Socio-technical energy transitions: Modelling innovation diffusion through markets with heterogeneous boundedly rational agents

In recent years, thanks to new computational techniques like Agent-Based Models (ABM), modelling tools for socio-technical transitions to sustainable energy use have become more sophisticated than top-down techno-economic energy models (TEEMs) that are normally used to inform policy worldwide. TEEMs tend to ignore complex market structures, socio-political agents and dynamics, or co-evolutionary features of society and technology that are important for understanding how actors adopt new technologies during socio-technical energy transitions (STETs). However, even thought that several aspects of energy transitions like diffusion, demand, and techno-economic-drivenness are already incorporated in ABM of STETs, in our view, these existing models need to include robust and tested market simulation and decision making algorithms for modelling economic interactions among agents that are boundedly rational and heterogeneous. Thus, our aim is to present an ABM framework, merging two application programming interfaces (API), which can leverage the modelling of STETs by allowing computational agents embedded in social networks and dynamic market structures while adoption of new technologies occur. These APIs are: LARA (Lightweight Architecture for Boundedly Rational Agents) and JASA (Java Auction Simulator API). In our view, this integration can allow the robust and novel simulation of innovation diffusion embedded in markets. In order to demonstrate the feasibility of this approach, we present a simple example in which agents decide whether to adopt electrical mobility or not. In doing so, we embed the agents inside a market structure to allow their interaction with firms selling conventional and electrical cars. Among other results, the model output shows a typical s-shape curve diffusion pattern like the ones produced in Bass-Models. Directions for further research are discussed.