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

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.