Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Analysis
  • Published:

The future cost of electrical energy storage based on experience rates

Nature Energy volume 2, Article number: 17110 (2017) Cite this article

Subjects

Abstract

Electrical energy storage could play a pivotal role in future low-carbon electricity systems, balancing inflexible or intermittent supply with demand. Cost projections are important for understanding this role, but data are scarce and uncertain. Here, we construct experience curves to project future prices for 11 electrical energy storage technologies. We find that, regardless of technology, capital costs are on a trajectory towards US$340 ± 60 kWh−1 for installed stationary systems and US$175 ± 25 kWh−1 for battery packs once 1 TWh of capacity is installed for each technology. Bottom-up assessment of material and production costs indicates this price range is not infeasible. Cumulative investments of US$175–510 billion would be needed for any technology to reach 1 TWh deployment, which could be achieved by 2027–2040 based on market growth projections. Finally, we explore how the derived rates of future cost reduction influence when storage becomes economically competitive in transport and residential applications. Thus, our experience-curve data set removes a barrier for further study by industry, policymakers and academics.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Experience curves for EES technologies.
Figure 2: Future cost of EES technologies at 1 TWh cumulative capacity.
Figure 3: Future cost of EES technologies relative to time.
Figure 4: Impact of cumulative investment in EES deployment on future cost of EES.
Figure 5: Applicability of experience-curve-based cost projections to application-specific levelized cost analyses.

Similar content being viewed by others

References

  1. Braff, W. A., Mueller, J. M. & Trancik, J. E. Value of storage technologies for wind and solar energy. Nat. Clim. Change 6, 964–969 (2016).

    Article  Google Scholar 

  2. Nykvist, B. & Nilsson, M. Rapidly falling costs of battery packs for electric vehicles. Nat. Clim. Change 5, 329–332 (2015).

    Article  Google Scholar 

  3. MacDonald, A. E. et al. Future cost-competitive electricity systems and their impact on US CO2 emissions. Nat. Clim. Change 6, 526–531 (2016).

    Article  Google Scholar 

  4. Stephan, A., Battke, B., Beuse, M. D., Clausdeinken, J. H. & Schmidt, T. S. Limiting the public cost of stationary battery deployment by combining applications. Nat. Energy 1, 16079 (2016).

    Article  Google Scholar 

  5. Pfenninger, S. & Keirstead, J. Renewables, nuclear, or fossil fuels? Scenarios for Great Britain’s power system considering costs, emissions and energy security. Appl. Energy 152, 83–93 (2015).

    Article  Google Scholar 

  6. Farmer, J. D. & Lafond, F. How predictable is technological progress? Res. Policy 45, 647–665 (2015).

    Article  Google Scholar 

  7. Perspectives on Experience (Boston Consulting Group, 1970).

  8. Junginger, M., van Sark, W. & Faaij, A. Technological Learning in the Energy Sector: Lessons for Policy, Industry and Science (Edward Elgar Publishing, 2010).

    Book  Google Scholar 

  9. Nagy, B., Farmer, J. D., Bui, Q. M. & Trancik, J. E. Statistical basis for predicting technological progress. PLoS ONE 8, e52669 (2013).

    Article  Google Scholar 

  10. Matteson, S. & Williams, E. Residual learning rates in lead-acid batteries: effects on emerging technologies. Energy Policy 85, 71–79 (2015).

    Article  Google Scholar 

  11. Sandalow, D., McCormick, C., Rowlands-Rees, T., Izadi-Najafabadi, A. & Orlandi, I. Distributed Solar and Storage—ICEF Roadmap 1.0 (Innovation for Cool Earth Forum, 2015).

    Google Scholar 

  12. Staffell, I. & Green, R. The cost of domestic fuel cell micro-CHP systems. Int. J. Hydrog. Energy 38, 1088–1102 (2013).

    Article  Google Scholar 

  13. Schoots, K., Ferioli, F., Kramer, G. J. & van der Zwaan, B. C. C. Learning curves for hydrogen production technology: an assessment of observed cost reductions. Int. J. Hydrog. Energy 33, 2630–2645 (2008).

    Article  Google Scholar 

  14. Gerssen-Gondelach, S. J. & Faaij, A. P. C. Performance of batteries for electric vehicles on short and longer term. J. Power Sources 212, 111–129 (2012).

    Article  Google Scholar 

  15. Neij, L. Cost development of future technologies for power generation—a study based on experience curves and complementary bottom-up assessments. Energy Policy 36, 2200–2211 (2008).

