IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v157y2020icp754-768.html
   My bibliography  Save this article

A parametric model for wind turbine power curves incorporating environmental conditions

Author

Listed:
  • Saint-Drenan, Yves-Marie
  • Besseau, Romain
  • Jansen, Malte
  • Staffell, Iain
  • Troccoli, Alberto
  • Dubus, Laurent
  • Schmidt, Johannes
  • Gruber, Katharina
  • Simões, Sofia G.
  • Heier, Siegfried

Abstract

A wind turbine’s power curve relates its power production to the wind speed it experiences. The typical shape of a power curve is well known and has been studied extensively. However, power curves of individual turbine models can vary widely from one another. This is due to both the technical features of the turbine (power density, cut-in and cut-out speeds, limits on rotational speed and aerodynamic efficiency), and environmental factors (turbulence intensity, air density, wind shear and wind veer). Data on individual power curves are often proprietary and only available through commercial databases. We therefore develop an open-source model for pitch regulated horizontal axis wind turbine which can generate the power curve of any turbine, adapted to the specific conditions of any site. This can employ one of six parametric models advanced in the literature, and accounts for the eleven variables mentioned above. The model is described, the impact of each technical and environmental feature is examined, and it is then validated against the manufacturer power curves of 91 turbine models. Versions of the model are made available in MATLAB, R and Python code for the community.

