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  • 标题:STUDY OF WIND POWER SHORT-TERM PREDICTION OF WIND FARM BASED ON NWP AND FUZZY NEURAL NETWORK
  • 本地全文:下载
  • 作者:GU BO ; AN CHAO ; LIU XINYU
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2013
  • 卷号:48
  • 期号:3
  • 出版社:Journal of Theoretical and Applied
  • 摘要:

    Wind power prediction of wind farm plays a decisive role in stable electric power system operation. Firstly to introduce fuzzy neural network�s basic principle; secondly to use 60 days numerical weather prediction (NWP) data and power data, from Jun.08 to Aug.08, as the training data of fuzzy neural network to train the fuzzy neural network; finally to use the next 2 days NWP data, from Aug.09 to Aug.10 as input data of fuzzy neural network, to predict the next 2 days output power of wind farm. The training process and prediction result show that fuzzy neural network has fuzzy decision and judgment, and has good self-learning and adaptive ability, which improves the stability of prediction system and prediction accuracy.

  • 关键词:Wind Power Prediction Of Wind Farm; Numerical Weather Prediction (NWP); Fuzzy Neural Network; Prediction Error
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