    Article  Google Scholar 

  16. Wright, T. P. Factors affecting the cost of airplanes. J. Aeronaut. Sci. 3, 122–128 (1936).

    Article  Google Scholar 

  17. Luo, X., Wang, J., Dooner, M. & Clarke, J. Overview of current development in electrical energy storage technologies and the application potential in power system operation. Appl. Energy 137, 511–536 (2015).

    Article  Google Scholar 

  18. Gross, R. et al. Presenting the Future—An assessment of Future Costs Estimation Methodologies in the Electricity Generation Sector (UK Energy Research Center, 2013).

    Google Scholar 

  19. BatPac v.3.0. (Argonne National Laboratory, accessed 1 December 2015); http://www.cse.anl.gov/batpac/about.html

  20. James, B. D., Moton, J. M. & Colella, W. G. Mass Production Cost Estimation of Direct H2 PEM Fuel Cell Systems for Transportation Applications: 2013 Update (Strategic Analysis, 2014).

    Google Scholar 

  21. Renewable Energy Technologies: Cost Analysis Series—Hydropower (International Renewable Energy Agency, 2012).

  22. Wadia, C., Albertus, P. & Srinivasan, V. Resource constraints on the battery energy storage potential for grid and transportation applications. J. Power Sources 196, 1593–1598 (2011).

    Article  Google Scholar 

  23. Lazard’s Levelized Cost of Storage Analysis—Version 2.0 (Lazard Ltd, accessed 26 January 2017); https://www.lazard.com/media/438042/lazard-levelized-cost-of-storage-v20.pdf

  24. Rogers, E. Diffusion of Innovations (Free Press, 1995).

    Google Scholar 

  25. MacDonald, J. Electric Vehicles to be 35% of Global New Car Sales by 2040 (Bloomberg New Energy Finance, accessed 19th August 2016); http://about.bnef.com/press-releases/electric-vehicles-to-be-35-of-global-new-car-sales-by-2040

    Google Scholar 

  26. Kahouli-Brahmi, S. Technological learning in energy-environment-economy modelling: a survey. Energy Policy 36, 138–162 (2008).

    Article  Google Scholar 

  27. Cobb, J. GM Says Li-ion Battery Cells Down To $145 kWh−1 and Still Falling (hybridCARS, accessed 30 April 2016); http://www.hybridcars.com/gm-ev-battery-cells-down-to-145kwh-and-still-falling

    Google Scholar 

  28. Curry, C. 2016 Lithium-ion Battery Price Survey (Bloomberg New Energy Finance, 2016).

    Google Scholar 

  29. Technology Roadmap—Energy Storage (International Energy Agency, 2014).

  30. McCrone, A., Moslener, U., D’Estais, F., Usher, E. & Grünig, C. Global Trends in Renewable Energy Investment 2016 (Frankfurt School-UNEP Centre/Bloomberg New Energy Finance, 2016).

    Google Scholar 

  31. Mills, L. & Louw, A. Global Trends in Clean Energy Investment (Bloomberg New Energy Finance, 2016).

    Google Scholar 

  32. World Energy Investment 2016 (International Energy Agency, 2016).

  33. Needell, Z. A., McNerney, J., Chang, M. T. & Trancik, J. E. Potential for widespread electrification of personal vehicle travel in the United States. Nat. Energy 1, 16112 (2016).

    Article  Google Scholar 

  34. Gaines, L. & Cuenca, R. Costs of Lithium-Ion Batteries for Vehicles (Argonne National Laboratory, 2000).

    Book  Google Scholar 

  35. Advanced Vehicle Testing Activity: 2014 Tesla Model S 85 kWh (Idaho National Laboratory, 2016).

  36. Hoppmann, J., Volland, J., Schmidt, T. S. & Hoffmann, V. H. The economic viability of battery storage for residential solar photovoltaic systems—a review and a simulation model. Renew. Sustain. Energy Rev. 39, 1101–1118 (2014).

    Article  Google Scholar 

  37. Abernathy, W. J. & Kenneth, W. Limits of the learning curve. Havard Business Review 109–119 (September 1974).

  38. Schmidt, O., Hawkes, A., Gambhir, A. & Staffell, I. Figshare Digital Repository (2017); http://dx.doi.org/10.6084/m9.figshare.5048062

    Google Scholar 

  39. Wiesenthal, T. et al. Technology Learning Curves for Energy Policy Support. JRC Scientific and Policy Reports (European Commission—Joint Research Centre, 2012).

