Understanding citizen acceptance of the Energy Union, responsiveness to socioeconomic incentives for increased ownership, and prosumerism requires a multidisciplinary understanding of social systems and inclusiveness and robustness of policymaking depends on having empirically and theoretically grounded methodological tools to assess and adapt policy strategies. SMARTEES addresses this need by an iterative process: (1) integration of theories and methodologies of social innovation and agent-based socio-economic simulation in a comprehensive, flexible framework; (2) unprecedented data collection and integration in five trans-European case clusters in the domains of consumer-driven regenerative energy production, energy efficiency in buildings, low-carbon regional transport and consumer empowerment; (3) dynamic, multilevel agent-based models of successful innovation transfer; which ultimately lead to (4) a policy sandbox which allows a realistic prospective analysis of existing and future policy and market incentive scenarios. Each case cluster addresses a particular social innovation and consists of two reference cases and 4-5 followers. This enables SMARTEES to study the upscaling and replicability in different contexts. The policy sandbox is developed in a co-constructive process with users on the case level and in policymakers workshops on the European level. By doing this, SMARTEES contributes to robust and adaptive future policymaking, understanding of barriers and sources of resistance, the effects of the Energy Union on vulnerable consumer groups, genders and cultures. Furthermore, SMARTEES substantially drives advancement of social innovation and social simulation research by dynamic modelling of supply chains, companies, social groups, cities and neighbourhoods. In addition to making all modelling code and findings publically available, SMARTEES also ensures long term impact of the project by developing a commercialized version of the policy sandbox tool.

<< Objectives >>This project aims to spread knowledge about Samsø Energyacademy's technical and social concepts to residents and operators on islands in the Swedish archipelago and continue to promote capacity building of human capital.<< Implementation >>These activities will be done partly through digital workshops, a two-day visit to Samsø with study visits to various facilities, and introduce to the EU's facilities for development and democracy.<< Results >>The goal is to stimulate that sustainable environmental and energy projects and national or European collaborations with a grassroots perspective can be started in Swedish archipelagos.

CRETE VALLEY aims to create a Renewable Energy Valley 'Living Lab' (REV-Lab) in Crete. It is envisioned as a decentralised renewable energy system that combines leading-edge ICT technologies, interoperable and open digital solutions (including data sovereignty), social innovation processes, and sound business models that are easy to adopt. CRETE VALLEY will demonstrate a digitalised, distributed, renewable, low carbon landscape that is affordable for all and fully covers the local energy needs on an annual basis, utilizing multiple renewable energy carriers and leveraging energy storage technologies. The REV-Lab will integrate four Community Energy Labs (CELs) located in distinct sites across CRETE VALLEY, conceived as Innovation Hubs. An integrated social, technological & business approach will be deployed, providing: A Social Science Framework for REV-Labs & CELs, innovative multi-level governance models & social-driven mechanisms for involving citizens in the co-design, implementation and exploitation of RES; AI-based market segmentation algorithms, MCDA methods and consensus analysis for REV configuration; Interactive tools for REV planning (REV Readiness Assessment & computation, Augmented Reality applications, decision support tool); Energy Data Space compliant digital backbone for consumer and REV-level data-driven ‘activation’; P2P DLT/Blockchain digital marketplace for tokenised energy and non-energy assets valuation and reciprocal compensation; Data-driven operational analysis, advanced AI/ML tools and flexibility modelling services for optimal operation & resilience of the local energy grid; System-of-system Dig. Twin for multiple carrier grid management & operation; Data-driven services and apps for energy efficiency and activation performance management towards energy autonomy; Enabling RES technologies to increase the power production; REV Business Sandbox and blueprints for REV-Lab setup, upscaling and replication (including 4 Follower Communities).