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Simulations, especially agent-based simulation, are able to facilitate the investigation of smart energy solutions and business models, and their impacts on the energy system and involved stakeholders. Technical details, alternatives, and multiple options for what-if scenarios influence simulation quality, but no methodology available to support the investigation. This paper proposes a method for identifying technical details of smart energy solutions in the energy system and identifying research gaps in the smart grid context with EV solutions as an example. The method includes the investigation of the state-of-the-art EV solutions by scoping review and the allocation of the scoping review results into the Smart Grid Architecture Model framework with three dimensions (Domains, Zones, and interoperability layers). The quantitative scoping review results in a total number of 240 references and 10 references match the criteria based on the qualitative scoping review. The results show that the most popular EV use case within the targeted scope is the V2G concept, and 6 out of the 10 references discuss the EVs’ potentials to work as energy storage. Seventeen features are identified by mapping the EV use cases (solutions and business models) into the three dimensions (domain, zone, and interoperability layers) of the SGAM framework. The process at the Zone layer is the most popularly covered (mentioned 64 times), and enterprise at the Zone layer and communication in the interoperability layer are the least covered (mentioned 4 times each).

energy informatics

Methodology for identifying technical details of smart energy solutions and research gaps in smart grid: an example of electric vehicles in the energy system