Deterministic and Probabilistic Prediction of Wind Power Based on a Hybrid Intelligent Model

Jiawei Zhang, Rongquan Zhang, Yanfeng Zhao, Jing Qiu, Siqi Bu, Yuxiang Zhu, Gangqiang Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)


Uncertainty in wind power is often unacceptably large and can easily affect the proper operation, quality of generation, and economics of the power system. In order to mitigate the potential negative impact of wind power uncertainty on the power system, accurate wind power forecasting is an essential technical tool of great value to ensure safe, stable, and efficient power generation. Therefore, in this paper, a hybrid intelligent model based on isolated forest, wavelet transform, categorical boosting, and quantile regression is proposed for deterministic and probabilistic wind power prediction. First, isolated forest is used to pre-process the original wind power data and detect anomalous data points in the power sequence. Then, the pre-processed original power sequence is decomposed into sub-frequency signals with better profiles by wavelet transform, and the nonlinear features of each sub-frequency are extracted by categorical boosting. Finally, a quantile-regression-based wind power probabilistic predictor is developed to evaluate uncertainty with different confidence levels. Moreover, the proposed hybrid intelligent model is extensively validated on real wind power data. Numerical results show that the proposed model achieves competitive performance compared to benchmark methods.

Original languageEnglish
Article number4237
Issue number10
Publication statusPublished - May 2023


  • categorical boosting
  • probabilistic predictor
  • wavelet transform
  • wind power forecasting

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Engineering (miscellaneous)
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering


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