Peer-to-peer, community or collective self-consumption, and transactive energy markets offer new models for trading energy locally. Over the past five years, there has been significant growth in the amount of academic literature examining how these local energy markets might function. This systematic literature review of 139 peer-reviewed journal articles examines the market designs used in these energy trading models. A modified version of the Business Ecosystem Architecture Modelling framework is used to extract market model information from the literature, and to identify differences and similarities between the models. This paper examines how peer-to-peer, community self-consumption and transactive energy markets are described in current literature. It explores the similarities and differences between these markets in terms of participation, governance structure, topology, and design. This paper systematises peer-to-peer, community self-consumption and transactive energy market designs, identifying six archetypes. Finally, it identifies five evidence gaps which require future research before these markets could be widely adopted. These evidence gaps are the lack of: consideration of physical constraints; a holistic approach to market design and operation; consideration about how these market designs will scale; consideration of information security; and, consideration of market participant privacy.@en

The emergence of peer-to-peer, collective or community self-consumption, and transactive energy concepts gives rise to new configurations of business models for local energy trading among a variety of actors. Much attention has been paid in the academic literature to the transition of the underlying energy system with its macroeconomic market framework. However, fewer contributions focus on the microeconomic aspects of the broad set of involved actors. Even though specific case studies highlight single business models, a comprehensive analysis of emerging business models for the entire set of actors is missing. Following this research gap, this paper conducts a systematic literature review of 135 peer-reviewed journal articles to examine business models of actors operating in local energy markets. From 221 businesses in the reviewed literature, nine macro-actor categories are identified. For each type of market actor, a business model archetype is determined and characterised using the business model canvas. The key elements of each business model archetype are discussed, and areas are highlighted where further research is needed. Finally, this paper outlines the differences of business models for their presence in the three local energy market models. Focusing on the identified customers and partner relationships, this study highlights the key actors per market model and the character of the interactions between market participants.@en

The authors regret that there were developments in affiliations and funding acknowledgements during the time from initial submission to final acceptance which have not been reported correctly. Specifically, the affiliations of the co-authors R. Chitchyan, M. Montakhabi, M. Andoni, and I. Scott were not up to date. The corrected affiliations of all authors are as follows. Concerning funding acknowledgements, the information of M. Andoni, V. Robu, and I.J. Scott were not up to date. In addition to the provided information, the following to fundings should be acknowledged. Merlinda Andoni received funding from the EPSRC DecarbonISation PAThways for Cooling and Heating (DISPATCH) project (grant number EP/V042955/1) and the InnovateUK Responsive Flexibility (ReFLEX) project [ref: 104780]. Valentin Robu was supported by the project “TESTBED2: Testing and Evaluating Sophisticated information and communication Technologies for enaBling scalablE smart griD Deployment”, funded by the European Union Horizon2020 Marie Skłodowska-Curie Actions (MSCA) [Grant agreement number: 872172]. Ian Scott was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS. The authors would like to apologise for any inconvenience caused.@en