Introducing: Prof. Dr. Simon Schramm - one of the founding professors of the ISES
Today in portrait: Prof. Dr. Simon Schramm
Simon Schramm joined the University of Applied Sciences Munich in 2014 as Professor of Renewable Energy and Energy Systems. In 2019, he co-founded the Research Institute for Sustainable Energy Systems (ISES). His research focuses on energy management, energy system modelling and power electronics. ⚡
❓ What motivated you to do your research?
I was appointed to Munich University of Applied Sciences by a central research centre in the field of high-performance electronics and energy technology of a major American corporation. During the 10 years of my professional career, research was part of my daily business. For me, the opportunity to do research was a key criterion for coming to the university. Working on new challenges, especially in the field of energy transition, and being able to make a real contribution is a key motivation for me.
❓ What innovations can this promote?
We are working on improving the applicability of AI in the field of energy consumption analyses. In another group, we are working on new planning methods for the energy transition to improve the involvement of the population.
❓ What areas of application do you want to open up?
Our research is intended to make a contribution to the ‘energy transition project of the century’. Areas of application include energy saving, energy system planning and technical equipment for efficient and resource-saving grid integration. Taking energy saving as an example: we are currently researching the topic of non-intrusive load monitoring. This is an approach in which the energy consumption of complex building structures is analysed with little measurement technology and a lot of intelligence: Which consumer accounts for what proportion of energy consumption, and when? The approach has been around for some time, but there are major challenges in its implementation. The results found are used, among other things, to plan energy-saving measures in a targeted and data-based manner, even with limited human and financial resources.