电测与仪表2018，Vol.55Issue(11)：120-124,5.
基于决策树理论的风电功率实时预测方法
Real-time wind power forecasting method based on decision tree theory
摘要
Abstract
The uncertainty of wind power will cause the impact to power grid.Real-time forecasting of wind power can ease the frequency modulation pressure and ensure the stability of the power grid.Based on the analysis of the characteristics of two kinds of single forecasting models,a combined forecasting model is proposed based on historical data and NWP data.The decision tree classification model is established based on the analysis of sequence feature of the historical data and the applicable forecasting method.The best forecasting method is selected by real-time data sequence feature analysis.The results show that the combined model can forecast the accuracy higher than that of the single model.Real-time sequence feature analysis and the best forecasting model matching can improve the prediction accuracy by the decision tree model.关键词
风电功率/实时预测/组合模型/序列特性/决策树Key words
wind power/real-time prediction/combinatorial model/sequence property/decision tree分类
信息技术与安全科学引用本文复制引用
杨茂,翟冠强..基于决策树理论的风电功率实时预测方法[J].电测与仪表,2018,55(11):120-124,5.基金项目
国家重点研发计划项目(2008YFB0904200) （2008YFB0904200）
