云南师范大学学报（自然科学版）2026，Vol.46Issue(2)：27-30,4.DOI:10.7699/j.ynnu.ns-2026-06
基于交叉注意力融合的短时光伏功率预测
Short-term Photovoltaic Power Forecasting Based on Cross-attention Fusion
摘要
Abstract
To improve the accuracy of short-term photovoltaic(PV)power forecasting for solar PV sys-tems under complex meteorological conditions,a multimodal short-term forecasting model named ViT-Informer is proposed.The Vision Transformer(ViT)and Informer are utilized to extract image fea-tures and temporal features,respectively,followed by a cross-attention mechanism to achieve bimodal feature fusion,capturing the key characteristics causing power fluctuations,thereby improving the ac-curacy of photovoltaic power prediction.Experiments conducted on a self-built small-scale PV system integrated with an all-sky imaging platform demonstrate that the attention mechanism can effectively extract critical features while suppressing redundant information.For 15-minute-ahead forecasting,compared with single-modality models,the proposed fusion model improves the prediction skill score(Fs)by 9.5％～28.2％,and reduces the normalized mean absolute error(NMAE)and normalized root mean square error(NRMSE)by up to 9.8％and 5.4％,respectively.关键词
光伏系统/短时功率预测/多模态/交叉注意力Key words
Photovoltaic system/Short-term power forecasting/Multimodality/Cross-attention分类
信息技术与安全科学引用本文复制引用
何毅元,王子健,姚海,付昆鹏,何洪伟,李琼..基于交叉注意力融合的短时光伏功率预测[J].云南师范大学学报（自然科学版）,2026,46(2):27-30,4.基金项目
国家自然科学基金资助项目(12262036) （12262036）
云南省基础研究计划资助项目(202301AT070064). （202301AT070064）
