To attain a better understanding of the energy transition we have applied Agent Based Modelling (ABM) to Integrated Assessment Modelling (IAM) in an abstract model with which we developed a proof of concept model of society’s response to a changing climate and energy system. Although there is no doubt that large scale neoclassical IAMs have provided key insights for business decisions and policy makers, we argue that there is a need for an approach that focuses on the role of heterogeneous agents. With our abstract ABM based on agents with heterogeneously spread discount rates we were able to give a new perspective on appropriate discount rates in the discussion between mitigation and adaption to climate change. We concluded that applying ABM to IAM yields good prospects to the further development of the implementation of society’s response to a changing environment and we propose future additions of the model to include adaptive behaviour.

Grid operators increasingly have to collaborate with other actors in order to realize smart grid innovations. For routine maintenance, grid operators typically acquire technologies in one-off transactions, but the innovative nature of smart grid projects may require more collaborate relationships. This paper studies how a transactional versus relational approach to governing smart grid innovation projects affects incentives for other actors to collaborate. We analyse 34 cases of smart grid innovation projects based on extensive archival data as well as interviews. We find that projects relying on relational governance are more likely to provide incentives for collaboration. Especially non-financial incentives such as reputational benefits and shared intellectual property rights are more likely to be found in projects relying on relational governance. Policy makers that wish to stimulate smart grid innovation projects should consider stimulating long-term relationships between grid operators and third parties, because such relationships are more likely to produce incentives for collaboration.