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.

Limiting the public cost of stationary battery deployment by combining applications

Abstract

Batteries could be central to low-carbon energy systems with high shares of intermittent renewable energy sources. However, the investment attractiveness of batteries is still perceived as low, eliciting calls for policy to support deployment. Here we show how the cost of battery deployment can potentially be minimized by introducing an aspect that has been largely overlooked in policy debates and underlying analyses: the fact that a single battery can serve multiple applications. Batteries thereby can not only tap into different value streams, but also combine different risk exposures. To address this gap, we develop a techno-economic model and apply it to the case of lithium-ion batteries serving multiple stationary applications in Germany. Our results show that batteries could be attractive for investors even now if non-market barriers impeding the combination of applications were removed. The current policy debate should therefore be refocused so as to encompass the removal of such barriers.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Investment attractiveness of battery systems in single applications.
Figure 2: Increase in investment attractiveness due to combined applications of battery systems.
Figure 3: Breakdown of the secondary application’s return and risk contributions to the combined NPV per € invested.
Figure 4: General framework of investment attractiveness when combining a primary with a secondary application.

References

  1. 1

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

  2. 2

    Battke, B. & Schmidt, T. S. Cost-efficient demand-pull policies for multi-purpose technologies—the case of stationary electricity storage. Appl. Energy 155, 334–348 (2015).

    Article  Google Scholar 

  3. 3

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

    Article  Google Scholar 

  4. 4

    Krajačić, G. et al. Feed-in tariffs for promotion of energy storage technologies. Energy Policy 39, 1410–1425 (2011).

    Article  Google Scholar 

  5. 5

    Schmidt, T. S. Low-carbon investment risks and de-risking. Nature Clim. Change 4, 237–239 (2014).

    Article  Google Scholar 

  6. 6

    del Río, P. & Gual, M. A. An integrated assessment of the feed-in tariff system in Spain. Energy Policy 35, 994–1012 (2007).

    Article  Google Scholar 

  7. 7

    Energie-Info Erneuerbare Energien und das EEG: Zahlen, Fakten, Grafiken der EEG-induzierten Zahlungsströme (Bundesverband der Energie- und Wasserwirtschaft e.V., 2015).

  8. 8

    Eyer, J. & Corey, G. Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide (Sandia National Laboratories, 2010).

    Book  Google Scholar 

  9. 9

    Zucker, A., Hinchliffe, T. & Spisto, A. Assessing Storage Value in Electricity Markets: A Literature Review (European Commission Joint Research Centre, 2013).

    Google Scholar 

  10. 10

    Fitzgerald, G., Mandel, J., Morris, J. & Touati, H. The Economics of Battery Energy Storage (Rocky Mountain Institute, 2015).

    Google Scholar 

  11. 11

    Renewables and Electricity Storage, A Technology Roadmap for REmap 2030 (International Renewable Energy Agency, 2015).

  12. 12

    Manz, D., Piwko, R. & Miller, N. Look before you leap. IEEE Power Eng. Mag. 10, 75–84 (2012).

    Article  Google Scholar 

  13. 13

    Denholm, P. et al. The Value of Energy Storage for Grid Applications (National Renewable Energy Laboratory, 2013).

    Google Scholar 

  14. 14

    Akhil, A. A. et al. DOE/EPRI 2013 Electricity Storage Handbook in Collaboration with NRECA (Sandia National Laboratories, 2013).

    Google Scholar 

  15. 15

    Kaun, B. Cost-Effectiveness of Energy Storage in California: Application of the Energy Storage Valuation Tool to Inform the California Utility Commission Proceeding R. 10-12-007 (Electric Power Research Institute, 2013).

    Google Scholar 

  16. 16

    Brealey, R. & Myers, S. Principles of Corporate Finance (McGraw-Hill, 1981).

    Google Scholar 

  17. 17

    Sioshansi, R., Denholm, P. & Jenkin, T. Market and policy barriers to deployment of energy storage. Econ. Energy Environ. Policy 1, 47–63 (2012).

    Article  Google Scholar 

  18. 18

    Culver, W. J. High-value energy storage for the grid: a multi-dimensional look. Electr. J. 23, 59–71 (2010).

    Article  Google Scholar 

  19. 19

    Sioshansi, R., Denholm, P., Jenkin, T. & Weiss, J. Estimating the value of electricity storage in PJM: arbitrage and some welfare effects. Energy Econ. 31, 269–277 (2009).

    Article  Google Scholar 

  20. 20

    Wilson, D. & Hughes, L. Barriers to the development of electrical energy storage: a North American perspective. Electr. J. 27, 14–22 (2014).

