Modellgestützte Analyse eines an die deutsche Energiewirtschaft angepassten lokalen Energiemarktes mit integriertem Engpassmanagement

Description

The energy transition is making the energy system more decentralised and fragmented. Prosumers are installing distributed energy systems, such as charging infrastructure and photovoltaic systems, facing an inert electricity grid that is increasingly unable to integrate these systems. As a result, congestion management at the lower voltage levels of the grid is becoming increasingly important, complex and comprehensive. This results in high costs for the expansion of the electricity grids. These costs are also driving up grid tariffs, encouraging prosumers to increasingly rely on selfconsumption. This self-consumption reduces electricity costs without necessarily reducing the peak power and thus relieving the grid. This is a missed opportunity to incentivise prosumers to reduce the need for grid expansion by means of a synthesis of self-consumption models, dynamic tariffs, variable grid charges and the expansion of smart metering systems. Properly configured local markets could harness the flexibility of prosumers to allocate and dimension electricity grids efficiently. To demonstrate this, this thesis designs a local energy market based on peer-to-peer trading, which also allows for a more efficient allocation of electricity grids. Unlike comparable studies, this market is derived based on existing market processes and regulations. Model-based analyses show that this not only reduces electricity costs for prosumers but also creates additional targeted investment incentives for flexibility. Overall, integrated congestion management leads to a more efficient allocation of the electricity grid and thus to less need for expansion.