电力系统保护与控制2025，Vol.53Issue(18)：74-87,14.DOI:10.19783/j.cnki.pspc.241500
基于二次模态分解重构及BiTCN-BiGRU模型的光伏短期发电功率预测
Short-term PV power generation forecasting based on quadratic mode decomposition reconstruction and BiTCN-BiGRU model
摘要
Abstract
To address the issue of low prediction accuracy caused by the unstable and fluctuating characteristics of photovoltaic(PV)power generation,a short-term PV power forecasting method is proposed.The method integrates quadratic mode decomposition reconstruction(QMDR),a bidirectional temporal convolutional network(BiTCN)and bidirectional gated recirculation unit(BiGRU)combined model,and a multi-strategy improved sand cat swarm optimization algorithm(MSCSO).First,meteorological features are selected as model inputs using the Spearman correlation coefficient,and fuzzy C-mean clustering method is applied for similar-day classification.Next,the PV power series are decomposed by improved complete ensemble empirical modal decomposition and variational modal decomposition,and the components are reconstructed by sample entropy.Finally,a combined prediction model of BiTCN-BiGRU is established,with the parameters of the model optimized by MSCSO.The final PV power prediction is obtained by superimposing the forecasts of each constructed component.Comparative analyses under different weather conditions and across different regions verify that the proposed model has higher prediction accuracy and better adaptability than existing approaches.关键词
二次模态分解重构/沙猫群算法/双向时序卷积网络/双向门控循环单元/光伏功率预测Key words
quadratic modal decomposition reconstruction/sand cat swarm optimization/bidirectional temporal convolutional networks/bidirectional gated recirculation unit/PV power prediction引用本文复制引用
文斌,章学勤,付文龙,丁弈夫,封宣宇..基于二次模态分解重构及BiTCN-BiGRU模型的光伏短期发电功率预测[J].电力系统保护与控制,2025,53(18):74-87,14.基金项目
This work is supported by the National Natural Science Foundation of China(No.62273200). 国家自然科学基金项目资助(62273200) （No.62273200）
湖北省输电线路工程技术研究中心研究基金项目资助(2022KXL03) （2022KXL03）
湖北省自然科学基金联合基金项目资助(2024AFD409) （2024AFD409）
