On the basis of our models and data our simulations generate a condensed image of real systems to achieve that complex systems become understandable and can be manageably modeled and analysed.
Using self-developed simulation tools we model and optimise electricity and heat supply systems as well as mobility systems. Additive to our models we use existing software, for example to process geographical information and analyse electrical grid stability. The focus of our models lies on the technical simulation of energy systems while also considering ecological and economical aspects.
Linking the different energy sectors makes it possible to detect yet unused flexibility potential. The intersectoral perspective enables us to use different modelling approaches that for example link the sectors electricity-heat, electricity-gas, electricity-mobility by integrating CHP and Power-to-Heat, Power-to-Gas and electric mobility, respectively.
The levels of abstraction of our models range from locally limited energy systems (e.g. micro smart grids and off-grid systems) tocounties and communities connected to the integrated grid system up to national, European and global system analyses.
For model validation we use measured data, check for plausibility by simulating the actual state and compare our results to the results of other models. This ensures a differentiated and objective evaluation of our results as well as a constant improvement and quality control of our models.
In order to individually model a system we develop models of technical components that can be composed flexibly. Components can for example be energy producers, energy consumers or energy storages. Among the components are established components such as photovoltaic systems or CHP as well as innovative technologies such as power-to-gas systems. The level of detail is adapted to the model approach. The great strength of our models is the individual integration of the various technologies with the necessary level of detail.
Optimisation (Solution strategy)
On top of simulating energy systems we optimise them with respect to one or more objective criteria, for example to minimise costs and/or CO2 emissions. The result of this can be a well-adapted system setup, an optimal plant scheduling as well as an ideal operation management. For the optimisation we use suitable optimisation algorithms, methods and solvers. Depending on the size of the optimisation problem we use linear and non-linear optimisation methods. On the strength of our diverse optimisation approaches we provide the ideal solution strategy for various questions.
Together with our partners we have established a platform for software development to collaboratively work on energy system modelling. The source code of some of our models is as well released there. By using open source licenses we can share our models, get feedback and benefit from the know-how of a large community. By working in a network we achieve a global, resource efficient model development and validation.
Through using GIS software we can process and clip various geographical data to gain knowledge regarding spatially resolved information. Clipping different infrastructure data (electricity grids, power plants, industry) with population and weather data extends the knowledge of potentials and locational factors. A result of this are visually prepared, detailed maps which are easily comprehensible and can be utilised in common digital maps.
Our models can be provided with user-friendly graphical interfaces (web-based or local) making it easy for new users to utilise. Through this our partners are enabled to produce their own results for individual questions based on our models.