IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v50y2013icp1014-1026.html
   My bibliography  Save this article

Long-term wind resource and uncertainty estimation using wind records from Scotland as example

Author

Listed:
  • Früh, Wolf-Gerrit

Abstract

A systematic analysis of the sensitivity of a wind turbine's output to changes in observed wind statistics between different sites in Scotland over available wind records of up to 43 years length was performed. The analysis was performed in the context of observed variability on time scales longer than a year. The findings are discussed in the context of the ability to predict the long-term wind energy potential reliably both for wind farms as well as small turbines. In the analysis, some measures are defined to quantify the forecast accuracy and the long-term prediction error. One of the items of discussion was motivated by the observation in the wind industry that the year 2010 was a poor year, with hopes that it was just an exceptional year and fears that it might be an indicator of continuing climate change. The result of this discussion is that 2010 can only be seen as an outlier if one assumes that the past decades represent a constant wind climate. A linear regression, however, suggests that this assumption may not be correct and that 2010 may have been a low-wind year but consistent with generally observed fluctuations around a changing wind climate.

Suggested Citation

  • Früh, Wolf-Gerrit, 2013. "Long-term wind resource and uncertainty estimation using wind records from Scotland as example," Renewable Energy, Elsevier, vol. 50(C), pages 1014-1026.
  • Handle: RePEc:eee:renene:v:50:y:2013:i:c:p:1014-1026
    DOI: 10.1016/j.renene.2012.08.047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148112005174
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2012.08.047?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. Carta, J.A. & Ramírez, P., 2007. "Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions," Renewable Energy, Elsevier, vol. 32(3), pages 518-531.
    2. Brayshaw, David James & Troccoli, Alberto & Fordham, Rachael & Methven, John, 2011. "The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the UK," Renewable Energy, Elsevier, vol. 36(8), pages 2087-2096.
    3. Cabello, M. & Orza, J.A.G., 2010. "Wind speed analysis in the province of Alicante, Spain. Potential for small-scale wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3185-3191, December.
    4. Sinden, Graham, 2007. "Characteristics of the UK wind resource: Long-term patterns and relationship to electricity demand," Energy Policy, Elsevier, vol. 35(1), pages 112-127, January.
    5. Safari, Bonfils & Gasore, Jimmy, 2010. "A statistical investigation of wind characteristics and wind energy potential based on the Weibull and Rayleigh models in Rwanda," Renewable Energy, Elsevier, vol. 35(12), pages 2874-2880.
    6. Sailor, David J. & Smith, Michael & Hart, Melissa, 2008. "Climate change implications for wind power resources in the Northwest United States," Renewable Energy, Elsevier, vol. 33(11), pages 2393-2406.
    7. Migoya, Emilio & Crespo, Antonio & Jiménez, Ángel & García, Javier & Manuel, Fernando, 2007. "Wind energy resource assessment in Madrid region," Renewable Energy, Elsevier, vol. 32(9), pages 1467-1483.
    8. Pryor, S.C. & Barthelmie, R.J., 2010. "Climate change impacts on wind energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 430-437, January.
    9. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    10. Pereira de Lucena, André Frossard & Szklo, Alexandre Salem & Schaeffer, Roberto & Dutra, Ricardo Marques, 2010. "The vulnerability of wind power to climate change in Brazil," Renewable Energy, Elsevier, vol. 35(5), pages 904-912.
    11. Oswald, James & Raine, Mike & Ashraf-Ball, Hezlin, 2008. "Will British weather provide reliable electricity?," Energy Policy, Elsevier, vol. 36(8), pages 3202-3215, August.
    12. Bivona, S. & Burlon, R. & Leone, C., 2003. "Hourly wind speed analysis in Sicily," Renewable Energy, Elsevier, vol. 28(9), pages 1371-1385.
    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. Loukatou, Angeliki & Howell, Sydney & Johnson, Paul & Duck, Peter, 2018. "Stochastic wind speed modelling for estimation of expected wind power output," Applied Energy, Elsevier, vol. 228(C), pages 1328-1340.
    2. Loukatou, Angeliki & Johnson, Paul & Howell, Sydney & Duck, Peter, 2021. "Optimal valuation of wind energy projects co-located with battery storage," Applied Energy, Elsevier, vol. 283(C).
    3. Murthy, K.S.R. & Rahi, O.P., 2017. "A comprehensive review of wind resource assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1320-1342.