Suggested Citation

  • Saint-Drenan, Yves-Marie & Besseau, Romain & Jansen, Malte & Staffell, Iain & Troccoli, Alberto & Dubus, Laurent & Schmidt, Johannes & Gruber, Katharina & Simões, Sofia G. & Heier, Siegfried, 2020. "A parametric model for wind turbine power curves incorporating environmental conditions," Renewable Energy, Elsevier, vol. 157(C), pages 754-768.
    • Handle: RePEc:eee:renene:v:157:y:2020:i:c:p:754-768
    DOI: 10.1016/j.renene.2020.04.123
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120306613
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.04.123?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. Bosch, Jonathan & Staffell, Iain & Hawkes, Adam D., 2018. "Temporally explicit and spatially resolved global offshore wind energy potentials," Energy, Elsevier, vol. 163(C), pages 766-781.
    2. González-Longatt, F. & Wall, P. & Terzija, V., 2012. "Wake effect in wind farm performance: Steady-state and dynamic behavior," Renewable Energy, Elsevier, vol. 39(1), pages 329-338.
    3. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    4. Dongheon Shin & Kyungnam Ko, 2019. "Application of the Nacelle Transfer Function by a Nacelle-Mounted Light Detection and Ranging System to Wind Turbine Power Performance Measurement," Energies, MDPI, vol. 12(6), pages 1-15, March.
    5. Shin, Dongheon & Ko, Kyungnam, 2017. "Comparative analysis of degradation rates for inland and seaside wind turbines in compliance with the International Electrotechnical Commission standard," Energy, Elsevier, vol. 118(C), pages 1180-1186.
    6. Schallenberg-Rodriguez, Julieta, 2013. "A methodological review to estimate techno-economical wind energy production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 272-287.
    7. Dai, Juchuan & Liu, Deshun & Wen, Li & Long, Xin, 2016. "Research on power coefficient of wind turbines based on SCADA data," Renewable Energy, Elsevier, vol. 86(C), pages 206-215.
    8. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
    9. Pfenninger, Stefan & DeCarolis, Joseph & Hirth, Lion & Quoilin, Sylvain & Staffell, Iain, 2017. "The importance of open data and software: Is energy research lagging behind?," Energy Policy, Elsevier, vol. 101(C), pages 211-215.
    10. Jie Tian & Dao Zhou & Chi Su & Mohsen Soltani & Zhe Chen & Frede Blaabjerg, 2017. "Wind Turbine Power Curve Design for Optimal Power Generation in Wind Farms Considering Wake Effect," Energies, MDPI, vol. 10(3), pages 1-19, March.
    11. Staffell, Iain & Green, Richard, 2014. "How does wind farm performance decline with age?," Renewable Energy, Elsevier, vol. 66(C), pages 775-786.
    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. Al Afif, Rafat & Ayed, Yasmine & Maaitah, Omer Nawaf, 2023. "Feasibility and optimal sizing analysis of hybrid renewable energy systems: A case study of Al-Karak, Jordan," Renewable Energy, Elsevier, vol. 204(C), pages 229-249.
    2. Cabrera, Pedro & Carta, José A. & Matos, Carlos & Rosales-Asensio, Enrique & Lund, Henrik, 2024. "Reduced desalination carbon footprint on islands with weak electricity grids. The case of Gran Canaria," Applied Energy, Elsevier, vol. 358(C).
    3. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    4. Yongnian Zhao & Yu Xue & Shanhong Gao & Jundong Wang & Qingcai Cao & Tao Sun & Yan Liu, 2022. "Computation and Analysis of an Offshore Wind Power Forecast: Towards a Better Assessment of Offshore Wind Power Plant Aerodynamics," Energies, MDPI, vol. 15(12), pages 1-17, June.
    5. Sebastiani, Alessandro & Peña, Alfredo & Troldborg, Niels, 2023. "Numerical evaluation of multivariate power curves for wind turbines in wakes using nacelle lidars," Renewable Energy, Elsevier, vol. 202(C), pages 419-431.
    6. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    7. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    8. Yang, Jian & Wang, Li & Song, Dongran & Huang, Chaoneng & Huang, Liansheng & Wang, Junlei, 2022. "Incorporating environmental impacts into zero-point shifting diagnosis of wind turbines yaw angle," Energy, Elsevier, vol. 238(PA).
    9. Mehrjoo, Mehrdad & Jafari Jozani, Mohammad & Pawlak, Miroslaw, 2021. "Toward hybrid approaches for wind turbine power curve modeling with balanced loss functions and local weighting schemes," Energy, Elsevier, vol. 218(C).
    10. Yang, Mao & Shi, Chaoyu & Liu, Huiyu, 2021. "Day-ahead wind power forecasting based on the clustering of equivalent power curves," Energy, Elsevier, vol. 218(C).
    11. Fortes, Patrícia & Simoes, Sofia G. & Amorim, Filipa & Siggini, Gildas & Sessa, Valentina & Saint-Drenan, Yves-Marie & Carvalho, Sílvia & Mujtaba, Babar & Diogo, Paulo & Assoumou, Edi, 2022. "How sensitive is a carbon-neutral power sector to climate change? The interplay between hydro, solar and wind for Portugal," Energy, Elsevier, vol. 239(PB).
    12. Davide Astolfi & Francesco Castellani & Andrea Lombardi & Ludovico Terzi, 2021. "Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring," Energies, MDPI, vol. 14(4), pages 1-18, February.
    13. Usama Aziz & Sylvie Charbonnier & Christophe Berenguer & Alexis Lebranchu & Frederic Prevost, 2022. "A Multi-Turbine Approach for Improving Performance of Wind Turbine Power-Based Fault Detection Methods," Energies, MDPI, vol. 15(8), pages 1-21, April.