    Google Scholar 

  40. OECD.Stat—Consumer Prices (OECD, accessed 24 February 2016); http://stats.oecd.org/Index.aspx?querytype=view queryname=221

  41. OECD.Stat—Producer Prices (OECD, accessed 24 February 2016); http://stats.oecd.org/Index.aspx?DataSetCode=MEI_PRICES_PPI

  42. Chen, H., Ngoc, T., Yang, W., Tan, C. & Li, Y. Progress in electrical energy storage system: a critical review. Prog. Nat. Sci. 19, 291–312 (2009).

    Article  Google Scholar 

  43. Ashby, M. F. & Polyblank, J. Materials for Energy Storage Systems—A White Paper (Granta Design, 2012).

    Google Scholar 

  44. Sullivan, J. L. & Gaines, L. Status of life cycle inventories for batteries. Energy Convers. Manag. 58, 134–148 (2012).

    Article  Google Scholar 

  45. Koj, J. C., Schreiber, A., Zapp, P. & Marcuello, P. Life cycle assessment of improved high pressure alkaline electrolysis. Energy Procedia 75, 2871–2877 (2015).

    Article  Google Scholar 

  46. Notter, D. A., Kouravelou, K., Karachalios, T., Daletou, M. K. & Haberland, N. T. Life cycle assessment of PEM FC applications: electric mobility and μ-CHP. Energy Environ. Sci. 8, 1969–1985 (2015).

    Article  Google Scholar 

  47. Galloway, R. C. & Dustmann, C.-H. ZEBRA battery—material cost availability and recycling. In Proc. Int. Electric Vehicle Symposium (EVS-20) 19–28 (Electric Drive Transportation Association, 2003).

    Google Scholar 

  48. Commodities (Bloomberg, accessed 19 August 2016); https://www.bloomberg.com/markets/commodities

  49. Wu, G., Inderbitzin, A. & Bening, C. Total cost of ownership of electric vehicles compared to conventional vehicles: a probabilistic analysis and projection across market segments. Energy Policy 80, 196–214 (2015).

    Article  Google Scholar 

  50. US Gasoline and Diesel Retail Prices (US Department of Energy, accessed 17 March 2017); https://www.eia.gov/dnav/pet/PET_PRI_GND_DCUS_NUS_M.htm

  51. Spot Prices for Crude Oil and Petroleum Products (US Department of Energy, accessed 17 March 2017); https://www.eia.gov/dnav/pet/pet_pri_spt_s1_m.htm

  52. Mayr, F. & Beushausen, H. Navigating the maze of energy storage costs. PV Magazine 84–88 (May, 2016).

  53. Batteries for Stationary Energy Storage in Germany: Market Status Outlook (Germany Trade & Invest, 2016).

  54. Tepper, M. Solarstromspeicher-Preismonitor Deutschland 2016 (Bundesverband Solarwirtschaft e.V. und Intersolar Europe, 2016).

    Google Scholar 

Download references

Acknowledgements

We would like to thank all manufacturers and industry analysts that actively contributed to this study, in particular L. Goldie-Scot, H. N. Beushausen, N. Nielsen, S. Schnez and M. Tepper. O.S. would like to acknowledge support from the Imperial College Grantham Institute for his PhD research. I.S. was funded by the EPSRC under EP/M001369/1. A.H. was supported by NERC/Newton project NE/N018656/1. A.G. and O.S. would like to acknowledge funding from the EPSRC and ESRC Imperial College London Impact Acceleration Accounts EP/K503733/1 and ES/M500562/1.

Author information

Authors and Affiliations

  1. Imperial College London, Grantham Institute—Climate Change and the Environment, Exhibition Road, London SW7 2AZ, UK

    O. Schmidt & A. Gambhir

  2. Imperial College London, Centre for Environmental Policy, 14 Princes Gardens, London SW7 1NA, UK

    O. Schmidt & I. Staffell

  3. Department of Chemical Engineering, Imperial College London, Prince Consort Road, London SW7 2AZ, UK

    A. Hawkes

Authors
  1. O. Schmidt
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Hawkes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Gambhir
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. I. Staffell
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

O.S. and I.S. conducted the main part of research design, data gathering and analysis. A.H. and A.G. contributed to research design and analysis. O.S. wrote the paper. I.S., A.H. and A.G. edited the paper.

Corresponding author

Correspondence to O. Schmidt.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Notes 1–2, Supplementary Tables 1–7, Supplementary Figures 1–11 and Supplementary References. (PDF 1075 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schmidt, O., Hawkes, A., Gambhir, A. et al. The future cost of electrical energy storage based on experience rates. Nat Energy 2, 17110 (2017). https://doi.org/10.1038/nenergy.2017.110

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/nenergy.2017.110

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing