Wind Power Pattern Forecasting Based on Projected Clustering and Classification Methods

@article{Lee2015WindPP,
  title={Wind Power Pattern Forecasting Based on Projected Clustering and Classification Methods},
  author={Heon Gyu Lee and Minghao Piao and Yong Ho Shin},
  journal={Etri Journal},
  year={2015},
  volume={37},
  pages={283-294}
}
A model that precisely forecasts how much wind power is generated is critical for making decisions on power generation and infrastructure updates. Existing studies have estimated wind power from wind speed using forecasting models such as ANFIS, SMO, k-NN, and ANN. This study applies a projected clustering technique to identify wind power patterns of wind turbines; profiles the resulting characteristics; and defines hourly and daily power patterns using wind power data collected over a year… 
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