浙江电力2026，Vol.45Issue(1)：66-77,12.DOI:10.19585/j.zjdl.202601007
考虑多维气象数据与时间影响的风电功率区间预测
Wind power interval forecasting based on multidimensional meteorological data and temporal effects
摘要
Abstract
Existing wind power interval forecasting models based on forecasting errors typically consider only the in-fluence of wind speed while neglecting the temporal effects in the modeling process.To address these challenges,this paper proposes a wind power interval forecasting model that combines the point forecasting model of neural hier-archical interpolation for time series forecasting(N-HiTS)with the theory of generalized additive model(GAM)-D-Vine copula based quantile regression(DVQR).First,the N-HiTS is employed to obtain point predictions of wind power and corresponding forecasting errors.Then,a DVQR model for the forecasting errors is constructed,where temporal variables are incorporated via P-splines GAM to model the correlation coefficients corresponding to Copula parameters,thereby obtaining conditional quantiles of the forecasting errors.Finally,the point predictions are cor-rected based on the conditional median of errors,and forecasting intervals are generated by superimposing the condi-tional quantiles of errors.Validation using actual operational data from a wind farm in Shanxi Province,China dem-onstrates the effectiveness and superiority of the proposed method.关键词
风电功率预测/广义可加模型/分位数回归/区间预测Key words
wind power forecasting/GAM/quantile regression/interval forecasting引用本文复制引用
黄学勤,杨鹏举,赵耀,高少炜..考虑多维气象数据与时间影响的风电功率区间预测[J].浙江电力,2026,45(1):66-77,12.基金项目
国家自然科学基金(52377111) （52377111）
