IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v53y2013icp306-318.html
   My bibliography  Save this article

Wind energy analysis based on turbine and developed site power curves: A case-study of Darling City

Author

Listed:
  • Olaofe, Zaccheus O.
  • Folly, Komla A.

Abstract

The observed wind at a given site varies continuously as a function of time and season, increasing hub heights, topography of the terrain, prevailing weather condition etc. The quality of wind resource is one of the important site factors to be considered when assessing the wind potential of any location for any energy project. In this study, two wind energy analysis techniques are presented: the use of direct technique where the electrical power outputs of the wind turbines at a time t are estimated using the turbine power curve(s) and the use of statistical-based technique where the power outputs are estimated based on the developed site power curve(s). The wind resource assessment at Darling site is conducted using a 5-min time series weather data collected on a 10 m height over a period of 24 months. Because of the non-linearity of the site's wind speed and its corresponding power output, the wind resources are modeled and the developed site power curve(s) are used to estimate the long term energy outputs of the wind turbines for changing weather conditions. Three wind turbines rating of 1.3 MW, 1.3 MW and 1.0 MW were selected for the energy generation based on the gauged wind resource(s) at 50, 60 and 70 m heights, respectively. The energy outputs at 50 m height using the 1.3 MW WT were compared to the energy outputs at 60 m to determine the standard height for utility scale energy generation at this site. An additional energy generation of 190.71 MWh was available by deploying the same rated turbine at a 60 m height. Furthermore, comparisons were made between the use of turbine and site power curve for wind energy analysis at the considered heights. The results show that the analysis of the energy outputs of the WTs based on the site power curve is an accurate technique for wind energy analysis as compared to the turbine power curve. Conclusions are drawn on the suitability of this site for utility scale generation based on the wind resources evaluation at different heights.

Suggested Citation

  • Olaofe, Zaccheus O. & Folly, Komla A., 2013. "Wind energy analysis based on turbine and developed site power curves: A case-study of Darling City," Renewable Energy, Elsevier, vol. 53(C), pages 306-318.
    • Handle: RePEc:eee:renene:v:53:y:2013:i:c:p:306-318
    DOI: 10.1016/j.renene.2012.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148112006945
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2012.11.003?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. Fyrippis, Ioannis & Axaopoulos, Petros J. & Panayiotou, Gregoris, 2010. "Wind energy potential assessment in Naxos Island, Greece," Applied Energy, Elsevier, vol. 87(2), pages 577-586, February.
    2. Sfetsos, A., 2000. "A comparison of various forecasting techniques applied to mean hourly wind speed time series," Renewable Energy, Elsevier, vol. 21(1), pages 23-35.
    3. Algifri, Abdulla H., 1998. "Wind energy potential in Aden-Yemen," Renewable Energy, Elsevier, vol. 13(2), pages 255-260.
    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. Samuel Van Ackere & Greet Van Eetvelde & David Schillebeeckx & Enrica Papa & Karel Van Wyngene & Lieven Vandevelde, 2015. "Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods," Energies, MDPI, vol. 8(8), pages 1-22, August.
    2. Yang, An-Shik & Su, Ying-Ming & Wen, Chih-Yung & Juan, Yu-Hsuan & Wang, Wei-Siang & Cheng, Chiang-Ho, 2016. "Estimation of wind power generation in dense urban area," Applied Energy, Elsevier, vol. 171(C), pages 213-230.
    3. Juan, Y.-H. & Wen, C.-Y. & Chen, W.-Y. & Yang, A.-S., 2021. "Numerical assessments of wind power potential and installation arrangements in realistic highly urbanized areas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    4. Ruiz de la Hermosa González-Carrato, Raúl, 2018. "Wind farm monitoring using Mahalanobis distance and fuzzy clustering," Renewable Energy, Elsevier, vol. 123(C), pages 526-540.
    5. Soheyli, Saman & Shafiei Mayam, Mohamad Hossein & Mehrjoo, Mehri, 2016. "Modeling a novel CCHP system including solar and wind renewable energy resources and sizing by a CC-MOPSO algorithm," Applied Energy, Elsevier, vol. 184(C), pages 375-395.
    6. Pang, Kang Ying & Liew, Peng Yen & Woon, Kok Sin & Ho, Wai Shin & Wan Alwi, Sharifah Rafidah & Klemeš, Jiří Jaromír, 2023. "Multi-period multi-objective optimisation model for multi-energy urban-industrial symbiosis with heat, cooling, power and hydrogen demands," Energy, Elsevier, vol. 262(PA).
    7. Watts, David & Oses, Nicolás & Pérez, Rodrigo, 2016. "Assessment of wind energy potential in Chile: A project-based regional wind supply function approach," Renewable Energy, Elsevier, vol. 96(PA), pages 738-755.
    8. Allouhi, A. & Zamzoum, O. & Islam, M.R. & Saidur, R. & Kousksou, T. & Jamil, A. & Derouich, A., 2017. "Evaluation of wind energy potential in Morocco's coastal regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 311-324.
    9. Santos, E.C.O. & Guedes, E.F. & Zebende, G.F. & da Silva Filho, A.M., 2022. "Autocorrelation of wind speed: A sliding window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    10. Lydia, M. & Kumar, S. Suresh & Selvakumar, A. Immanuel & Prem Kumar, G. Edwin, 2014. "A comprehensive review on wind turbine power curve modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 452-460.

