Elman神经网络在电力负荷预测中的应用探究  

Exploration of the Application of Elman Neural Network in Power Load Forecasting

作　　者：王平[1] Wang Ping(Shanxi Datong University,Datong,Shanxi,China,037009)

机构地区：[1]山西大同大学,山西大同037009

出　　处：《仪器仪表用户》2024年第12期108-110,113,共4页Instrumentation

基　　金：山西大同大学2020-2021年度科研基金项目“Elman神经网络的数据预测在电力负荷模型分析中的应用研究”(2021K6)

摘　　要：本文探讨了Elman神经网络在电力负荷预测中的应用。通过对Elman神经网络的原理和特点进行分析,结合电力负荷预测的实际需求,论证了将Elman神经网络应用于电力负荷预测的可行性和有效性。文章介绍了Elman神经网络的训练算法和优化方法,并通过实例分析说明了该网络在电力负荷预测中的具体应用。研究表明,Elman神经网络能够有效捕捉电力负荷时间序列的动态特征,对于提高电力负荷预测的精度具有重要意义。This article explores the application of Elman neural network in power load forecasting.Through the analysis of the principles and characteristics of the Elman neural network,combined with the actual needs of power load forecasting,the feasibility and effectiveness of applying the Elman neural network to power load forecasting are demonstrated.The article introduces the training algorithm and optimization method of the Elman neural network,and illustrates the specific application of this network in power load forecasting through case analysis.The research shows that the Elman neural network can effectively capture the dynamic characteristics of the power load time series,which is of great significance for improving the accuracy of power load forecasting.

关 键 词：ELMAN神经网络 电力负荷预测 时间序列 动态特征 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]