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Evaluation of planetary boundary layer simulations for wind resource study in east of Iran

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  • Mohammadpour Penchah, Mohammadreza
  • Malakooti, Hossein
  • Satkin, Mohammad

Abstract

The usual way to collect wind data for wind resource assessment is installing wind masts, which might not be feasible due to the cost or time constraints. Conducting qualified long term numerical simulations is classified as a new method for this purpose. In this study, WRF model experiments are evaluated for simulating wind field over east of Iran. Planetary Boundary Layer (PBL) physical parameterization plays an important role in the structure of simulated low level wind field. Evaluation of PBL schemes over the study area could be an essential issue for reduction of simulated wind errors. The ACM2, MYJ, MYNN2.5, QNSE and YSU PBL schemes are evaluated during July and December 2007. The MYJ PBL scheme showed the best performance for Fadeshk area. We then carried out one-year simulations for the whole of 2007 and simulated wind field and wind energy productions compared to the measurement wind data. Wind distribution during 2007 was simulated well with this PBL scheme, although it showed overestimations over 3 a.m. – 8 p.m. of day and underestimation over 8 p.m. -3 a.m. Relative errors for shape parameter, scale parameter, mean of Weibull distribution and wind power are estimated equal to 13.2%, 5.54%, 4.85% and −0.47% respectively. Overall, model has good performance in simulation of wind energy parameters in this area.

Suggested Citation

  • Mohammadpour Penchah, Mohammadreza & Malakooti, Hossein & Satkin, Mohammad, 2017. "Evaluation of planetary boundary layer simulations for wind resource study in east of Iran," Renewable Energy, Elsevier, vol. 111(C), pages 1-10.
    • Handle: RePEc:eee:renene:v:111:y:2017:i:c:p:1-10
    DOI: 10.1016/j.renene.2017.03.040
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    Cited by:

    1. González-Alonso de Linaje, N. & Mattar, C. & Borvarán, D., 2019. "Quantifying the wind energy potential differences using different WRF initial conditions on Mediterranean coast of Chile," Energy, Elsevier, vol. 188(C).
    2. Sward, J.A. & Ault, T.R. & Zhang, K.M., 2022. "Genetic algorithm selection of the weather research and forecasting model physics to support wind and solar energy integration," Energy, Elsevier, vol. 254(PB).
    3. Denis E.K. Dzebre & Muyiwa S. Adaramola, 2019. "Impact of Selected Options in the Weather Research and Forecasting Model on Surface Wind Hindcasts in Coastal Ghana," Energies, MDPI, vol. 12(19), pages 1-16, September.
    4. Yang, Jaemo & Sengupta, Manajit & Xie, Yu & Shin, Hyeyum Hailey, 2023. "Developing a 20-year high-resolution wind data set for Puerto Rico," Energy, Elsevier, vol. 285(C).
    5. Xsitaaz T. Chadee & Naresh R. Seegobin & Ricardo M. Clarke, 2017. "Optimizing the Weather Research and Forecasting (WRF) Model for Mapping the Near-Surface Wind Resources over the Southernmost Caribbean Islands of Trinidad and Tobago," Energies, MDPI, vol. 10(7), pages 1-23, July.
    6. Mylonas, M.P. & Barbouchi, S. & Herrmann, H. & Nastos, P.T., 2018. "Sensitivity analysis of observational nudging methodology to reduce error in wind resource assessment (WRA) in the North Sea," Renewable Energy, Elsevier, vol. 120(C), pages 446-456.
    7. Dzebre, Denis E.K. & Adaramola, Muyiwa S., 2020. "A preliminary sensitivity study of Planetary Boundary Layer parameterisation schemes in the weather research and forecasting model to surface winds in coastal Ghana," Renewable Energy, Elsevier, vol. 146(C), pages 66-86.
    8. D’Isidoro, Massimo & Briganti, Gino & Vitali, Lina & Righini, Gaia & Adani, Mario & Guarnieri, Guido & Moretti, Lorenzo & Raliselo, Muso & Mahahabisa, Mabafokeng & Ciancarella, Luisella & Zanini, Gabr, 2020. "Estimation of solar and wind energy resources over Lesotho and their complementarity by means of WRF yearly simulation at high resolution," Renewable Energy, Elsevier, vol. 158(C), pages 114-129.
    9. Perini de Souza, Noele Bissoli & Sperandio Nascimento, Erick Giovani & Bandeira Santos, Alex Alisson & Moreira, Davidson Martins, 2022. "Wind mapping using the mesoscale WRF model in a tropical region of Brazil," Energy, Elsevier, vol. 240(C).
    10. Herrero-Novoa, Cristina & Pérez, Isidro A. & Sánchez, M. Luisa & García, Ma Ángeles & Pardo, Nuria & Fernández-Duque, Beatriz, 2017. "Wind speed description and power density in northern Spain," Energy, Elsevier, vol. 138(C), pages 967-976.

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