To solve the problem of difficulty in accurately predicting wind power using a single prediction model,a short-term wind power prediction method based on principal component analysis(PCA),adaptive boosting(Adaboost),and gradient boosting decision tree(GBDT)was proposed.The PCA method was used to reduce the dimension of the data,and the Adaboost-GBDT combined model was used to train the wind power data.The results show that the proposed algorithm has significant advantages in accuracy and efficiency.The research results provide reference and guidance for accurate prediction of wind power.
关键词
风电功率/功率预测/梯度提升树/自适应增强/组合模型
Key words
wind power/power prediction/gradient boosting decision tree(GBDT)/adaptive boosting(Adaboost)/combined model
维普
万方数据