FORECASTING HOURLY ELECTRICITY DEMAND USING TIME-VARYING SPLINES

被引：136

作者：

HARVEY, A

KOOPMAN, SJ

机构：

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 1993年 / 88卷 / 424期

关键词：

CUBIC SPLINES; FORECASTING; KALMAN FILTER; LOAD CURVE; NONLINEAR REGRESSION; SEASONALITY; STRUCTURAL TIME SERIES MODEL;

D O I：

10.2307/2291261

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A method for modeling a changing periodic pattern is developed. The use of time-varying splines enables this to be done relatively parsimoniously. The method is applied in a model used to forecast hourly electricity demand, with the periodic movements being intradaily or intraweekly. The. full model contains other components, including a temperature response, which is also modeled using splines.

引用

页码：1228 / 1236

页数：9

共 10 条

[1]

Bunn D., 1985, COMP MODELS ELECTRIC

[2] SEMIPARAMETRIC ESTIMATES OF THE RELATION BETWEEN WEATHER AND ELECTRICITY SALES [J].