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Economics of compressed air energy storage to integrate wind power: A case study in ERCOT

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  • Fertig, Emily
  • Apt, Jay
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    Abstract

    Compressed air energy storage (CAES) could be paired with a wind farm to provide firm, dispatchable baseload power, or serve as a peaking plant and capture upswings in electricity prices. We present a firm-level engineering-economic analysis of a wind/CAES system with a wind farm in central Texas, load in either Dallas or Houston, and a CAES plant whose location is profit-optimized. With 2008 hourly prices and load in Houston, the economically optimal CAES expander capacity is unrealistically large - 24Â GW - and dispatches for only a few hours per week when prices are highest; a price cap and capacity payment likewise results in a large (17Â GW) profit-maximizing CAES expander. Under all other scenarios considered the CAES plant is unprofitable. Using 2008 data, a baseload wind/CAES system is less profitable than a natural gas combined cycle (NGCC) plant at carbon prices less than $56/tCO2 ($15/MMBTU gas) to $230/tCO2 ($5/MMBTU gas). Entering regulation markets raises profit only slightly. Social benefits of CAES paired with wind include avoided construction of new generation capacity, improved air quality during peak times, and increased economic surplus, but may not outweigh the private cost of the CAES system nor justify a subsidy.

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    File URL: http://www.sciencedirect.com/science/article/B6V2W-528XD2W-5/2/c3d03f0a559d3926585bb01c8072bc40
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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 39 (2011)
    Issue (Month): 5 (May)
    Pages: 2330-2342

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    Handle: RePEc:eee:enepol:v:39:y:2011:i:5:p:2330-2342

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    Web page: http://www.elsevier.com/locate/enpol

    Related research

    Keywords: Wind power Electric Reliability Council of Texas Compressed air energy storage;

    References

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    1. Denholm, Paul & Sioshansi, Ramteen, 2009. "The value of compressed air energy storage with wind in transmission-constrained electric power systems," Energy Policy, Elsevier, vol. 37(8), pages 3149-3158, August.
    2. Fischbeck, Paul & Vajjhala, Shalini, 2006. "Quantifying Siting Difficulty: A Case Study of U.S. Transmission Line Siting," Discussion Papers dp-06-03, Resources For the Future.
    3. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    4. DeCarolis, Joseph F. & Keith, David W., 2006. "The economics of large-scale wind power in a carbon constrained world," Energy Policy, Elsevier, vol. 34(4), pages 395-410, March.
    5. Pattanariyankool, Sompop & Lave, Lester B., 2010. "Optimizing transmission from distant wind farms," Energy Policy, Elsevier, vol. 38(6), pages 2806-2815, June.
    6. Greenblatt, Jeffery B. & Succar, Samir & Denkenberger, David C. & Williams, Robert H. & Socolow, Robert H., 2007. "Baseload wind energy: modeling the competition between gas turbines and compressed air energy storage for supplemental generation," Energy Policy, Elsevier, vol. 35(3), pages 1474-1492, March.
    7. Sioshansi, Ramteen & Denholm, Paul & Jenkin, Thomas & Weiss, Jurgen, 2009. "Estimating the value of electricity storage in PJM: Arbitrage and some welfare effects," Energy Economics, Elsevier, vol. 31(2), pages 269-277, March.
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    Cited by:
    1. Yang Gu & James McCalley & Ming Ni & Rui Bo, 2013. "Economic Modeling of Compressed Air Energy Storage," Energies, MDPI, Open Access Journal, vol. 6(4), pages 2221-2241, April.
    2. Lamy, Julian & Azevedo, Inês L. & Jaramillo, Paulina, 2014. "The role of energy storage in accessing remote wind resources in the Midwest," Energy Policy, Elsevier, vol. 68(C), pages 123-131.

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