    Article  Google Scholar 

  21. 21

    Bhatnagar, D. & Loose, V. Evaluating Utility Procured Electric Energy Storage Resources: A Perspective for State Electric Utility Regulators A Study for the DOE Energy Storage Systems Program (Sandia National Laboratories, 2012).

    Google Scholar 

  22. 22

    Schoenung, S. M. & Eyer, J. Benefit/Cost Framework for Evaluating Modular Energy Storage (Sandia National Laboratories, 2008).

    Google Scholar 

  23. 23

    EPRI-DOE Handbook of Energy Storage for Transmission & Distribution Applications (Electric Power Research Institute, 2003).

  24. 24

    Sharpe, W. F. Capital asset prices: a theory of market equilibrium under conditions of risk. J. Finance 19, 425–442 (1964).

    Google Scholar 

  25. 25

    Dunn, B., Kamath, H. & Tarascon, J.-M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011).

    Article  Google Scholar 

  26. 26

    Renewables 2015 Global Status Report (Renewable Energy Policy Network for the 21st Century, 2015).

  27. 27

    KfW-Programm Erneuerbare Energien “Speicher” (KfW Bankengruppe, 2015).

  28. 28

    Waissbein, O., Glemarec, Y., Bayraktar, H. & Schmidt, T. S. Derisking Renewable Energy Investment (United Nations Development Programme, 2013).

    Google Scholar 

  29. 29

    Ebner, M., Marone, F., Stampanoni, M. & Wood, V. Visualization and quantification of electrochemical and mechanical degradation in Li ion batteries. Science 342, 716–720 (2013).

    Article  Google Scholar 

  30. 30

    He, X., Delarue, E., D’haeseleer, W. & Glachant, J.-M. A novel business model for aggregating the values of electricity storage. Energy Policy 39, 1575–1585 (2011).

    Article  Google Scholar 

  31. 31

    Taylor, J. A. Financial storage rights. IEEE Trans. Power Syst. 30, 997–1005 (2015).

    Article  Google Scholar 

  32. 32

    Energy and Climate Change World Energy Outlook Special Report (International Energy Agency, 2015).

  33. 33

    Agnew, S. & Dargusch, P. Effect of residential solar and storage on centralized electricity supply systems. Nature Clim. Change 5, 315–318 (2015).

    Article  Google Scholar 

  34. 34

    Graffy, E. & Kihm, S. Does disruptive competition mean a death spiral for electric utilities? Energy Law J. 35, 1–44 (2014).

    Google Scholar 

  35. 35

    Bontrup, H.-J. & Marquardt, R.-M. Die Zukunft der Großen Energieversorger (Greenpeace e.V., 2015).

    Google Scholar 

  36. 36

    Brown, L. et al. An inventory of nitrous oxide emissions from agriculture in the UK using the IPCC methodology: emission estimate, uncertainty and sensitivity analysis. Atmos. Environ. 35, 1439–1449 (2001).

    Article  Google Scholar 

  37. 37

    Vose, D., Koupeev, T., Van Hauwermeiren, M., Smet, W. & van den Bossche, S. Help File for ModelRisk Version 5 Vose Software (2007); http://www.vosesoftware.com/ModelRiskHelp/index.htm#Modeling_expert_opinion/Distributions_used_in_modeling_expert_opinion.htm

    Google Scholar 

  38. 38

    Damodaran, A. Strategic Risk Taking: a Framework for Risk Management (Wharton School Publishing, 2008).

    Google Scholar 

  39. 39

    Kerber, G. Aufnahmefähigkeit von Niederspannungsverteilnetzen für die Einspeisung aus Photovoltaikkleinanlagen (Technische Universität München, 2011).

    Google Scholar 

  40. 40

    Hille, C. et al. Technische und Wirtschaftliche Potenziale von Speichersystemen in Verteilungsnetzen (P3 Energy; RWTH Aachen, 2015).

    Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the financial support provided by EnergieSchweiz (project ID 131916726). We also would like to thank V. Hoffmann, J. Kölbel and P. Thömmes for their support for and valuable inputs to this study.

Author information

Affiliations

Authors

Contributions

T.S.S., A.S. and B.B. designed the research, A.S., M.D.B. and J.H.C. developed the model and carried out the data search, A.S. and T.S.S. carried out the analyses, A.S. and T.S.S. wrote the paper.

Corresponding author

Correspondence to T. S. Schmidt.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Figures 1–4, Supplementary Tables 1–4, Supplementary Notes 1–4, Supplementary References. (PDF 604 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Stephan, A., Battke, B., Beuse, M. et al. Limiting the public cost of stationary battery deployment by combining applications. Nat Energy 1, 16079 (2016). https://doi.org/10.1038/nenergy.2016.79

Download citation

Further reading

Search

Quick links