    14. Justyna Zalewska & Krzysztof Damaziak & Jerzy Malachowski, 2021. "An Energy Efficiency Estimation Procedure for Small Wind Turbines at Chosen Locations in Poland," Energies, MDPI, vol. 14(12), pages 1-18, June.
    15. Francisco Bilendo & Angela Meyer & Hamed Badihi & Ningyun Lu & Philippe Cambron & Bin Jiang, 2022. "Applications and Modeling Techniques of Wind Turbine Power Curve for Wind Farms—A Review," Energies, MDPI, vol. 16(1), pages 1-38, December.
    16. López Prol, Javier & de Llano Paz, Fernando & Calvo-Silvosa, Anxo & Pfenninger, Stefan & Staffell, Iain, 2024. "Wind-solar technological, spatial and temporal complementarities in Europe: A portfolio approach," Energy, Elsevier, vol. 292(C).
    17. Wang, Peng & Li, Yanting & Zhang, Guangyao, 2023. "Probabilistic power curve estimation based on meteorological factors and density LSTM," Energy, Elsevier, vol. 269(C).
    18. Sebastiani, Alessandro & Angelou, Nikolas & Peña, Alfredo, 2024. "Wind turbine power curve modelling under wake conditions using measurements from a spinner-mounted lidar," Applied Energy, Elsevier, vol. 364(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. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    2. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    3. Kies, Alexander & Schyska, Bruno U. & Bilousova, Mariia & El Sayed, Omar & Jurasz, Jakub & Stoecker, Horst, 2021. "Critical review of renewable generation datasets and their implications for European power system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    4. Bosch, Jonathan & Staffell, Iain & Hawkes, Adam D., 2018. "Temporally explicit and spatially resolved global offshore wind energy potentials," Energy, Elsevier, vol. 163(C), pages 766-781.
    5. Zhang, Hengxu & Cao, Yongji & Zhang, Yi & Terzija, Vladimir, 2018. "Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data," Applied Energy, Elsevier, vol. 216(C), pages 172-182.
    6. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    7. Höfer, Tim & Madlener, Reinhard, 2018. "Locational (In-)Efficiency of Renewable Power Generation Feeding in the Electricity Grid: A Spatial Regression Analysis," FCN Working Papers 13/2018, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised 01 Dec 2019.
    8. Kueppers, Martin & Paredes Pineda, Stephany Nicole & Metzger, Michael & Huber, Matthias & Paulus, Simon & Heger, Hans Joerg & Niessen, Stefan, 2021. "Decarbonization pathways of worldwide energy systems – Definition and modeling of archetypes," Applied Energy, Elsevier, vol. 285(C).
    9. Lombardi, Francesco & Rocco, Matteo Vincenzo & Colombo, Emanuela, 2019. "A multi-layer energy modelling methodology to assess the impact of heat-electricity integration strategies: The case of the residential cooking sector in Italy," Energy, Elsevier, vol. 170(C), pages 1249-1260.
    10. 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.
    11. Nömm, Jakob & Rönnberg, Sarah K. & Bollen, Math H.J., 2021. "Techno-economic analysis with energy flow modeling for investigating the investment risks related to consumption changes within a standalone microgrid in Sweden," Energy, Elsevier, vol. 225(C).
    12. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
    13. Brändle, Gregor & Schönfisch, Max & Schulte, Simon, 2021. "Estimating long-term global supply costs for low-carbon hydrogen," Applied Energy, Elsevier, vol. 302(C).
    14. de Aquino Ferreira, Saulo Custodio & Cyrino Oliveira, Fernando Luiz & Maçaira, Paula Medina, 2022. "Validation of the representativeness of wind speed time series obtained from reanalysis data for Brazilian territory," Energy, Elsevier, vol. 258(C).
    15. Hayes, Liam & Stocks, Matthew & Blakers, Andrew, 2021. "Accurate long-term power generation model for offshore wind farms in Europe using ERA5 reanalysis," Energy, Elsevier, vol. 229(C).
    16. Hu, Jing & Harmsen, Robert & Crijns-Graus, Wina & Worrell, Ernst, 2019. "Geographical optimization of variable renewable energy capacity in China using modern portfolio theory," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    17. Bosch, Jonathan & Staffell, Iain & Hawkes, Adam D., 2019. "Global levelised cost of electricity from offshore wind," Energy, Elsevier, vol. 189(C).
    18. Alexis Tantet & Marc Stéfanon & Philippe Drobinski & Jordi Badosa & Silvia Concettini & Anna Cretì & Claudia D’Ambrosio & Dimitri Thomopulos & Peter Tankov, 2019. "e 4 clim 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy," Energies, MDPI, vol. 12(22), pages 1-37, November.
    19. Carmona, Roberto & Miranda, Ricardo & Rodriguez, Pablo & Garrido, René & Serafini, Daniel & Rodriguez, Angel & Mena, Marcelo & Fernandez Gil, Alejandro & Valdes, Javier & Masip, Yunesky, 2024. "Assessment of the green hydrogen value chain in cases of the local industry in Chile applying an optimization model," Energy, Elsevier, vol. 300(C).
    20. Gruber, Katharina & Regner, Peter & Wehrle, Sebastian & Zeyringer, Marianne & Schmidt, Johannes, 2022. "Towards global validation of wind power simulations: A multi-country assessment of wind power simulation from MERRA-2 and ERA-5 reanalyses bias-corrected with the global wind atlas," Energy, Elsevier, vol. 238(PA).

    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:157:y:2020:i:c:p:754-768. 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.