    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. Yip, Chak Man Andrew & Gunturu, Udaya Bhaskar & Stenchikov, Georgiy L., 2016. "Wind resource characterization in the Arabian Peninsula," Applied Energy, Elsevier, vol. 164(C), pages 826-836.
    2. Birgir Freyr Ragnarsson & Gudmundur V. Oddsson & Runar Unnthorsson & Birgir Hrafnkelsson, 2015. "Levelized Cost of Energy Analysis of a Wind Power Generation System at Búrfell in Iceland," Energies, MDPI, vol. 8(9), pages 1-22, September.
    3. Fazelpour, Farivar & Markarian, Elin & Soltani, Nima, 2017. "Wind energy potential and economic assessment of four locations in Sistan and Balouchestan province in Iran," Renewable Energy, Elsevier, vol. 109(C), pages 646-667.
    4. Munir Ali Elfarra & Mustafa Kaya, 2018. "Comparison of Optimum Spline-Based Probability Density Functions to Parametric Distributions for the Wind Speed Data in Terms of Annual Energy Production," Energies, MDPI, vol. 11(11), pages 1-15, November.
    5. Hu, Jianming & Wang, Jianzhou & Zeng, Guowei, 2013. "A hybrid forecasting approach applied to wind speed time series," Renewable Energy, Elsevier, vol. 60(C), pages 185-194.
    6. Rana Muhammad Adnan & Zhongmin Liang & Xiaohui Yuan & Ozgur Kisi & Muhammad Akhlaq & Binquan Li, 2019. "Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation," Energies, MDPI, vol. 12(2), pages 1-22, January.
    7. Ata, Rasit, 2015. "Artificial neural networks applications in wind energy systems: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 534-562.
    8. Zhao, Jing & Guo, Zhen-Hai & Su, Zhong-Yue & Zhao, Zhi-Yuan & Xiao, Xia & Liu, Feng, 2016. "An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed," Applied Energy, Elsevier, vol. 162(C), pages 808-826.
    9. Liu, Hui & Tian, Hong-qi & Pan, Di-fu & Li, Yan-fei, 2013. "Forecasting models for wind speed using wavelet, wavelet packet, time series and Artificial Neural Networks," Applied Energy, Elsevier, vol. 107(C), pages 191-208.
    10. Islam, M.R. & Saidur, R. & Rahim, N.A., 2011. "Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function," Energy, Elsevier, vol. 36(2), pages 985-992.
    11. Xydis, G. & Koroneos, C. & Loizidou, M., 2009. "Exergy analysis in a wind speed prognostic model as a wind farm sitting selection tool: A case study in Southern Greece," Applied Energy, Elsevier, vol. 86(11), pages 2411-2420, November.
    12. Daojun Chen & Qingwu Gong & Bichang Zou & Xiaohui Zhang & Jian Zhao, 2012. "A Low-Carbon Dispatch Model in a Wind Power Integrated System Considering Wind Speed Forecasting and Energy-Environmental Efficiency," Energies, MDPI, vol. 5(4), pages 1-26, April.
    13. Muhammad Fitra Zambak & Catra Indra Cahyadi & Jufri Helmi & Tengku Machdhalie Sofie & Suwarno Suwarno, 2023. "Evaluation and Analysis of Wind Speed with the Weibull and Rayleigh Distribution Models for Energy Potential Using Three Models," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 427-432, March.
    14. Wei Fang & Cheng Yang & Dengfeng Liu & Qiang Huang & Bo Ming & Long Cheng & Lu Wang & Gang Feng & Jianan Shang, 2023. "Assessment of Wind and Solar Power Potential and Their Temporal Complementarity in China’s Northwestern Provinces: Insights from ERA5 Reanalysis," Energies, MDPI, vol. 16(20), pages 1-23, October.
    15. Khraiwish Dalabeeh, Ali S., 2017. "Techno-economic analysis of wind power generation for selected locations in Jordan," Renewable Energy, Elsevier, vol. 101(C), pages 1369-1378.
    16. Mostafaeipour, Ali & Jadidi, Mohsen & Mohammadi, Kasra & Sedaghat, Ahmad, 2014. "An analysis of wind energy potential and economic evaluation in Zahedan, Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 641-650.
    17. Celik, Ali N., 2011. "Review of Turkey's current energy status: A case study for wind energy potential of Çanakkale province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2743-2749, August.
    18. Chang, Tian-Pau & Ko, Hong-Hsi & Liu, Feng-Jiao & Chen, Pai-Hsun & Chang, Ying-Pin & Liang, Ying-Hsin & Jang, Horng-Yuan & Lin, Tsung-Chi & Chen, Yi-Hwa, 2012. "Fractal dimension of wind speed time series," Applied Energy, Elsevier, vol. 93(C), pages 742-749.
    19. Deep, Sneh & Sarkar, Arnab & Ghawat, Mayur & Rajak, Manoj Kumar, 2020. "Estimation of the wind energy potential for coastal locations in India using the Weibull model," Renewable Energy, Elsevier, vol. 161(C), pages 319-339.
    20. Ajlan, Abdullah & Tan, Chee Wei & Abdilahi, Abdirahman Mohamed, 2017. "Assessment of environmental and economic perspectives for renewable-based hybrid power system in Yemen," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 559-570.

    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:53:y:2013:i:c:p:306-318. 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.