforcing. Local authorities might, for example, rely on funding from the central government to implement local plans while national strategies might depend on coordination or enforcement at the local level. Thus, it is vital for authorities to take into account other governmental scales and to develop a common understanding of decarbonization strategies.

This thesis is interested in supporting this process by developing a multi-scale heat sector model to explore scenario pathways spanning local to national scale. Scenario pathways are a well established way to shape thinking about the future energy system and inform policy-making. By providing pathways consistent across scales, this work intends to complement local and national models to provide the means to help shape coordination and common thinking on heat decarbonization strategies across scales. At the same time, it intends to shed light on the methodological aspects of multi-scale energy system optimization models, which are adaptable beyond the topical sphere of the thesis. It aims to address following research questions:

* How might local characteristics influence varying strategies and pathways for local area heat decarbonization within the national context?

* What is the influence of spatially explicit representations of regions and local areas in a national scale energy model on the generation of favorable energy futures?

In order to address these research questions, the project establishes and applies an innovative energy modeling approach. It addresses two specific challenges previously identified in current energy models. First, the approach aims to further knowledge on representing different scales in energy models by incorporating different ways of representing subnational areas within a nationwide energy system optimization model. Second, the work is strongly committed to tackle the challenge of transparency and reproducibility in energy modeling, fostering the notion of open science. It is based on an open-source modeling framework and aims to rely on open data to create an accessible and transparent model setup allowing for critical examination and facilitate further use of the work.