    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. Engeland, Kolbjørn & Borga, Marco & Creutin, Jean-Dominique & François, Baptiste & Ramos, Maria-Helena & Vidal, Jean-Philippe, 2017. "Space-time variability of climate variables and intermittent renewable electricity production – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 600-617.
    2. Simon Watson, 2014. "Quantifying the variability of wind energy," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(4), pages 330-342, July.
    3. Wang, Bing & Ke, Ruo-Yu & Yuan, Xiao-Chen & Wei, Yi-Ming, 2014. "China׳s regional assessment of renewable energy vulnerability to climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 185-195.
    4. Hdidouan, Daniel & Staffell, Iain, 2017. "The impact of climate change on the levelised cost of wind energy," Renewable Energy, Elsevier, vol. 101(C), pages 575-592.
    5. Florin Onea & Andrés Ruiz & Eugen Rusu, 2020. "An Evaluation of the Wind Energy Resources along the Spanish Continental Nearshore," Energies, MDPI, vol. 13(15), pages 1-23, August.
    6. Goh, H.H. & Lee, S.W. & Chua, Q.S. & Goh, K.C. & Teo, K.T.K., 2016. "Wind energy assessment considering wind speed correlation in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1389-1400.
    7. Jung, Christopher & Schindler, Dirk, 2019. "Wind speed distribution selection – A review of recent development and progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    8. Shin, Ju-Young & Ouarda, Taha B.M.J. & Lee, Taesam, 2016. "Heterogeneous mixture distributions for modeling wind speed, application to the UAE," Renewable Energy, Elsevier, vol. 91(C), pages 40-52.
    9. Cabello, M. & Orza, J.A.G., 2010. "Wind speed analysis in the province of Alicante, Spain. Potential for small-scale wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3185-3191, December.
    10. Jiang, Haiyan & Wang, Jianzhou & Wu, Jie & Geng, Wei, 2017. "Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1199-1217.
    11. Schaeffer, Roberto & Szklo, Alexandre Salem & Pereira de Lucena, André Frossard & Moreira Cesar Borba, Bruno Soares & Pupo Nogueira, Larissa Pinheiro & Fleming, Fernanda Pereira & Troccoli, Alberto & , 2012. "Energy sector vulnerability to climate change: A review," Energy, Elsevier, vol. 38(1), pages 1-12.
    12. 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.
    13. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    14. Carta, José A. & Velázquez, Sergio & Cabrera, Pedro, 2013. "A review of measure-correlate-predict (MCP) methods used to estimate long-term wind characteristics at a target site," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 362-400.
    15. Santos, J.A. & Rochinha, C. & Liberato, M.L.R. & Reyers, M. & Pinto, J.G., 2015. "Projected changes in wind energy potentials over Iberia," Renewable Energy, Elsevier, vol. 75(C), pages 68-80.
    16. Cannon, D.J. & Brayshaw, D.J. & Methven, J. & Coker, P.J. & Lenaghan, D., 2015. "Using reanalysis data to quantify extreme wind power generation statistics: A 33 year case study in Great Britain," Renewable Energy, Elsevier, vol. 75(C), pages 767-778.
    17. Boccard, Nicolas, 2010. "Economic properties of wind power: A European assessment," Energy Policy, Elsevier, vol. 38(7), pages 3232-3244, July.
    18. Jentsch, Mark F. & James, Patrick A.B. & Bourikas, Leonidas & Bahaj, AbuBakr S., 2013. "Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates," Renewable Energy, Elsevier, vol. 55(C), pages 514-524.
    19. repec:hal:spmain:info:hdl:2441/53r60a8s3kup1vc9l564igg8g is not listed on IDEAS
    20. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    21. Emilio Gómez-Lázaro & María C. Bueso & Mathieu Kessler & Sergio Martín-Martínez & Jie Zhang & Bri-Mathias Hodge & Angel Molina-García, 2016. "Probability Density Function Characterization for Aggregated Large-Scale Wind Power Based on Weibull Mixtures," Energies, MDPI, vol. 9(2), pages 1-15, February.

    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:50:y:2013:i:c:p:1014-1026. 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.