University of Applied Sciences Ansbach

Master of Engineering in Smart Energy Systems

Driven by the energy transition, the energy industry is currently undergoing a major change. The share of renewable energy sources such as photovoltaics or wind power is growing steadily, allowing consumers to generate energy rather than only consuming it. The increasing decentralisation of plants and the increased volatility of energy production, e.g. due to changing solar radiation, make intelligent networking necessary. Only digitalisation will enable both the conversion to an economical and renewable energy system, securing supply in the long term.

For this, interdisciplinarily trained experts are needed who have profound expertise in the field of energy sciences and digital technologies as well as competencies for organisational implementation under economic, legal and ecological aspects.

To this end, students in the international and English-language Master's degree programme SES learn the different producer and consumer technologies in modern, decentralised energy grids. They deal in particular with the exchange of information between the individual participants and the associated transmission paths as well as the resulting interaction of the overall system. Knowledge from the field of artificial intelligence (AI) and optimisation is also taught, combined with the respective possibilities from the field of information and communication technology for secure and reliable data exchange. The aim is to sharpen the understanding of the individual generator and consumer technologies and, in particular, to impart knowledge and skills with regard to the optimal operation of an entire energy system.

Students thus acquire knowledge about the design, operation and optimisation of intelligent, decentralised energy systems through the application of innovative and digital technologies. The growing complexity and interconnection of the energy sectors makes SES graduates ideal specialists and managers not only in the field of energy production and marketing, but also in the real estate industry and building technology sector, the automotive industry or in energy-intensive industries (building materials, chemicals, glass, non-ferrous metals, paper and steel).

Example of an intelligently networked energy system:

Residential house with PV system, battery storage, heat pump and charging station for an electric car.

Winter morning, it is cold outside, but the sun is shining and the PV system is supplying electricity. The residents are at school or at work. The AI recognises the consistently sunny weather forecast and activates the washing machine. Since a severe frost is forecast for the coming night, the heat pump also runs to sufficiently charge the heat buffer. The battery storage is charged with surplus electricity.

In the evening, the family comes home and the electric car is connected. The increased energy demand expected by the AI due to light and other consumers in the house will greatly reduce the charge level of the battery storage, so that the charging process with own electricity is not released for the electric car. Since no trips are necessary for the next day in the home office, the AI also decides not to charge the car with grid electricity overnight, but waits until sufficient wind energy (weather forecast) is available the next day.

This sounds simple, but it is a highly complex task. Not every system consisting of individual energy generators, consumers and storage units is automatically "smart". Not only energy flows, but above all, information, forecasts and data must be exchanged. In addition, there must be an intelligent instance that translates this information and data into decisions and communicates these to the participants in real time or as a forecast or timetable. In the future, more and more of these highly complex energy systems will emerge as an important building block for the energy transition and a sustainable and regenerative energy supply.