C4: Methods for Assessing the Electrical Energy Supply with Special Consideration of New Mobility Concepts

A major impact of the energy transition is the stronger link between the energy sectors of electricity, mobility, and thermal energy. The mobility scenarios have a significant impact on the electrical energy supply. This project will analyze the impact on electrical grids based on mobility scenarios that are coordinated in a cluster, taking into account the increasing digitization of energy supply. It should be noted that, due to the technical restrictions, perhaps not all mobility scenarios can be implemented. In this subproject, the step from the scenario to a technical solution should be substantiated methodologically. The aim is to achieve this by applying the methods of "machine learning". Here, this method can be expanded or adapted for the preliminary planning of electrical supply systems. The use of machine learning for network planning is a new approach and has not yet been studied or implemented. The aim is not to create a detailed geographic layout for the laying of cables or overhead lines using machine learning, but to automatically design a "calculable" electrical network. This is the basis for a subsequent technical and economic assessment.
The particular challenge is that the previously mentioned mobility scenarios are not the only technical change expected to have a significant influence on the initial planning of the electrical energy supply system. These other changes include the development in the field of information and storage technology, the use of electrically operated heat pumps, and the further expansion of decentralized photovoltaic and wind power plants.

Doctoral Candidate: Sajjad Haider

First (Main-) Supervisor: Prof. Dr.-Ing. Peter Schegner

Second Supervisor: N.N.