Short-term load forecasting using AR and ARIMA box Jenkins model / Romi Ehendra Abdul Aziz

Abdul Aziz, Romi Ehendra (2008) Short-term load forecasting using AR and ARIMA box Jenkins model / Romi Ehendra Abdul Aziz. Degree thesis, Universiti Teknologi MARA (UiTM).

Abstract

This paper presents an overview research on the short term load forecasting (STLF) in power system field. The method used in this approach was based on autoregressive (AR) Box Jenkins model. AR was mathematical model in solving iteration problem. The AR model was selected based on the behavior of the sample autocorrelation (SAC) and sample partial autocorrelation (SPAC). Furthermore the adequacy of the AR model was determined by Ljung Box test. The (AR) Box Jenkins model then is compared with the ARIMA Box Jenkins model to determine the performance of both models in assessment of STLF. The main purpose was to study the important of load forecasting. Whereby from the load forecasting analysis we can estimate on how many generation plants that have to turn on in certain period time, and switching.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Abdul Aziz, Romi Ehendra
UNSPECIFIED
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Othman, Muhammad Murtadha
UNSPECIFIED
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Production of electric energy or power. Powerplants. Central stations
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electric power distribution. Electric power transmission
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Programme: Bachelor of Electrical Engineering (Hons)
Keywords: Short-term load forecasting (STLF), autoregressive Box Jenkins Model (AR), sample autocorrelation
Date: 2008
URI: https://ir.uitm.edu.my/id/eprint/67130
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