四川轻化工大学学报（自然科学版）2026，Vol.39Issue(3)：68-77,10.DOI:10.11863/j.suse.2026.03.08
基于MLP与iTransformer融合的中长期光伏发电功率预测
Medium-to-Long-Term Photovoltaic Power Forecasting Based on MLP and iTransformer Fusion
摘要
Abstract
In order to improve the prediction accuracy of PV power in the medium-to-long-term,an MLPformer model based on the fusion of Multilayer Perceptron(MLP)and iTransformer is proposed,which can accurately and effectively predict PV power.MLPformer innovatively proposes to perform variable correlation,feature extraction,and temporal feature extraction for the time series separately.This approach solves the problem of insufficient feature extraction of time series by existing single models.The Multilayer Perceptron Feedforward(MLPforward)unit is designed to improve the ability of the iTransformer model to extract variable correlation features.Multilayer Perceptron Blcok(MLPBlock)is designed to extract time-dependent features and capture nonlinear relationships.It is experimentally verified that the model possesses higher accuracy in medium-to-long-term PV power prediction,and the model shows an average decrease of 4.49％in mean square error and 4.79％in mean absolute error compared with the current state-of-the-art iTransformer model on two publicly available PV power datasets.关键词
iTransformer/多层感知机/特征融合/光伏发电功率中长期预测Key words
iTransformer/multilayer perceptron/feature fusion/medium-to-long-term forecast of photovoltaic power分类
信息技术与安全科学引用本文复制引用
王文,朱文忠,刘德飞,吴宇浩,罗缘..基于MLP与iTransformer融合的中长期光伏发电功率预测[J].四川轻化工大学学报（自然科学版）,2026,39(3):68-77,10.基金项目
四川省科技计划重点研发项目(2023YFS0371) （2023YFS0371）
四川省科技创新(苗子工程)培育项目(2022049) （苗子工程）
企业信息化与物联网测控技术四川省高校重点实验室开放基金项目(2024WYJ03) （2024WYJ03）
四川省智慧旅游研究基地项目(ZHYJ24-01) （ZHYJ24-01）
