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The Gaussian-Enhanced Rayleigh Distribution (GERD): A Hybrid Model for Wind Speed and Power Output Estimation in Tokyo

Author

Listed:
  • Flowery Francis

    (Associate Professor, Department of Statistics, Sri. C. Achuthamenon Government College, Thrissur)

  • Jeena Joseph

    (Assistant Professor, Department of Statistics, St. Thomas College (Autonomous), Thrissur)

Abstract

In this paper, we came up with the Gaussian-Enhanced Rayleigh Distribution (GERD), a mix of Rayleigh and Gaussian parts, to see if it could do a better job with wind speed data. For testing, we used monthly records from Tokyo between 2000 and 2020. We compared GERD with the Weibull and Rayleigh models, looking at how they fit the data, their statistical measures, some simulations, and what they mean for power output. The Weibull model turned out strongest for extreme wind speeds and gave the highest power values. Rayleigh came out too low. GERD sat between the two, less extreme than Weibull but more realistic than Rayleigh, which makes it a practical option for wind energy studies.

Suggested Citation

  • Flowery Francis & Jeena Joseph, 2026. "The Gaussian-Enhanced Rayleigh Distribution (GERD): A Hybrid Model for Wind Speed and Power Output Estimation in Tokyo," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 11(5), pages 409-417, May.
    • Handle: RePEc:bjf:journl:v:11:y:2026:i:5:p:409-417
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
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