Reducing the carbon footprint of the Swiss power sector: How to fill the gap?

Transcription

1 Wir schaffen Wissen heute für morgen Reducing the carbon footprint of the Swiss power sector: How to fill the gap? Christian Bauer, P. Eckle, K. Volkart, W. Schenler Paul Scherrer Institut, Laboratory for Energy Systems Analysis

2 Electricity generation [PJ] Reference scenario: CO 2 reduction in the Swiss power sector To be replaced by alternatives with lower GHG emissions 2035

3 Research question to be answered Given (a) certain preference profile(s): Which will be the preferred options for CO 2 reduction in the Swiss power sector in the future? Reference year 2035 Comparing different alternatives according to multiple criteria

4 Method Multi-Criteria Decision Analysis (MCDA) Comparing various electricity generation technologies Taking into account environmental, economic & social evaluation criteria Allowing stakeholder interaction by considering individual weighting of criteria/indicators using the weighted sum approach

5 MCDA: How does it work? Goal: CO 2 reduction in the power sector Selection of technology options (alternatives) Selection of criteria & indicators Quantification of indicators for each alternative Normalisation of indicators Weighting of indicators Aggregation: Combination of indicator values & weighting factors Ranking of alternatives

6 Alternatives for CO 2 reduction in the Swiss power sector Hydro: reservoir & run-of river Photovoltaic: mc- & a-si, roof-top Wind: onshore & offshore (import) Geothermal: Enhanced geothermal system Wood: with & w/o CCS (sustainable forestry) Biogas: from organic waste Nuclear: EPR Natural Gas CC: with CCS Hard coal & lignite: with CCS (import) Solar thermal (import) Differing generation potentials need to be considered in conclusions!

7 online MCDA tool

8 Selection of indicators Four main categories: Environment Economy Society Security of supply

9 Selection of indicators Environment based on LCIA fossil energy demand (CED) nuclear energy demand (CED) metal depletion (ReCiPe) ecosystem quality (ReCiPe) GHG emissions (IPCC biog. CO 2 ) [MJ/t CO 2 avd.] [MJ/t CO 2 avd.] [kg Fe-eq/t CO 2 avd.] [species*a/t CO 2 avd.] [kg CO 2 -eq/t CO 2 avd.] Economy CO 2 avoidance costs capital costs (investments) fuel sensitivity marginal avoidance costs [CHF/t CO 2 avd.] [CHF NPV] [share of fuel costs] [marginal CHF/t CO 2 avd.]

10 Selection of indicators Society conflict potential direct employment impacts on human health (ReCiPe) expected fatalities (severe accidents) max. number of fatalities (severe accidents) waste: chemical & radioactive (LCI results) Security of supply share of domestic supply diversity of resources reliability [ordinal scale] [person*a/t CO 2 avd.] [DALY/t CO 2 avd.] [fatalities/t CO 2 avd.] [max. fatalities/accident] [m 3 /t CO 2 avd.] [ordinal scale] [ordinal scale] [ordinal scale]

11 kg CO 2 eq/kwh GHG emissions from electricity generation (preliminary) 1.0E E E E E E E E E E E+00 NGCC emission level Reservoir Run-of-river EPR NGCC NGCC-post ATR H2CC ATR H2CC-pre NG CHP Wood comb. Wood comb.-post SNGCC SNGCC-post Biogas CHP PV multicrist. Si roof PV amorphous Si roof Wind onshore Geothermal Wind offshore Concentr. Solar-therm. Hard coal PC Hard coal PC-post Hard coal PC-oxy Hard coal IGCC Hard coal IGCC-pre Lignite PC Lignite PC-post Lignite PC-oxy Lignite IGCC Lignite IGCC-pre

12 ReCiPe H [DALY/kWh] Example: impacts on human health (ReCiPe H) (preliminary) 1.0E E E E E E+00 Reservoir Run-of-river EPR NGCC-post ATR H2CC-pre Wood comb. Wood comb.-post SNGCC SNGCC-post Biogas CHP PV multicrist. Si roof PV amorphous Si roof Wind onshore Geothermal Wind offshore Concentr. Solar-therm. Hard coal PC-post Hard coal PC-oxy Hard coal IGCC-pre Lignite PC-post Lignite PC-oxy Lignite IGCC-pre

13 normalized DALY per t CO 2 avoided Example: impacts on human health (ReCiPe H) (preliminary) best worst

14 Weighting of indicators Stakeholder profiles (exemplary) 1. focus on health & environment 2. focus on economy 3. focus on autonomous electricity supply & social factors

15 Weighting of indicators: 3 profiles

16 MCDA results (preliminary): profile health & environment best worst

17 MCDA results (preliminary): profile economy best worst

18 MCDA results (preliminary): profile social & autonomous best supply worst

19 Summary & Conclusions MCDA tool allows a transparent & interactive evaluation of technology options Considering stakeholder preference profiles & a comprehensive set of evaluation criteria/indicators Showing pros & cons of each alternative Preliminary MCDA results for CO 2 reduction in the Swiss power sector Hydro shows in general a good performance (BUT: very limited potential) Decentralized renewables tend to perform better than fossil power with CCS Biomass combustion with CCS turns out to be a good option Limited potentials of renewables to be considered NGCC with CCS

20 Outlook Generation of final indicator results Extension to further economic sectors with high potential for CO 2 reduction: residential, industry, mobility Consideration of efficiency measures Implementation of stakeholder interaction: integration of real preference profiles

21 Thanks for your attention! More information: Research carried out within the project CARMA :