基于改进SSA的MVMD-Timemixer的短期风速预测

熊晓凤; 贾世会; 迟晓妮; 李高西

doi:10.19912/j.0254-0096.tynxb.2025-0308

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (7) : 58-69. DOI: 10.19912/j.0254-0096.tynxb.2025-0308

基于改进SSA的MVMD-Timemixer的短期风速预测

熊晓凤^1,2, 贾世会^1,2, 迟晓妮³, 李高西⁴

作者信息 +

SHORT-TERM WIND SPEED PREDICTION BASED ON TIMEMIXER AND MVMD OPTIMIZED BY IMPROVED SPARROW SEARCH ALGORITHM

Xiong Xiaofeng^1,2, Jia Shihui^1,2, Chi Xiaoni³, Li Gaoxi⁴

Author information +

文章历史 +

摘要

针对风速预测中因随机性和波动性导致风速预测精度低的问题,提出一种基于改进麻雀搜索算法（ISSA）优化参数的多元变分模态分解（MVMD）和Timemixer模型混合预测方法。首先基于最大互信息系数和随机森林算法对数据变量进行降维,并使用引入Logistic-Tent混沌映射和黄金正弦策略的改进麻雀搜索算法（ISSA）对MVMD中的模态数及惩罚系数进行自动寻优;优化后的MVMD模型将数据分解成多个本征模态函数（IMF）,然后使用Timemixer模型对每个IMF进行预测;最后将各IMF预测结果叠加得到最终风速预测结果。两组数据实验结果表明：所提模型与其他预测模型相比,预测精度更高,在风速预测上表现出良好的性能。

Abstract

To address the problem of low wind speed prediction accuracy caused by the inherent randomness and volatility of wind speed, this study proposes a hybrid prediction method based on multivariate variational mode decomposition (MVMD） with parameters optimized by an improved sparrow search algorithm (ISSA） and the Timemixer model. First, data variables are reduced in dimensionality using the maximum information coefficient (MIC） and the random forest algorithm. Then, the ISSA, which incorporates Logistic-Tent chaotic mapping and a golden sine strategy, is utilized to automatically optimize the number of modes and the penalty coefficient in MVMD. The optimized MVMD decomposes the data into multiple intrinsic mode functions (IMFs）, and each IMF is individually predicted using the TimeMixer model. Finally, the IMF predictions are aggregated to produce the final wind speed forecast. Experimental results on two datasets demonstrate that, compared with other prediction models, the proposed model achieves higher prediction accuracy and exhibits good performance in wind speed forecasting.

导出引用

熊晓凤, 贾世会, 迟晓妮, 李高西. 基于改进SSA的MVMD-Timemixer的短期风速预测[J]. 太阳能学报. 2026, 47(7): 58-69 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0308

Xiong Xiaofeng, Jia Shihui, Chi Xiaoni, Li Gaoxi. SHORT-TERM WIND SPEED PREDICTION BASED ON TIMEMIXER AND MVMD OPTIMIZED BY IMPROVED SPARROW SEARCH ALGORITHM[J]. Acta Energiae Solaris Sinica. 2026, 47(7): 58-69 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0308

中图分类号： TM614

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