IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v101y2017icp1124-1130.html
   My bibliography  Save this article

Is it always windy somewhere? Occurrence of low-wind-power events over large areas

Author

Listed:
  • Handschy, Mark A.
  • Rose, Stephen
  • Apt, Jay

Abstract

The incidence of widespread low-wind conditions is important to the reliability and economics of electric grids with large amounts of wind power. In order to investigate a future in which wind plants are geographically widespread but interconnected, we examine how frequently low generation levels occur for wind power aggregated from distant, weakly-correlated wind generators. We simulate the wind power using anemometer data from nine tall-tower sites spanning the contiguous United States. The number of low-power hours per year declines exponentially with the number of sites being aggregated. Hours with power levels below 5% of total capacity, for example, drop by a factor of about 60, from 2140 h/y for the median single site to 36 h/y for the generation aggregated from all nine sites; the standard deviation drops by a factor of 3. The systematic dependence of generation-level probability distribution “tails” on both number and power threshold is well described by the theory of Large Deviations. Combining this theory for tail behavior with the normal distribution for behavior near the mean allows us to estimate, without the use of any adjustable parameters, the entire generation duration curve as a function of the number of essentially independent sites in the array.

Suggested Citation

  • Handschy, Mark A. & Rose, Stephen & Apt, Jay, 2017. "Is it always windy somewhere? Occurrence of low-wind-power events over large areas," Renewable Energy, Elsevier, vol. 101(C), pages 1124-1130.
    • Handle: RePEc:eee:renene:v:101:y:2017:i:c:p:1124-1130
    DOI: 10.1016/j.renene.2016.10.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148116308680
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2016.10.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dowds, Jonathan & Hines, Paul & Ryan, Todd & Buchanan, William & Kirby, Elizabeth & Apt, Jay & Jaramillo, Paulina, 2015. "A review of large-scale wind integration studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 768-794.
    2. Rose, Stephen & Apt, Jay, 2016. "Quantifying sources of uncertainty in reanalysis derived wind speed," Renewable Energy, Elsevier, vol. 94(C), pages 157-165.
    3. Huang, Junling & Lu, Xi & McElroy, Michael B., 2014. "Meteorologically defined limits to reduction in the variability of outputs from a coupled wind farm system in the Central US," Renewable Energy, Elsevier, vol. 62(C), pages 331-340.
    4. Milligan, Michael & Porter, Kevin, 2006. "The Capacity Value of Wind in the United States: Methods and Implementation," The Electricity Journal, Elsevier, vol. 19(2), pages 91-99, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Adler, David B. & Jha, Akshaya & Severnini, Edson, 2020. "Considering the nuclear option: Hidden benefits and social costs of nuclear power in the U.S. since 1970," Resource and Energy Economics, Elsevier, vol. 59(C).
    2. Gao, Yang & Ma, Shaoxiu & Wang, Tao & Miao, Changhong & Yang, Fan, 2022. "Distributed onshore wind farm siting using intelligent optimization algorithm based on spatial and temporal variability of wind energy," Energy, Elsevier, vol. 258(C).
    3. Shahriari, Mehdi & Blumsack, Seth, 2018. "The capacity value of optimal wind and solar portfolios," Energy, Elsevier, vol. 148(C), pages 992-1005.
    4. Nian Shi & Yi Luo, 2017. "Energy Storage System Sizing Based on a Reliability Assessment of Power Systems Integrated with Wind Power," Sustainability, MDPI, vol. 9(3), pages 1-20, March.
    5. Raynaud, D. & Hingray, B. & François, B. & Creutin, J.D., 2018. "Energy droughts from variable renewable energy sources in European climates," Renewable Energy, Elsevier, vol. 125(C), pages 578-589.
    6. Karadöl, İsrafil & Yıldız, Ceyhun & Şekkeli, Mustafa, 2021. "Determining optimal spatial and temporal complementarity between wind and hydropower," Energy, Elsevier, vol. 230(C).
    7. Han, Chanok & Vinel, Alexander, 2022. "Reducing forecasting error by optimally pooling wind energy generation sources through portfolio optimization," Energy, Elsevier, vol. 239(PB).
