现代电力2026，Vol.43Issue(1)：20-29,10.DOI:10.19725/j.cnki.1007-2322.2023.0429
基于改进变分模态分解与Informer组合模型的风电功率多步预测研究
Multi-step Prediction of Wind Power Based on Improved Variational Modal Decomposition and Informer Hybrid Model
摘要
Abstract
The accurate predition of wind power is crucial for enhancing the efficiency of wind energy utilization and achieving sustainable development of the power system.In view of this,a multi-step wind power prediction model based on the improved variational modal decomposition(VMD)with Informer is proposed in this paper.Firstly,the original meteorological factors such as wind speed,wind direction,and pressure are filtered using the random forest model.Secondly,the wind power signal is decomposed by the pelican optimization algorithm-improved VMD algorithm to enhance the accuracy of wind power sequence prediction.Thirdly,multi-step wind power prediction is performed using the Informer model.Finally,the superiority of this model in multi-step wind power prediction is verified through multi-dimensional comparison with other models.The case results demonstrate that the wind power multi-step prediction model based on the improved VMD with Informer exhibits excellent prediction performance and can provide reference for wind power prediction.关键词
风电功率预测/随机森林/鹈鹕优化算法/信号分解/多步预测Key words
wind power prediction/random forest(RF)/pelican optimization algorithm(POA)/signal decomposition/multi-step prediction分类
信息技术与安全科学引用本文复制引用
郭晓鹏,赵琪,张国维..基于改进变分模态分解与Informer组合模型的风电功率多步预测研究[J].现代电力,2026,43(1):20-29,10.基金项目
国家自然科学基金(青年科学基金项目)(72301102).Project Supported by National Natural Science Foundation of China(Young Scientistic Program)(72301102). （青年科学基金项目）
