General Role: Technical coordination of the overall project
Specific technologies in charge of: Energy system modelling and optimisation
Main goal of the project: The overall goal of GISOptiTes is to assess the potentials of Large-Scale Thermal Energy Storage (LSTES)
to achieve high degree of decarbonization in the Swiss energy system by 2050. To achieve that goal a novel methodology is being developed enhancing synergies between top-down and bottom-up energy modelling optimization targeting energy policy.
Extended Summary: GISOptiTes will develop a methodology to increase synergies between top-down and bottom-up energy optimization tools with the goal of assessing the potentials of large-scale seasonal thermal energy storage (TES) in Switzerland. The top-down approach carried out with Energy Scope will be used to assess the transition path and the potentials of energy storage as well as electricity markets without considering the space domain and therefore independent on local conditions. To include the necessary local reality with the considerations of important aspects such as availability of different thermal energy storage technologies due to e.g., geography and regulations, the energy modelling will be coupled with GIS. The transition paths will be used to define market and cost conditions in which seasonal thermal energy storages could play a role. The bottom-up approach will be based on the optihood optimization framework coupled with GIS data. The foreseen bottom-up tool will allow to scan large regions and carry optimization cluster-by-cluster considering the geographical and regulations constrains to assess where seasonal TES will be possible and under which conditions will be economical. The project will deliver i) a GIS layer superimposing heat density and energy storage availability that will allow to assess the theoretical potentials/availability of different TES technologies in Switzerland (without
assessing whether are economically viable) ii) an open-source GIS-coupled energy optimization tool able to carry on optimizations on large regions targeting energy policy at large scale iii) a methodology to use synergies between top-down and bottom-up energy optimization to benefit from the best of both approaches and iv) recommendations on cost incentives necessary on a transitional path towards 2050 to fully deploy the optimum energy storage capacity by 2050. GISOptiTes is based on the most recent practices of open science and all models used and developed/extended will be open source via Git.
Duration: 2024-2026
Project Partners:
Web: https://www.aramis.admin.ch/Beteiligte/?ProjectID=54679
Funding Agency: Swiss Federal Office Of Energy (SFOE)
