基于不同分布下GARCH-M族模型的短期用户负荷预测  

Short-term user load forecasting based on GARCH-M family model with different distributions

作　　者：王晨 叶江明[1] 何嘉弘 WANG Chen;YE Jiangming;HE Jiahong(School of Electric Power Engineering,Nanjing Institute of Technology,Nanjing 211167,China;School of Electrical Engineering,Southeast University,Nanjing 210096,China)

机构地区：[1]南京工程学院电力工程学院,江苏南京211167 [2]东南大学电气工程学院,江苏南京210096

出　　处：《电力工程技术》2022年第5期110-115,共6页Electric Power Engineering Technology

基　　金：国家自然科学基金资助项目(51807028)。

摘　　要：电力负荷预测是电力系统研究的基础工作之一,而时间序列分析法是目前使用最广泛的预测方法。针对用户日度负荷时间序列存在的波动性及尖峰厚尾特征,文中提出利用均值广义自回归条件异方差(GARCH-M)族模型进行用户负荷预测。首先根据用户日度负荷时间序列的分布情况,利用拉格朗日乘数(LM)检验方法检验了负荷序列的自回归条件异方差(ARCH)效应;其次提出在高斯分布、t分布和广义误差分布(GED)3种不同分布下,根据波动补偿项的不同形式,建立GARCH-M族模型;最后结合损失函数进行预测分析,结果表明相比传统时间序列分析模型,在不同分布下的GARCH-M族模型提高了短期用户负荷预测准确度。Power load forecasting is one of the basic tasks power system research,and time series analysis is currently the most widely used forecasting method.Aiming at the fluctuation and the characteristics of peak and thick tail of user daily load time series,the generalized autoregressive conditional heteroskedasticity-in-mean(GARCH-M)family model is proposed to predict user load.Firstly,the autoregressive conditional heteroskedasticity(ARCH)effect of load series is examined by using the Lagrange multiplier(LM)test according to the distribution of user daily load time series.Secondly,under three different distributions of Gaussian distribution,t-distribution and generalized error distribution(GED),the GARCH-M family model is established according to the different forms of fluctuation compensation terms.Finally,combined with the loss function,the prediction analysis results show that the GARCH-M family model with different distributions improves the accuracy of short-term user load prediction compared with the traditional time series analysis model.

关 键 词：时间序列分析法 短期用户负荷预测 自回归条件异方差(ARCH)效应 GARCH-M族模型 厚尾效应 损失函数 

分 类 号：TM715[电气工程—电力系统及自动化]