Emile Chappin

Transition modelling is an emerging but growing niche within the broader field of sustainability transitions research. The objective of this paper is to explore the characteristics of this niche in relation to a range of existing modelling approaches and literatures with which it shares commonalities or from which it could draw. We distil a number of key aspects we think a transitions model should be able to address, from a broadly acknowledged, empirical list of transition characteristics. We review some of the main strands in modelling of socio-technological change with regards to their ability to address these characteristics. These are: Eco-innovation literatures (energy-economy models and Integrated Assessment Models), evolutionary economics, complex systems models, computational social science simulations using agent based models, system dynamics models and socio-ecological systems models. The modelling approaches reviewed can address many of the features that differentiate sustainability transitions from other socio-economic dynamics or innovations. The most problematic features are the representation of qualitatively different system states and of the normative aspects of change. The comparison provides transition researchers with a starting point for their choice of a modelling approach, whose characteristics should correspond to the characteristics of the research question they face. A promising line of research is to develop innovative models of co-evolution of behaviours and technologies towards sustainability, involving change in the structure of the societal and technical systems.

To ensure sufficient investment in electricity generation capacity, mechanisms such as strategic reserves are being considered or already implemented. We analyze the effectiveness of a strategic reserve in the presence of a growing portfolio share of renewable energy sources (RES) with EMLab-Generation, an agent-based electricity market model. A strategic reserve can stabilize investment, but within limits. Uncertainty regarding future demand may cause the market to become instable, potentially leading to periods with very high electricity prices. In the presence of a large share of variable renewable energy sources, the reserve design should be adjusted or replaced by an alternative capacity mechanism.

ABSTRACT Heating behavior of households is key for reducing domestic energy demand and mitigating climate change. Recently, various technical devices have been developed, providing households with feedback on their heating behavior and supporting energy conservation behavior. The impact of such devices on overall energy consumption depends on (1) the impact of a device within a household, (2) the diffusion of devices to other households and the number of adopters, and (3) the diffusion of the induced behavioral change beyond these households. While the first two processes are currently established in assessments of sustainable household devices, we suggest that adding behavior diffusion is essential when assessing devices that explicitly target behavioral change. We therefore propose an assessment framework that includes all three processes. We implement this framework in an agent-based model by combining two existing simulation models to explore the effect of adding behavior diffusion. In three simulation experiments, we identify two mechanisms by which behavior diffusion (1) spreads the effect of such devices from adopters to non-adopters and (2) increases the average speed of behavioral change of households. From these results we conclude that behavior diffusion should be included in assessments of behavior-changing feedback devices.