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The future cost of electrical energy storage based on experience rates

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

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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.

An informed understanding of the potential future costs of electricity storage technologies is essential to quantify their uptake as well as the uptake of low-carbon technologies reliant on storage1,2,3. This can increase investor confidence and enable policymakers to design suitable deployment strategies4. A lack of open data to project storage costs currently necessitates incorporating wide cost ranges1, using cost projections of electric vehicle (EV) battery packs for stationary applications4,5 or excluding storage from studies of future electricity systems3.

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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.

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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.

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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

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  1. O. Schmidt
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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.

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Correspondence to O. Schmidt.

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

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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

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