4.6 Article

Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea

Journal

ENERGY REPORTS
Volume 7, Issue -, Pages 7358-7373

Publisher

ELSEVIER
DOI: 10.1016/j.egyr.2021.10.078

Keywords

Wind speed; Weibull distribution; Weibull parameter; Estimation methods; Statistical analysis

Categories

Funding

  1. Korea Institute of Energy Technology Evaluation and Planning (KETEP) of the Republic of Korea [20194030202300]
  2. Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea [20194030202300]
  3. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF2021R1A6A1A0304518511]
  4. Korea Evaluation Institute of Industrial Technology (KEIT) [20194030202300] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This study analyzed 10 years of wind speed data in Maldo island and Saemangeum seawall in Korea, comparing 12 Weibull parameter estimation methods to identify the most reliable and efficient ones. Results showed varying accuracies among different methods in predicting wind speed distributions, with some methods performing better than others.
The Weibull probability distribution indicates the probability of a specific wind speed and must be calculated before wind turbine installation. The Weibull distribution is affected by shape and scale parameters, which are driven in various ways. Many studies have conducted research to determine a more reliable method among various Weibull parameter estimation methods. However, since these studies showed different results, studies on determining the higher reliable Weibull parameter estimation methods continues. In this study, we analyzed 10 years of data collected at the same location and height level in Maldo island(from 2010 to 2019) and Saemangeum seawall (from 2011 to 2012), the Republic of Korea. While former studies tried to rank the Weibull distribution methods based on the statistical analyses, in this study, we compared the Weibull parameters using twelve methods and identified the highest reliable and efficient methods for deriving the Weibull probability distribution by using the new approach comparing the variance of RMSE, R-2 , and chi(2) , which give a comprehensive insight about the level and fluctuations errors. These twelve methods are Alternative maximum likelihood method, Equivalent energy method, Empirical method of Justus, Empirical method of Lysen, Energy pattern factor method, Graphical method, Modified energy pattern factor method, Maximum likelihood method, Moment method, Modified maximum likelihood method, Power density method, Standard deviation method. The results showed while Empirical method of Justus, Empirical method of Lysen, Moment method, and Standard deviation method had the best accuracies in prediction of wind speed distribution, some methods such as Graphical method, Alternative maximum likelihood method, Equivalent energy method, and Energy pattern factor method had the worst prediction of wind speed distribution based on all variance of statistical methods for both regions. (C) 2021 The Authors. Published by Elsevier Ltd.

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