基于经验模态分解法的发电功率预测在电力系统中的应用分析  

Analysis of Generation Power Forecasting Based on Empirical Modal Decomposition Method in Power Systems

作　　者：刘文康 Liu Wenkang(School of Electrical and Control Engineering,Liaoning Technical University,Huludao Liaoning 125105,China)

机构地区：[1]辽宁工程技术大学电气与控制工程学院,辽宁葫芦岛125105

出　　处：《现代工业经济和信息化》2024年第7期127-128,共2页Modern Industrial Economy and Informationization

摘　　要：为了减小发电功率预测的误差,提出一种基于经验模态分解(EMD)的发电功率预测方法,避免了过多变量对预测过程的干扰,减小了模型的复杂程度,对最初始的数据进行拆分再进行建模,最后进行累加得到最终的预测结果,这种方法相比于传统的线性模型具有较小的误差。In order to reduce the error of power generation prediction,a power generation prediction method based on empirical modal decomposition(EMD)is now proposed,which avoids too many variables interfering with the prediction process,reduces the complexity of the model,splits and then models the most initial data,and finally sums up to get the final prediction result,which has a smaller error compared with the traditional linear model.

关 键 词：电力系统 经验模态分解 发电功率预测 

分 类 号：TM615[电气工程—电力系统及自动化]