计算机与数字工程2025，Vol.53Issue(2)：432-436,443,6.DOI:10.3969/j.issn.1672-9722.2025.02.023
基于IVMD-SVR模型的短期风速预测
Short-term Wind Speed Prediction Based on IVMD-SVR Model
摘要
Abstract
With the sharp decline of traditional fossil fuels,as well as the increasingly serious environmental pollution,all countries in the world are focusing on the development of wind power generation as one of the renewable energy generation technolo-gy,accurate wind speed prediction is to ensure the safe and stable operation of wind power system is a long-term challenge.There-fore,a wind speed prediction model based on chaotic characteristics of variational modal decomposition and support vector regres-sion is proposed.The IVMD(Improved Variational Mode Decomposition)-SVR(Support Vector Regression)proposed in this pa-per uses variational mode decomposition(VMD)to decompose the wind speed series.The complexity and nonstationarity of wind speed sequence are reduced.Then the method of chaos test is used to judge whether the decomposed time series has chaotic charac-teristics.If it has chaotic characteristics,G-P algorithm is used to determine the embedding dimension m,if it does not have chaot-ic characteristics,partial autocorrelation coefficient is used to determine the order,and the prediction of support vector regression machine is summarized.Finally,through real data simulation experiment,the experimental results show that the IVMD-SVR meth-od proposed in this paper is superior to other common prediction methods in terms of prediction error,prediction accuracy and pre-diction effect,which proves that the prediction method is effective.关键词
VMD/混沌特性/SVR/风速预测Key words
VMD/chaotic characteristics/SVR/wind speed forecasting分类
数理科学引用本文复制引用
尹隆腾,陈娟..基于IVMD-SVR模型的短期风速预测[J].计算机与数字工程,2025,53(2):432-436,443,6.
