中国电力2025，Vol.58Issue(5)：21-32,12.DOI:10.11930/j.issn.1004-9649.202411101
基于时序分解与共形分位数回归的超短期光伏功率区间预测
Ultra-Short-Term Photovoltaic Power Interval Forecasting Based on Time-Series Decomposition and Conformal Quantile Regression
摘要
Abstract
Traditional PV power interval forecasting relies on specific probabilistic distribution assumptions,which often result in inconsistencies between the assumed probability distributions and the actual heteroscedastic nature of PV power distributions,thus affecting the accuracy and confidence level of interval predictions.To address this issue,an ultra-short-term PV power interval forecasting method based on time-series decomposition and conformal quantile regression(CQR)is proposed.Firstly,the PV power series is modeled as the sum of three additive subseries:trend components,periodic components,and autoregressive components,based on the NeuralProphet time-series decomposition framework.Then,piecewise linear models,Fourier series decomposition models,and AR-Net models are respectively employed to fit the three subseries,with the Fourier series decomposition model enhancing the fitting capability for daily and seasonal periodicities of PV power.Finally,by calculating the prediction uncertainty of the CQR model,the quantile interval of the prediction results are determined based on conformal scores,enabling dynamic adjustment of the prediction interval width without the need for preset probability distributions.Case studies demonstrate that the proposed method outperforms the advanced Transformer-based algorithms like TimesNet and Informer in deterministic PV power forecasting tasks,and with the introduction of the daily and seasonal periodic components,the prediction error is further reduced by 11.65%.In interval forecasting tasks,the proposed method surpasses the traditional quantile regression algorithms in terms of prediction interval coverage rate,normalized interval width,and coverage width-based criterion.关键词
光伏发电/时间序列分解/周期分量/共形预测/分位数回归/区间预测Key words
photovoltaic power generation/time-series decomposition/periodic component/conformal prediction/quantile regression/interval predication引用本文复制引用
桂前进,徐文法,李晓阳,罗利荣,叶海峰,王正风..基于时序分解与共形分位数回归的超短期光伏功率区间预测[J].中国电力,2025,58(5):21-32,12.基金项目
国网安徽省电力有限公司科技项目(B312D023000Q). This work is supported by Science&Technology Project of State Grid Anhui Electric Power Co.,Ltd.(No.B312D023000Q). （B312D023000Q）
