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AUTOREGRESSIVE MODELS IN SHORT TERM LOAD FORECAST: A COMPARISON OF AR AND ARMA

Baharudin , Z. (2008) AUTOREGRESSIVE MODELS IN SHORT TERM LOAD FORECAST: A COMPARISON OF AR AND ARMA. In: The 28th International Symposium on Forecasting, 22nd to 25th June 2008, Nice, France.

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Abstract

Short-term load forecasting plays an important role in planning and operation of power system. The accuracy of this forecasted value is necessary for economically efficient operation and also for effective control. This paper describes a comparison of autoregressive moving average (ARMA) and autoregressive (AR) Burg’s and modified covariance (MCOV) methods in solving one week ahead of short term load forecast. The methods are tested based from historical load data of National Grid of Malaysia and load demand in New South Wales, Australia. The accuracy of discussed methods are obtained and reported.

Item Type:Conference or Workshop Item (Lecture)
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Mission Oriented Research > Sustainable Development
ID Code:6163
Deposited By: Dr Zuhairi Baharudin
Deposited On:07 Jul 2011 07:03
Last Modified:19 Jan 2017 08:26

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