东北电力技术2024，Vol.45Issue(7)：27-31,37,6.
基于VMD-GWO-SVR的短期电力负荷预测方法
Short-Term Power Load Forecasting Method Based on VMD-GWO-SVR
张异殊 1李宜伦 1姚志远 1陈蕾宇1
作者信息
- 1. 国网丹东供电公司,辽宁 丹东 118000
- 折叠
摘要
Abstract
Short-term power load forecasting plays an important role in the safe and stable operation of power system and power market transactions.It proposes a short-term power load forecasting method based on decomposition and reconstruction framework.Firstly,the load sequence is decomposed into five components by variational mode decomposition(VMD),and the support vector regression(SVR)prediction model of five components is established to predict the power load component.Secondly,the power load component is predicted and the grey wolf optimization(GWO)algorithm is used to optimize the parameters of SVR.Finally,the predicted values of the five components are superimposed to obtain the final power load forecasting results.It compares this method with SVR method without modal decomposition and other prediction methods.The three evaluation indexes of this method are optimal.It shows that the method has a good application prospect in short-term power load forecasting.关键词
变分模态分解/灰狼算法/支持向量机/电力负荷预测Key words
variable mode decomposition/grey wolf algorithm/support vector machine/power load forecasting分类
信息技术与安全科学引用本文复制引用
张异殊,李宜伦,姚志远,陈蕾宇..基于VMD-GWO-SVR的短期电力负荷预测方法[J].东北电力技术,2024,45(7):27-31,37,6.
