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Internship, Semester Thesis, Master Thesis
Factors driving uptake of renewable energy systems in Swiss households
Keywords: energy systems, mathematical models, statistics,
The adoption of robust and environmentally friendly energy solutions within households is prerequisite of reaching the energy goals set by Swiss 2050+ energy strategy. It is therefore imperative to devise reliable mathematical models which can project the uptake of these solutions, taking into account the contributions of different
socio-economic and technological forces. The project investigates factors affecting the spread of renewable systems across local-communities and nation-wide in Switzerland. The tasks involve acquisition, preprocessing, and initial statistical assessments of gathered datasets, with primary focus on installation of heatpumps and Photovoltaics. The resultant datasets will be employed in a heterogeneous Bass diffusion model to predict the uptake of various renewable energy systems, in different plausible scenarios. The project duration is set for six months, with the option of flexible starting date upon mutual agreement. Previous familiarity with R would be advantageous. Work location is at the Laboratory of Computational Engineering in Dübendorf.
The adoption of robust and environmentally friendly energy solutions within households is prerequisite of reaching the energy goals set by Swiss 2050+ energy strategy. It is therefore imperative to devise reliable mathematical models which can project the uptake of these solutions, taking into account the contributions of different socio-economic and technological forces. The project investigates factors affecting the spread of renewable systems across local-communities and nation-wide in Switzerland. The tasks involve acquisition, preprocessing, and initial statistical assessments of gathered datasets, with primary focus on installation of heatpumps and Photovoltaics. The resultant datasets will be employed in a heterogeneous Bass diffusion model to predict the uptake of various renewable energy systems, in different plausible scenarios. The project duration is set for six months, with the option of flexible starting date upon mutual agreement. Previous familiarity with R would be advantageous. Work location is at the Laboratory of Computational Engineering in Dübendorf.
Not specified
Dr. Hossein Gorji
Laboratory for Computational Engineering - Empa
mohammadhossein.gorji@empa.ch
Dr. Hossein Gorji Laboratory for Computational Engineering - Empa mohammadhossein.gorji@empa.ch
