Statistical Analysis of Wind Resource Assessment for Different Locations in South-Western Thailand

Authors

  • Attapon Chumapan Energy Technology Program, Faculty of Engineering, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand
  • Paramin Neranon Department of Mechanical and Mechatronics Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand
  • Juntakan Taweekun Department of Mechanical and Mechatronics Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand

DOI:

https://doi.org/10.37934/arfmts.118.2.87100

Keywords:

Weibull distribution, Weibull parameters, Soot formation, graphical method, energy pattern factor method, maximum likelihood method

Abstract

Weibull parameters have been widely used to evaluate wind energy potential. In this work presents wind resource assessment by statistical analysis with a Weibull distribution model for Krabi, Phuket, and Ranong weather stations in south-western Thailand. Ten-minute intervals include wind speed and wind direction of 10m from four-year records obtained by the Thai meteorological department. Four numerical methods, namely empirical method, graphical method, energy pattern factor method and maximum likelihood method are examined to estimate the Weibull parameters. The Weibull distribution obtained from each method is compared with the observed wind speed distribution by the performance tests using root mean square error, mean percentage error, and chi-square error to select a suitable method for the station area. The results revealed that the maximum likelihood method was the most accurate for Krabi and Phuket stations, and the energy pattern factor method was the most accurate for Ranong station. At a hub height of 80m, the highest mean wind speed and mean wind power density found in Krabi station were 3.25 m/s and 44.84 W/m2. The most probable wind speed value in three stations had a range from 1.80 to 2.50 m/s. The maximum wind speed carrying maximum energy found in Krabi station was 5.53 m/s. The operating probability of a wind turbine in Krabi station was 49.61%, followed by Phuket station was 46.80%, and Ranong station was 37.84%, respectively. In conclusion, all three stations had wind power potential classified as wind class 1 and can be sorted as follows: Krabi, Phuket, and Ranong stations.

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Author Biographies

Attapon Chumapan, Energy Technology Program, Faculty of Engineering, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand

ongattapon2021@gmail.com

Paramin Neranon, Department of Mechanical and Mechatronics Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand

nparamin@me.psu.ac.th

Juntakan Taweekun, Department of Mechanical and Mechatronics Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand

juntakan.t@psu.ac.th

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Published

2024-06-30

How to Cite

Attapon Chumapan, Paramin Neranon, & Juntakan Taweekun. (2024). Statistical Analysis of Wind Resource Assessment for Different Locations in South-Western Thailand. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 118(2), 87–100. https://doi.org/10.37934/arfmts.118.2.87100

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