SARIMA-Orthogonal Polynomial Curve Fitting Model for Medium-Term Load Forecasting

Seasonal component has been a key factor in time series modeling for medium-term electric load forecasting. In this paper, a seasonal-ARIMA model is developed, but the parameters of the SAR and the SMA turn out to be quite nonsignificant in most cases during the model order selection. To address thi...

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Main Authors: Herui Cui, Pengbang Wei, Yupei Mu, Xu Peng
Format: Article
Language:English
Published: Wiley 2016-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2016/9649682
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author Herui Cui
Pengbang Wei
Yupei Mu
Xu Peng
author_facet Herui Cui
Pengbang Wei
Yupei Mu
Xu Peng
author_sort Herui Cui
collection DOAJ
description Seasonal component has been a key factor in time series modeling for medium-term electric load forecasting. In this paper, a seasonal-ARIMA model is developed, but the parameters of the SAR and the SMA turn out to be quite nonsignificant in most cases during the model order selection. To address this issue, the hybrid time series model based on the HP filter is utilized to extract the spectrum sequences with different frequencies and analyze interactions among various factors. Finally, an integrative forecast is made for the electricity consumption from January to November in 2014. The empirical results demonstrate that the method with HP filter could reduce the relative error caused by the interaction between the trend component and the seasonal component.
format Article
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institution OA Journals
issn 1026-0226
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language English
publishDate 2016-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-ece3679aed4748d68709f191185a98f52025-08-20T02:22:09ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2016-01-01201610.1155/2016/96496829649682SARIMA-Orthogonal Polynomial Curve Fitting Model for Medium-Term Load ForecastingHerui Cui0Pengbang Wei1Yupei Mu2Xu Peng3School of Economics and Management, North China Electric Power University, Baoding 071003, ChinaSchool of Economics and Management, North China Electric Power University, Baoding 071003, ChinaSchool of Economics and Management, North China Electric Power University, Baoding 071003, ChinaSchool of Economics and Management, North China Electric Power University, Baoding 071003, ChinaSeasonal component has been a key factor in time series modeling for medium-term electric load forecasting. In this paper, a seasonal-ARIMA model is developed, but the parameters of the SAR and the SMA turn out to be quite nonsignificant in most cases during the model order selection. To address this issue, the hybrid time series model based on the HP filter is utilized to extract the spectrum sequences with different frequencies and analyze interactions among various factors. Finally, an integrative forecast is made for the electricity consumption from January to November in 2014. The empirical results demonstrate that the method with HP filter could reduce the relative error caused by the interaction between the trend component and the seasonal component.http://dx.doi.org/10.1155/2016/9649682
spellingShingle Herui Cui
Pengbang Wei
Yupei Mu
Xu Peng
SARIMA-Orthogonal Polynomial Curve Fitting Model for Medium-Term Load Forecasting
Discrete Dynamics in Nature and Society
title SARIMA-Orthogonal Polynomial Curve Fitting Model for Medium-Term Load Forecasting
title_full SARIMA-Orthogonal Polynomial Curve Fitting Model for Medium-Term Load Forecasting
title_fullStr SARIMA-Orthogonal Polynomial Curve Fitting Model for Medium-Term Load Forecasting
title_full_unstemmed SARIMA-Orthogonal Polynomial Curve Fitting Model for Medium-Term Load Forecasting
title_short SARIMA-Orthogonal Polynomial Curve Fitting Model for Medium-Term Load Forecasting
title_sort sarima orthogonal polynomial curve fitting model for medium term load forecasting
url http://dx.doi.org/10.1155/2016/9649682
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AT pengbangwei sarimaorthogonalpolynomialcurvefittingmodelformediumtermloadforecasting
AT yupeimu sarimaorthogonalpolynomialcurvefittingmodelformediumtermloadforecasting
AT xupeng sarimaorthogonalpolynomialcurvefittingmodelformediumtermloadforecasting