Addressing the trends of digitalization, decentralization, democratization, and decarbonization, local peer-to-peer (P2P) markets have the potential to significantly accelerate decarbonization at the communal level. However, due to an increase in the number of energy consumers, such as electric vehicles or heat pumps, grid congestion can occur since actual low-voltage grids are not designed to transmit large loads. This paper introduces a novel concept for a platform to combine the advantages of P2P trading with the need for secure, automated low-voltage grid control, ensuring effective congestion management. Therefore, a dual local energy market has been developed, comprising a P2P energy market and a flexibility market with the latter ensures preventively managing congestion. Furthermore, mechanisms exist to provide curative, real-time congestion management. Additionally, the platform empowers prosumers, i.e. end users that produce and consume electrical energy, with intelligent market strategies to maximize their financial outcomes by participating in both markets. To provide a secure trading mechanism, the novel concept of Self-Sovereign-Identity is integrated into the platform. Tested in a smart grid laboratory at the University of Wuppertal, the platform provides financial gains for prosumers and effectively manages current- and voltage-related grid congestions.

Simulation based studies for operational energy system analysis play a significant role in evaluation of various new age technologies and concepts in the energy grid. Various modelling approaches already exist and in this original paper, four models representing these approaches are compared in two real-world hybrid energy system scenarios. The models, namely TransiEnt, µGRiDS, and OpSim (including pandaprosumer and mosaic) are classified into component-oriented or system-oriented approaches as deduced from the literature research. The methodology section describes their differences under standard conditions and the necessary parameterization for the purpose of creating a framework facilitating a closest possible comparison. A novel methodology for scenario generation is also explained. The results help to quantify primary differences in these approaches that are also identified in literature and qualify the influence of the accuracy of the models for application in a system-wide analysis. It is shown that a simplified model may be sufficient for the system-oriented approach especially when the objective is an optimization-based control or planning. However, from a field level operational point of view, the differences in the time series signify the importance of the component-oriented approaches.