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The Probability Density Function for Wind Speed Using Modified Weibull Distribution

Author

Listed:
  • Suwarno Suwarno

    (Department of Electrical Engineering, Universitas Muhammadiyah Sumatera Utara, Indonesia)

  • M. Fitra Zambak

    (Department of Electrical Engineering, Universitas Muhammadiyah Sumatera Utara, Indonesia)

Abstract

Wind speed (WS) is important information to determine the potential for wind energy in an area. Wind speed has been widely expressed by the probability density function (Pdf), one of which uses the Weibull Distribution (WD). Not all WS data can be analyzed by WD because some deficiencies need to be corrected. Modified Weibull Distribution (MWD) is proposed to improve the existing WD models. In addition, this paper also compares the performance of MWD against WD using WS data measured in Medan City. To validate the two models (WD and MWD), the coefficient of determination (R-squared) and the mean square root error (RMSE) were used. In addition, data validation tests were also carried out using Chi-square and Kolmogorov-Smirnov. The result obtained is that MWD has a more acceptable fit than WD for this case.

Suggested Citation

  • Suwarno Suwarno & M. Fitra Zambak, 2021. "The Probability Density Function for Wind Speed Using Modified Weibull Distribution," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 544-550.
    • Handle: RePEc:eco:journ2:2021-06-62
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    References listed on IDEAS

    as
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    Cited by:

    1. 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.
    2. Abdulaziz S. Alghamdi & M. M. Abd El-Raouf, 2023. "A New Alpha Power Cosine-Weibull Model with Applications to Hydrological and Engineering Data," Mathematics, MDPI, vol. 11(3), pages 1-25, January.
    3. Mohammed Chakib Sekkal & Zakarya Ziani & Moustafa Yassine Mahdad & Sidi Mohammed Meliani & Mohammed Haris Baghli & Mohammed Zakaria Bessenouci, 2024. "Assessing the Wind Power Potential in Naama, Algeria to Complement Solar Energy through Integrated Modeling of the Wind Resource and Turbine Wind Performance," Energies, MDPI, vol. 17(4), pages 1-34, February.
    4. Janter Napitupulu & Suwarno Suwarno & Catra Indra Cahyadi & Sukarwoto Sukarwoto, 2024. "Evaluation and Modeling of Green Energy Consumption in North Sumatra, Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 14(1), pages 570-578, January.

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    More about this item

    Keywords

    Wind speed; Distribution function; Weibull distribution; Modified Weibull distribution;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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