SCCER JA S&M – Joint Activity Scenario and Modeling

Source: Swiss Competence Centers for Energy Research (SCCER)

Partner: EPFL, ETHZ, PSI, UniBas, EMPA, UniGE

Duration: 2017 – 2020 (4 years)

External website: https://sccer-jasm.ch; data platform: https://data.sccer-jasm.ch

Abstract:

The Joint Activity Scenarios and Modelling (JASM) aims at providing a set of robust scenarios for the realization of the Swiss Energy Strategy 2050. The modeling groups of the 8 Swiss Competence Centers for Energy Research (SCCER) work together and bring in their respective experience in the field of electricity generation technologies, buildings, mobility, industry, grids, biomass, storage and economy.

The objective is to generate scenarios on how CO2 emissions from the Swiss energy system can be substantially reduced from 36 Mt/y in 2015 down to 10 Mt/y in 2050. We want (i) to understand which technologies will form the basis for the future supply of electricity, heat and mobility services, (ii) to give guidance to policy-makers on how the transition from today to 2050 can be managed within the rules of a free market, and (iii) to deduce what this transition means to the Swiss economy and to the Swiss citizen in terms of costs, import dependency, etc.

 

Contact person: Stefano Moret (stefano.moret@epfl.ch), Xiang Li (xiang.li@epfl.ch)

Publication list

[1]
S. Moret : Strategic energy planning under uncertainty. EPFL, 2017. DOI : 10.5075/epfl-thesis-7961.
[2]
V. Codina Gironès; M. Allais; D. Favrat; F. Vuille; F. Maréchal : Exergy assessment of future energy transition scenarios with application to Switzerland. 2017. 30th International Conference on Efficiency, Cost, Optimisation, Simulation and Environmental Impact of Energy Systems, San Diego, California, USA, July 2-6, 2017.
[3]
V. Codina Gironès; S. Moret; F. Maréchal; D. Favrat : Strategic energy planning for large-scale energy systems: A modelling framework to aid decision-making; Energy. 2015. DOI : 10.1016/j.energy.2015.06.008.
[4]
S. Moret; M. Bierlaire; F. Maréchal : Robust Optimization for Strategic Energy Planning. 2014.