This overarching objective was pursued in four different lines of work in SMARTEES.
(1) Developing the SMARTEES social innovation case-study clusters. The focus of analysis in SMARTEES is an in-depth study of social energy innovations in ten carefully selected cases, grouped into five clusters of specific energy innovations. After the close collaboration with the cases had been established in the first reporting period, the activities in the second reporting period were mostly focussing on involving the cases in providing input to the other research activities. For each case cluster, a group of 4-5 follower cities/islands was established early in the project, among which a Premium follower city/island was identified. The contact to the follower cases was taken up again in the second reporting period as they were involved in the discussion of the policy scenarios, the development of the policy sandbox tool, and the model transfer activities. The case representatives were an important source of information also in the second reporting period, providing access to documents and datasets relevant for different WPs, providing input to the design of the simulation models and simulated scenarios and giving feedback on the policy sandbox tool. In discussion with the reference and follower cases, the concept for the workshops in the business model were developed.
(2) Studying social innovation and co-evolving socio-technical systems. One key strain of SMARTEES research is to build a framework model of social energy innovations across Europe from a multidisciplinary perspective. Based on the activities in the first reporting period in WPs 2 and 3, this work was developed further by refining the project ontology and common analysis framework in WP2, through a series of four project internal workshops, of which two were in the second reporting period (both virtual). The work of WP3 on models of social innovation in the energy sector which ended in the first reporting period was continued in the work of WP5 and WP6, who used the case analyses and the data from the interviews and simulations to explore policy relevance of the findings, the barriers and drivers of social innovations, the impact of social innovation on energy equality, and the impact of the simulation results on social innovation theory. All data collections of primary (mostly survey data in the second reporting period) and secondary data was coordinated by WP4.
(3) Social simulation – Modelling consumer and collective behaviour in energy transitions. The second main component of the second reporting period’s work was the extensive work for implementing seven independent social simulation models, based on the groundwork laid in the first reporting period. Models for Groningen, Aberdeen and Vitoria-Gasteiz were developed first as lead models for testing the architectures and possibilities of the models. Then models for Barcelona, el Hierro, Samsø, and Stockholm/Malmö were built based on these experiences. The models focussed on aspects so different as votes in a referendum, depending on the social dynamics prior to the referendum (Groningen), acceptance and support of social energy innovations by the local population (Vitoria-Gasteiz, Barcelona, el Hierro), the decision to connect to a heat network (Aberdeen and Samsø), and the decision to accept the renovation proposal of the dwelling in a socially challenged neighbourhood (Stockholm / Malmö). The heat network and dwelling renovation simulations also assess the economic effects of the activities on the population, especially with respect to energy poverty.
(4) Knowledge co-creation and development of a policy-scenario framework. The final work line in SMARTEES explored policy scenarios for alternative approaches. A series of two times five policy workshops with the cases were conducted (mostly virtual or as hybrid workshops) which explored potential alternative policy scenarios which were interesting for the local policy makers and feasible to test and implement in the ABMs. The policy scenarios were then tested in the simulation models and the most interesting of these were implemented in the online policy sandbox tool as a demonstration of what ABM could provide to policy making.
