1 / 22

Future Technology Options for Sustainable Electricity Generation

This study analyzes the technical trends, costs, and environmental performance of emerging electricity generation technologies for long-term energy scenarios. It covers advanced fossil fuels, hydrogen technologies, fuel cells, off-shore wind, photovoltaic, concentrating solar thermal power plants, biomass, advanced nuclear, and ocean technologies.

Télécharger la présentation

Future Technology Options for Sustainable Electricity Generation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. SIXTH FRAMEWORK PROGRAMME [6.1] [ Sustainable Energy Systems] Future technology options for electricity generation: technical trends, costs and environmental performance Wolfram Krewitt, DLR Brussels, 16.2.2009

  2. Objective • support the representation of technology development time dynamics in long term energy scenarios • characterisation of emerging electricity generation technologies with respect to long term future technical, economic and environmental performance

  3. technologies covered in NEEDS RS1a • Advanced fossil fuels (incl. CCS) • Hydrogen technologies • Fuel cells • Off-shore wind • Photovoltaic • Concentrating solar thermal power plants • Biomass • Advanced nuclear • ocean technologies

  4. methodology • Technology foresight analyse possible technological futures in connection with scenarios about energy systems and related societal developments • Experience curves analyse cost trends of future energy technologies • Life cycle assessment quantification of environmental burdens from future technologies based on dynamic LCA (‘environmental learning curve’) • external costs quantification of external costs of future technology configuration based on future LCA inventories

  5. technology futures depend on socio-economic framing conditions • ‘pessimistic scenario’ Socio-economic framing conditions do not stimulate market uptake and technical innovations. • ‘optimistic-realistic scenario’ Strong socio-economic drivers support dynamic market uptake and continuous technology development. It is very likely that the respective technology gains relevance on the global electricity market. • ‘very optimistic scenario’ A technological breakthrough makes the respective technology on the long term a leading global electricity supply technology.

  6. future off-shore wind technologies Source: NEEDS, DONG Energy

  7. history of wind energy technology development 140 120 100 80 rotor diameter in m 60 40 20 0 1980 1985 1990 1995 2000 2005 2010 MW 0.05 0.3 0.5 1.3 2 4.5 5

  8. concentrating solar thermal power plants • dispatchable large scale grid connected solar electricity generation • electricity generation today 800 GWh/y • Several power plants under construction

  9. CSP technology developments

  10. ocean energy technologies (examples) 2 MW pilot plant deployed 2004 in Portugal Pelamis 750 kW (4 articulated tubes; d = 3.5 m; each 40 m long); Wave dragon

  11. future cost developments Three complementary approaches: • Bottom-up assessment of cost development • Experience curves • Expert assessment of long term cost developments (interviews)

  12. progress ratios for new energy technologies Source: NEEDS, L. Neij

  13. PV technology development pathway Source: NEEDS, Ambiente Italia

  14. PV learning curve model(‘optimistic-realistic’ scenario) • fixed learning rate for PV modules (20%) (market penetration of thin films after 2010, and shift to third generation devices after 2025) • variable learning rate for electrical BOS: • 20% until 2010 • 10% 2011-2025 • 5% after 2025 • variable learning rate for mechanical BOS: • 20% until 2010 • 10% after 2010 • variable allocation of mechanical BOS to PV for building integrated PV: • 100% until 2010, then -1% each year to 85% in 2025, fixed after 2025 Source: NEEDS, Ambiente Italia

  15. future costs of building integrated PV Source: NEEDS, Ambiente Italia

  16. environmental burdens from full life cycle • life cycle inventory data on unit process level for each technology; by technology scenario and by base year (‘today’, 2025, 2050) • future configurations for key background processes (e.g. transport, production of iron and steel, copper, aluminium, flat glass, etc.) • energy mix scenarios • centralised LCA data processing at esu-services • final results available in web-based LCA database

  17. Comparison present, 2025, 2050 1,800 kWh/(m2*yr) on tilted roof, south-oriented 40 33,0 35 30 25 g CO2 / kWh 20 12,3 15 8,2 7,0 10 4,6 3,0 5 0 single c-Si ribbon CdTe 2025 c-Si ribbon CdTe 2050 Concentrator crystalline 2025 2050 GaInP/GaAs present 2050 future PV life cycle CO2-emissions 2025 2050 Source: NEEDS, Ambiente Italia

  18. life cycle CO2 emissions today 2050 g/kWh

  19. technology specific external costs • ‘generic’ external cost estimates for future electricity generation technologies in Europe • based on life cycle inventory data and unit damage cost estimates (from RS1b) • significant uncertainties in the field of climate change damage costs

  20. quantifiable external costs of future technologies (2050) ct/kWh

  21. conclusions • potential for technical innovations offers broad range of development options • policy settings trigger innovation and technical development • emerging energy technologies have a significant potential to reduce costs and environmental impacts • external costs of future low-carbon technologies seem to be relatively low compared to private costs • ‘total costs’ as a one-dimensional decision criteria might be misleading (large remaining uncertainties in quantifying environmental and societal externalities)

  22. Thank you very much for your attention! contact us: wolfram.krewitt@dlr.de or visit the websites: www.dlr.de/tt/system www.needs-project.org Acknowledgements: European Commission, 6th framework program Research teams of NEEDS Research stream 1a

More Related