Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.


Calculation of a dynamic carbon factor for the Swiss electricity grid


A. Chevrier

Semester Thesis, FS16 (10539)

Although the electricity production mix of Switzerland is very clean in terms of CO2, the mix supplying the country contains electricity imported from neighboring countries, whose production generates considerably more emissions. As imports and exports are not constant throughout the year nor the months or days, the emission factor of the Swiss electricity grid varies continuously. Moreover, the rising penetration of intermittent renewables, as for wind and solar, can lead to stronger variations in the carbon factor over a short time span. The design and control of energy systems can be improved by a better monitoring of the CO2eq emissions of the electricity grid over time, leading to less overall emissions. By considering the strong changes that the mobility sector is undergoing, an even greater potential of emissions savings can be reached.

In the continuity of this idea, this project's aim is the real time assessment of the CO2eq emissions of the Swiss electricity mix, in form of an emissions factor indicator, given in g 􀀀 CO2eq=kWh. The calculations rest on production and exchange data from Switzerland and from the bordering countries. Taking the difficulties of tracing back the electricity origin into account, four different variants of handling exports are created and analyzed. With R, an interactive tool giving the carbon factor values of the different variants through the year is created.

From the results, the emission factor of the Swiss grid shows clear seasonal and daily patterns. The variant with the yearly average the closest to the published value from the federal office for environment of 100.5 g 􀀀 CO2eq=kWh (2011) over the year shows that yearly values are not precise enough [1]. Only four months from this variant's calculation falls approximately around the 100.5 g 􀀀 CO2eq=kWh. The calculation extracts minimum monthly median of less than 50g 􀀀 CO2eq=kWh during May and June, while October shows a median value around 150 g 􀀀 CO2eq=kWh with peaks at nearly 250g 􀀀 CO2eq=kWh. Finally, the report raises an important question concerning the relation between low emission factor and low loads. Periods of high electricity demand might be wrongly linked with those of high emissions. In the current setup, Switzerland experiences lower emission factor from its electricity mix during peak hours compared with o_-peak hours. The question of the maximal load on the system has to be considered before using the emission factor indicator.

Supervisors: Dr. Andrew Bollinger, Prof. Roy Smith


Type of Publication:

(13)Semester/Bachelor Thesis

File Download:

Request a copy of this publication.
(Uses JavaScript)
% Autogenerated BibTeX entry
@PhdThesis { Xxx:2016:IFA_5544
Permanent link