1038 / 2019-05-18 17:36:15
Turbine Location Wind Speed Prediction Using Convolutional Neural Network
Convolutional neural network,deep learning,multi-task prediction,wind farm,wind speed forecast
全文录用
Tianhu Wan / State Grid Shaanxi Electric Power Research Institutes
Hua Li / State Grid Shaanxi Electric Power Research Institutes
Chen Wang / Xi’an Jiaotong University
Peng Kou / Xi’an Jiaotong University
Traditional wind speed forecast usually regards wind farm as a point to make forecast, but in a wind farm, wind speed of wind turbines in different geographical locations is not the same. For many wind turbines with wide geographical distribution in a wind farm, this paper gives a forecast method based on convolutional neural network (CNN) to forecast the wind speed at each wind turbine location. In this method, the wind speed and direction characteristics of all wind turbines at different geographical locations are input into the CNN network as variables, and local low-dimensional features of the original data are mapped to high-dimensional features through convolution operation of CNN, thereby realizing the wind speed forecast. The main advantage of this method is that by automatically studying the informative spatial correlation of wind speed, rather than artificial extracting , multi-task forecasts(MTF)are made and the wind speed forecast at different wind turbines locations is more informative and accurate.
重要日期
  • 会议日期

    10月21日

    2019

    10月24日

    2019

  • 10月13日 2019

    摘要录用通知日期

  • 10月13日 2019

    初稿截稿日期

  • 10月14日 2019

    初稿录用通知日期

  • 10月24日 2019

    注册截止日期

  • 10月29日 2019

    终稿截稿日期

承办单位
Xi'an Jiaotong University
联系方式
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询