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A new method for wind speed forecasting based on copula theory.
Wang, Yuankun; Ma, Huiqun; Wang, Dong; Wang, Guizuo; Wu, Jichun; Bian, Jinyu; Liu, Jiufu.
Affiliation
  • Wang Y; Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing 210023, China.
  • Ma H; Shandong Electric Power Engineering Consulting Institute Corp, Ltd., Jinan 250013, China.
  • Wang D; Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing 210023, China. Electronic address: wangdong@nju.edu.cn.
  • Wang G; Development Research Center of the Ministry of Water Resources, Beijing 100038, China.
  • Wu J; Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing 210023, China.
  • Bian J; Nanjing Hydraulic Research Institute, Nanjing 210029, China.
  • Liu J; Nanjing Hydraulic Research Institute, Nanjing 210029, China.
Environ Res ; 160: 365-371, 2018 01.
Article in En | MEDLINE | ID: mdl-29073570
ABSTRACT
How to determine representative wind speed is crucial in wind resource assessment. Accurate wind resource assessments are important to wind farms development. Linear regressions are usually used to obtain the representative wind speed. However, terrain flexibility of wind farm and long distance between wind speed sites often lead to low correlation. In this study, copula method is used to determine the representative year's wind speed in wind farm by interpreting the interaction of the local wind farm and the meteorological station. The result shows that the method proposed here can not only determine the relationship between the local anemometric tower and nearby meteorological station through Kendall's tau, but also determine the joint distribution without assuming the variables to be independent. Moreover, the representative wind data can be obtained by the conditional distribution much more reasonably. We hope this study could provide scientific reference for accurate wind resource assessments.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Wind / Meteorology / Forecasting Type of study: Prognostic_studies Language: En Journal: Environ Res Year: 2018 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Wind / Meteorology / Forecasting Type of study: Prognostic_studies Language: En Journal: Environ Res Year: 2018 Type: Article Affiliation country: China