基于SARIMA-ARCH的电量预测模型  

Electricity Prediction Model Based on SARIMA-ARCH

作　　者：许然 杨黎娜 钟强 XU Ran;YANG Li-na;ZHONG Qiang(Liupanshui Normal University,Liupanshui 553000,China;Liupanshui Power Supply Bureau of Guizhou Power Grid Co.,Ltd.,Liupanshui 553000,China)

机构地区：[1]六盘水师范学院计算机科学与技术学院,贵州六盘水553000 [2]贵州电网有限责任公司六盘水供电局,贵州六盘水553000

出　　处：《电脑与电信》2024年第5期88-91,共4页Computer & Telecommunication

摘　　要：电量预测是供电单位购电的重要依据,是电力经济稳定运行的根本基础。提出采用SARIMA-ARCH融合模型对某地区售电量进行预测。首先,采用季节时间序列分析方法(SARIMA)对月度电量时间序列进行建模,通过ACF和PACF图筛选确定出最佳模型阶数,得到季节性时间序列模型(SARIMA)基础预测模型;提取模型残差的波动性,建立自回归条件异方差(ARCH)模型;最后,将SARIMA-ARCH模型与常规SRIAM和ARIMA的预测值进行对比分析。结果表明,SARIMAARCH混合模型的预测精度较高。Electricity quantity prediction is an important basis for power supply units to purchase electricity,and it is the fundamental foundation for the stable operation of the electricity economy.This article proposes using the SARIMA-ARCH fusion model to predict electricity consumption.Firstly,the seasonal time series model(SARIMA) is used to model the monthly electricity consumption time series.The optimal model order is determined through ACF and PACF graph screening,and the basic prediction model of the seasonal time series model(SARIMA) is obtained.Subsequently,the regression residuals of the basic model are subjected to ARCH effect testing,and an autoregressive conditional heteroscedasticity(ARCH) model is established.Finally,this article compares and analyzes the predicted values of the SARIMA-ARCH model with those of conventional SRIAM and ARIMA.The results show that the prediction accuracy of the hybrid model of SARIMA-ARCH is high.

关 键 词：SARIMA 时间序列分析 ARCH效应 售电量 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]