Document Type : ORIGINAL RESEARCH ARTICLE

Authors

Department of Agricultural Engineering, Kalasalingam Academy of Research and Education, Krishnankoil 626126, Srivilliputhur, Virudhunagar District, Tamil Nadu, India

Abstract

BACKGROUND AND OBJECTIVES: Overusing renewable resources for various purposes is making it necessary to use fewer non-renewable ones to generate energy. Finding alternative renewable energy sources is essential for energy production. This study concentrated on using wind direction and speed to produce wind energy among renewable energy sources. Data on wind direction and speed were statistically analyzed to determine the current distribution pattern, which is then used to project the amount of wind energy that will be available in the future.
METHODS: This study concentrated on choosing wind direction and speed to minimize the potential for current electricity generation from wind turbines, using data collected between 1981 and 2023. The wind speed and direction distribution pattern was assessed through the Weibull distribution, beta distribution, and three-parameter Weibull distribution. The Anderson-Darling test and the Kolmogorov-Smirnov test were employed in this study to determine the goodness-of-fit of a specific distribution. The forecasting analysis was expanded from 2024 to 2050 based on the three-parameter Weibull distribution and Anderson-Darling test results for future sustainable wind energy production.
FINDINGS: The average wind speed was found to be 6.51 meters per second, with a standard deviation of 0.280 meters per second between 1981 and 2023. The wind direction varied between a minimum of 3.56 and a maximum of 356.44 degrees for the same duration. The study discovered that the three-parameter Weibull distribution caused less error in the wind speed data distribution pattern than both the Weibull distribution and beta distribution, based on the results of the Anderson-Darling and Kolmogorov-Smirnov tests. From both the tests on Weibull distribution, beta distribution, and three-parameter Weibull distribution, this study found that the Anderson-Darling test was the most appropriate for forecasting the wind speed corresponding to the wind direction for the periods between 2024 and 2050 to produce sustainable wind energy from the wind turbine.
CONCLUSION: The outcomes of this study demonstrate that there is a good likelihood that the parameter Weibull distribution and Anderson-Darling test will be used in other nations to aid in the complementary integration of wind energy. This research has the potential to significantly reduce the amount of environmentally hazardous energy sources used to meet societal requirements. This study offers a trustworthy technique for assessing wind direction and speed, which helps design sustainable wind power plants, construct engineering curricula, and estimate clean, environmentally friendly energy sources.

Graphical Abstract

Wind speed and direction on predicting wind energy availability for a sustainable ecosystem

Highlights

  • The results imply that more successful micrositing tactics for wind turbines inside a wind farm result from taking into account both wind speed and direction unpredictability;
  • The results offer grid dependability and stability, which necessitates comprehension of the relationship between wind direction, speed, and energy output;
  • Studies have indicated that to preserve system stability and balance supply and demand, wind energy projections must be incorporated into grid management techniques;
  • Research results have an impact on how wind energy-related regulations and policies are developed.

Keywords

Main Subjects

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