    8. Böhme, Gustavo S. & Fadigas, Eliane A. & Soares, Dorel & Gimenes, André L.V. & Macedo, Bruno C., 2020. "Wind speed variability and portfolio effect – A case study in the Brazilian market," Energy, Elsevier, vol. 207(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shahriari, Mehdi & Blumsack, Seth, 2017. "Scaling of wind energy variability over space and time," Applied Energy, Elsevier, vol. 195(C), pages 572-585.
    2. Dey, Subhashish & Sreenivasulu, Anduri & Veerendra, G.T.N. & Rao, K. Venkateswara & Babu, P.S.S. Anjaneya, 2022. "Renewable energy present status and future potentials in India: An overview," Innovation and Green Development, Elsevier, vol. 1(1).
    3. Min, C.G. & Park, J.K. & Hur, D. & Kim, M.K., 2016. "A risk evaluation method for ramping capability shortage in power systems," Energy, Elsevier, vol. 113(C), pages 1316-1324.
    4. Paik, Chunhyun & Chung, Yongjoo & Kim, Young Jin, 2021. "ELCC-based capacity credit estimation accounting for uncertainties in capacity factors and its application to solar power in Korea," Renewable Energy, Elsevier, vol. 164(C), pages 833-841.
    5. Rezaee Jordehi, Ahmad, 2016. "Allocation of distributed generation units in electric power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 893-905.
    6. Cole, Wesley & Lewis, Haley & Sigrin, Ben & Margolis, Robert, 2016. "Interactions of rooftop PV deployment with the capacity expansion of the bulk power system," Applied Energy, Elsevier, vol. 168(C), pages 473-481.
    7. Ye, Lin & Zhang, Cihang & Xue, Hui & Li, Jiachen & Lu, Peng & Zhao, Yongning, 2019. "Study of assessment on capability of wind power accommodation in regional power grids," Renewable Energy, Elsevier, vol. 133(C), pages 647-662.
    8. Álvarez-García, Francisco J. & Fresno-Schmolk, Gonzalo & OrtizBevia, María J. & Cabos, William & RuizdeElvira, Antonio, 2020. "Reduction of aggregate wind power variability using Empirical Orthogonal Teleconnections: An application in the Iberian Peninsula," Renewable Energy, Elsevier, vol. 159(C), pages 151-161.
    9. Dan Tong & David J. Farnham & Lei Duan & Qiang Zhang & Nathan S. Lewis & Ken Caldeira & Steven J. Davis, 2021. "Geophysical constraints on the reliability of solar and wind power worldwide," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    10. Teresa Pakulska, 2021. "Green Energy in Central and Eastern European (CEE) Countries: New Challenges on the Path to Sustainable Development," Energies, MDPI, vol. 14(4), pages 1-19, February.
    11. Moisés Costa, Paulo & Matos, Manuel A., 2010. "Capacity credit of microgeneration and microgrids," Energy Policy, Elsevier, vol. 38(10), pages 6330-6337, October.
    12. Han, Chanok & Vinel, Alexander, 2022. "Reducing forecasting error by optimally pooling wind energy generation sources through portfolio optimization," Energy, Elsevier, vol. 239(PB).
    13. McPherson, Madeleine & Karney, Bryan, 2017. "A scenario based approach to designing electricity grids with high variable renewable energy penetrations in Ontario, Canada: Development and application of the SILVER model," Energy, Elsevier, vol. 138(C), pages 185-196.
    14. Dunja Srpak & Ladislav Havaš & Boštjan Polajžer, 2019. "Regulating Reserve Dynamic Scheduling and Optimal Allocation in Systems with a Large Share of Wind-Power Generation," Energies, MDPI, vol. 12(2), pages 1-14, January.
    15. Ciupăgeanu, Dana-Alexandra & Lăzăroiu, Gheorghe & Barelli, Linda, 2019. "Wind energy integration: Variability analysis and power system impact assessment," Energy, Elsevier, vol. 185(C), pages 1183-1196.
    16. José V. P. Miguel & Eliane A. Fadigas & Ildo L. Sauer, 2019. "The Influence of the Wind Measurement Campaign Duration on a Measure-Correlate-Predict (MCP)-Based Wind Resource Assessment," Energies, MDPI, vol. 12(19), pages 1-15, September.
    17. Siripha Junlakarn & Radhanon Diewvilai & Kulyos Audomvongseree, 2022. "Stochastic Modeling of Renewable Energy Sources for Capacity Credit Evaluation," Energies, MDPI, vol. 15(14), pages 1-27, July.
    18. Huang, Junling & McElroy, Michael B., 2015. "A 32-year perspective on the origin of wind energy in a warming climate," Renewable Energy, Elsevier, vol. 77(C), pages 482-492.
    19. Pearre, Nathaniel & Adye, Katherine & Swan, Lukas, 2019. "Proportioning wind, solar, and in-stream tidal electricity generating capacity to co-optimize multiple grid integration metrics," Applied Energy, Elsevier, vol. 242(C), pages 69-77.
    20. Chang-Gi Min & Mun-Kyeom Kim, 2017. "Net Load Carrying Capability of Generating Units in Power Systems," Energies, MDPI, vol. 10(8), pages 1-13, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:101:y:2017:i:c:p:1124-1130. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.