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Investigation of wind resource characteristics in mountain wind farm using multiple-unit SCADA data in Chenzhou: A case study

Lookup NU author(s): Dr Juchuan Dai, Dr Wenxian YangORCiD



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Wind resource characteristics in a mountain wind farm is more complicated and changeable than that in a flat wind farm due to the influence of complex mountain terrain-topography on air flow. Although there have been a large number of investigations on wind resource characteristics, the local wind resource characteristics in a mountain wind farm are still a lack. To fill this knowledge gap, high-resolution wind data are extracted for investigating from multiple-unit SCADA data, that is, wind data are collected from four selected wind turbines with SCADA system, which means wind data are from four different locations. For each location, more than thirty million sets of wind data are extracted for investigation in 2015. Then, several kinds of probability density functions (PDFs) are compared, and one-dimensional and multidimensional kernel density estimation method is selected for the investigation of the frequency distribution. Data preprocessing methods of both wind speed and wind direction are also presented. Finally, the results of this investigation reveal the specific change characteristics of wind speed and wind direction in the investigated mountain wind farm. Yearly mean wind speeds for four different locations are 3.8m/s, 5.1m/s, 5.4m/s and 5.6m/s, respectively.

Publication metadata

Author(s): Dai J, Tan Y, Yang W, Wen L, Shen X

Publication type: Article

Publication status: Published

Journal: Energy Conversion and Management

Year: 2017

Volume: 148

Pages: 378-393

Print publication date: 15/09/2017

Online publication date: 13/06/2017

Acceptance date: 30/05/2017

Date deposited: 28/06/2017

ISSN (print): 0196-8904

ISSN (electronic): 1879-2227

Publisher: Elsevier


DOI: 10.1016/j.enconman.2017.05.075


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