Innovative Verfahren der Komplexitätsreduktion zur Bestimmung des Netzausbaubedarfs

Due to the key energy policy of the energy transition ("Energiewende") in Germany, a huge amount of decentralized energy resources has been installed in the German power system, especially in distribution grids. To ensure a reliable energy supply and to increase the hosting capacity, German distribution grids hence need to be properly reinforced. An important part during the grid planning process is to estimate the future transport demands. Therefore, Worst-Case scenarios using simultaneity factors are used by distribution system operators in classical practice. However, by using simultaneity factors, the correlations of different types of customers and generators may not be precisely and correctly represented, which might lead to overestimation of required grid reinforcement.
In this Thesis, a case study for 500 low-voltage grid extensions is investigated. The accuracy and complexity of the innovative method is evaluated by comparing the resulting boundary values and the calculation demands of the different methods. The grid is then expanded according to the Worst-Case scenarios for all those 500 low-voltage grids, determined with the different methods. A further accuracy check is carried out based on the demand and the final plan of the grid reinforcement.