In line with its commitments to lower carbon emissions under the Paris Agreement and its own 2030 Climate & Energy Framework, the European Union (EU) has committed to increase the share of renewable energy use–around 15% in 2018–to be at least 32% by 2030. Achieving this will require a major reconfiguration of current energy systems in what could be seen as an example of a socio-technical transition or, more specifically, of an ‘energy transition’. The key driver of this transition will be the electrification of heating and mobility functions. However, owing to the intermittent nature of most renewable energy sources (RES), this will need to be accompanied by the increased decentralisation and digitalisation of electricity networks. Existing energy system modelling softwares can simulate the dynamics of many of these processes. Nevertheless, they generally do not adequately capture the social and ecological aspects of the technologies that will drive this transition. Accordingly, the report aims to identify ways that future modelling applications–such as the ENVIRO and QTDIAN modules to be developed within the current project–can be used to address this gap and what information, theories, frameworks and methodologies exist that can guide such processes. Following a brief introduction to the key concepts involved, Section 2 provides a summary of the current energy system at the global and EU scale, followed by a detailed investigation into the technologies most relevant to the transition towards the greater use of renewable energy. This includes all important energy supply, demand and storage technologies. Recognising that achieving a just and sustainable energy transition will also require changes within society itself, a selection of six key social trends relating to the energy transition are also discussed. Collectively, these trends suggest that addressing issues of social acceptance, democracy and justice are likely to greatly improve the success of transition processes. Section 3 outlines a number of frameworks and theories that can be used to conceptualise the social processes and processes of technological emergence likely to occur within broader energy transition processes. Firstly, the four main theoretical foundations for visualising transitions are identified as the Multi-Level Perspective (MLP), the Technological Innovation System (TIS), Strategic Niche Management (SNM) and Transition Management (TM). All four–and the MLP in particular–can be used to understand how structural changes occur in energy systems and how to guide sustainable energy transition processes. Two further approaches for quantifying the rates of technological progress and market impact for burgeoning technologies are also discussed. Together, it is hoped that this information can be used to conceptualise and predict the myriad potential transition pathways that are to be developed using the ENVIRO and QTDIAN modules. Lastly, section 4 presents a summary of six existing frameworks and approaches that have found use in the quantitative modelling of energy transitions. The first of these–the use of integrated assessment models (IAMs)–involves the integration of multiple existing quantitative models, is already widely employed to simulate transition scenarios at larger scales and is perhaps the most relevant to the current project. The remaining five model categories are a group of more abstract frameworks and approaches that attempt to model complex systems, behaviours and dynamics, often at finer levels of detail. This includes agent-based models (ABMs)–the most commonly used to date–as well as the broadly classified group of complex systems models, evolutionary economics models, socio-ecological systems models and system dynamics models. Collectively, the findings of the report act as the foundation for the development of the ENVIRO and QTDIAN modules that will allow social and ecological factors and impacts to be integrated into the energy system modelling platform of the SENTINEL project. It also serves to open doors to the continued integration of social and environmental factors into future energy system models by demonstrating the ways in which societal and technological trends can be integrated into energy system modelling projects.