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Cost Modeling and Valuation of Grid-Scale Electrochemical Energy Storage Technologies

Chapter
Part of the Green Energy and Technology book series (GREEN)

Abstract

Electrochemical Energy storage (ES) technologies are seen as valuable flexibility assets with their capabilities to control grid power intermittency or power quality services in generation, transmission & distribution, and end-user consumption side. Grid-scale storage technologies can contribute significantly to enhance asset utilization rate and reliability of the power systems. The latter is particularly critical for deployment of regional and national energy policies of implementing renewable sources. Once the suitable storage technology is chosen, modeling and simulation of electrochemical storage devices are utilized extensively for performance or life cycle prediction purposes. The main challenge of adopting electrochemical storage technologies among utilities is how to match the right energy storage technology for a site-specific grid configuration to an appropriate grid service. The majority of system-level modeling efforts do not provide information that can be used for valuation of storage technologies. Battery performance models generally suffer from lacking techno-economic predictions and accurate assessment of performance characteristics of the emerging ES technologies. This chapter introduces a valuation framework that is built upon high-level electrochemical storage models. This valuation model can characterize and quantify different grid applications and services for which electrochemical storage devices are used. Taking local differences in electricity markets and storage value for several grid applications and services, the modeling framework is employed in case studies to identify the value that storage systems can provide to the grid.

Keywords

Cash Flow Electricity Market Power Quality Energy Storage System Grid Service 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Bouffard F, Kirschen DS (2008) Centralized and distributed electricity systems. Energy Policy 36:4504–4508CrossRefGoogle Scholar
  2. 2.
    Wade NS, Taylor PC, Lag PD, Jones PR (2010) Evaluating the benefits of an electrical energy storage system in a future smart grid. Energy Policy 38:7180–7188CrossRefGoogle Scholar
  3. 3.
    International Energy Agency (IEA) (2013) World energy outlook. Available from http://www.iea.org/newsroomandevents/speeches/131112_WEO2013_Presentation.pdf. Accessed 10 May 2014
  4. 4.
    Scott J (2004) Distributed generation: embrace the change. Power Engineering 2(18):12–13 Google Scholar
  5. 5.
    Electricity Advisory Committee (2008) Bottling electricity: storage as a strategic tool for managing variability and capacity concerns in the modern grid. Available from http://www.oe.energy.gov/final-energy-storage_12-16-08.pdfS. Accessed 19 Aug 2010
  6. 6.
    Sandia National Laboratories (2004) Energy storage benefits and market analysis handbook, SAND 2004-6177Google Scholar
  7. 7.
    Walawalkar R, Apt J (2008) Market analysis of emerging electric energy storage systems, DOE/NETL-2008/1330Google Scholar
  8. 8.
    Yang Z, Zhang J, Kintner-Meyer MCW, Lu X, Choi D, Lemmon JP, Liu J (2011) Electrochemical energy storage for green grid. Chem Rev 211:3577Google Scholar
  9. 9.
    Pearre S, Swan LG (2014) Applied energy, Article in pressGoogle Scholar
  10. 10.
    Sandia National Laboratories (2004) Energy storage benefits and market analysis handbook, SAND 2004-6177Google Scholar
  11. 11.
    Sandia National Laboratories/DNV-KEMA (2014) ES-select documentation and user’s manual. Available from http://www.sandia.gov/ess/ESSelectUpdates/ES-Select_Documentation_and_User_Manual-VER_2-2013.pdf. Accessed 10 May 2014
  12. 12.
    Lamontagne C (2014) Navigant survey of models and tools for the stationary energy storage industry. Available from http://www.slideshare.net/navigant/survey-of-models-and-tools-for-the-stationary-energy-storage-industry-february-2014. Accessed 01 Oct 2014
  13. 13.
    Pye J (2014) Three possible business models for distributed storage March 2014. Available from http://www.wattclarity.com.au/2014/03/three-possible-business-models-for-distributed-storage/. Accessed 01 Oct 2014
  14. 14.
    Denholm P, Sioshansi R (2009) The value of compressed air energy storage with wind in transmission-constrained electric power systems. Energy Policy 37:3149–3158CrossRefGoogle Scholar
  15. 15.
    Hittinger E, Whitacre JF, Apt J (2012) What properties of grid energy storage are most valuable? J Power Sources 206:436–449CrossRefGoogle Scholar
  16. 16.
    Denholm P et al, NREL (2010) The role of energy storage with renewable electricity generation. Available from http://www.nrel.gov/docs/fy10osti/47187.pdf. Accessed 10 May 2014
  17. 17.
    Electric Power Research Institute, Electricity Energy Storage Technology Options (2010) http://my.epri.com/portal/server.pt? Abstract id = 000000000001020676. Accessed 10 May 2014
  18. 18.
    EPRI (2014) The integrated grid: realizing the full value of central and distributed energy resources. Available from http://www.epri.com/abstracts/Pages/ProductAbstract.aspx?ProductId=3002002733. Accessed 10 May 2014
  19. 19.
    EPRI, US Department of Energy (2003) EPRI-DOE handbook of electricity storage for transmission and distribution applications, 1001834Google Scholar
  20. 20.
    Denholm P et al, NREL (2013) The value of energy storage for grid applications. Available from http://www.nrel.gov/docs/fy13osti/58465.pdf. Accessed 10 May 2014
  21. 21.
    Kaun B (2013) Cost-effectiveness of energy storage in California, Application of the EPRI Energy Storage Valuation Tool to Inform the California Public Utility Commission Proceeding R. 10-12-007. Available from http://www.cpuc.ca.gov/NR/rdonlyres/1110403D-85B2-4FDB-B927-5F2EE9507FCA/0/Storage_CostEffectivenessReport_EPRI.pdf. Accessed 10 May 2014

Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  1. 1.Department of Management SciencesUniversity of WaterlooWaterlooCanada
  2. 2.NRC-EMEVancouverCanada

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