Dynamic regression intervention modeling for the Malaysian daily load

Fadhilah Abd Razak, Mahendran Shitan, Amir Hisham Hashim, Izham Zainal Abidin

Research output: Contribution to journalArticle

Abstract

Malaysia is a unique country due to having both fixed and moving holidays. These moving holidays may overlap with other fixed holidays and therefore, increase the complexity of the load forecasting activities. The errors due to holidays' effects in the load forecasting are known to be higher than other factors. If these effects can be estimated and removed, the behavior of the series could be better viewed. Thus, the aim of this paper is to improve the forecasting errors by using a dynamic regression model with intervention analysis. Based on the linear transfer function method, a daily load model consists of either peak or average is developed. The developed model outperformed the seasonal ARIMA model in estimating the fixed and moving holidays' effects and achieved a smaller Mean Absolute Percentage Error (MAPE) in load forecast.

Original languageEnglish
Pages (from-to)41-55
Number of pages15
JournalPakistan Journal of Statistics and Operation Research
Volume10
Issue number1
Publication statusPublished - 2014

Fingerprint

Load Forecasting
Regression
Modeling
ARIMA Models
Malaysia
Linear Function
Transfer Function
Percentage
Forecast
Forecasting
Overlap
Regression Model
Dynamic Model
Transfer functions
Series
Model
Holidays

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research

Cite this

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Dynamic regression intervention modeling for the Malaysian daily load. / Abd Razak, Fadhilah; Shitan, Mahendran; Hashim, Amir Hisham; Zainal Abidin, Izham.

In: Pakistan Journal of Statistics and Operation Research, Vol. 10, No. 1, 2014, p. 41-55.

Research output: Contribution to journalArticle

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