JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (4): 111-116.doi: 10.6040/j.issn.1672-3961.0.2016.235

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Analysis of spatial and temporal distribution of wind power output and variation characteristics based on NASA observation data

LIU Xiaoming1, NIU Xinsheng1, ZHANG Yi2, CAO Benqing2, SHI Xiaohan2,ZHANG Youquan3, ZHANG Jie1, AN Peng3, WANG Yuan3   

  1. 1. Economic &
    Technology Research Institute, State Grid Shandong Electirc Power Company, Jinan 250001, Shandong, China;
    2. Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education(Shandong University), Jinan 250061, Shandong, China;
    3. State Grid Shandong Electirc Power Company, Jinan 250001, Shandong, China
  • Received:2016-06-29 Online:2016-08-20 Published:2016-06-29

Abstract: In order to overcome the difficulties of acquiring operation data of the practical wind farms, an estimation method of wind energy resources based on the history wind speed has been put forward. First, the wind speed data was acquired from the NASA data center and was converted to the the output sequence of an imaginary wind turbine, and then the indexes such as expectation and probability of half load were calculated by statically analyisis of the wind turbine output sequence to evaluate the spatial and temporal distribution of the wind energy. Finally, the variance of the wind power output as well as the statistical law of the wind power output differences between adjacent peak and valley points were calculated to analyze the variation characteristics of the wind energy. The proposed method could take the nature of wind energy resources as well as the characteristics of wind turbine into consideration and quantitatively describe the variance of the wind power ouput. The method was used to analyze the wind energy resources in Shandong Province and the results showed that the technological available wind energy varies with regions, seasons as well as day and night in an obvious law.

Key words: spatial and temporal distribution, variation characteristic analysis, wind turbine characteristic, wind energy resource estimation, probability and statistics

CLC Number: 

  • TM315
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