FURIESSCH - Future Swiss Electrical Infrastructure
The main research challenge of the WP2 is to build a realistic technical model of the Swiss energy system including the transmission systems, which model can be used for planning, operation, and economic evaluation of the system. This model must comprise: (i) location of renewable generation and the limited predictability of these sources; (ii) location of storage devices, both large scale, i.e. pumped hydro storage, and distributed devices; (iii) interconnections with regional grids; (iv) interconnections on the bulk power level, i.e. high voltage lines and gas pipelines; (v) possibility to interface it with models for market and other economic simulations.
This work involves the modelling of individual components, which requires interaction with other WPs and possibly other SCCER, but also the development of a general system framework taking into account different energy carriers. Furthermore, since the model will be of very high order and complexity, it should be formulated in such a way that large-scale optimization methods could be applied. In this way different optimization objectives could be used in the planning and operation of the system. The results from the optimization have to be robust.
The developed models should cover both slowly varying phenomena, i.e. time scale of minutes, but also faster phenomena, i.e. time scale of seconds. The models used for studying and analysing phenomena of different time scales will be different but with the same architecture. Another research challenge is the dynamics of a system with considerably lower inertia than the existing systems. Innovative geoinformation system will be used to identify locations for renewable generation and storage devices. The developed model, achieved with real data related to the system, is expected to be a powerful tool for optimizing the future Swiss energy system in terms of planning and operation.
- Kardoš J., Holt T. A. B., Fazio V., Fabietti L., Spazzini F. ., Schenk O. (2022) Massively Parallel Data Analytics for Smart Grid Applications, Sustainable Energy, Grids and Networks, 31:1-18. ISSN 2352-4677
- Holt T. A. B., Kardoš J., Fazio V., Fazio L., Spazzini F. ., Schenk O. (2021) High-Performance Data Analytics Techniques for Power Markets Simulation. SEST 2021. International Conference on Smart Energy Systems and Technologies 2021. Vaasa, Finland. September 6-8, 2021
- Kourounis D., Schenk O. (2020) Method to Accelerate the Processing of Multiperiod Optimal Power Flow Problems
- Kardoš J., Kourounis D., Schenk O. (2020) Parallel Structure Exploiting Interior Point Methods. Parallel Algorithms in Computational Science&Engineering - Parallelism as Enabling Technology in CSE Applications. Birkhauser, 1-30
- Kourounis D., Fuchs A., Schenk O. (2017) Toward the next generation of multiperiod optimal power flow solvers, IEEE Transactions on Power Systems, 33 (4):4005-4014. ISSN 0885-8950