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

• المؤلف الرئيسي: Baharudin , Z.
• التنسيق: Conference or Workshop Item
• منشور في: The International Institute of Forecasters 2008
• الموضوعات: TK Electrical engineering. Electronics Nuclear engineering
• الوصول للمادة أونلاين: http://eprints.utp.edu.my/6163/1/isf2008.pdf; http://forecasters.org/isf/pdfs/ISF2008_Proceedings.pdf; http://eprints.utp.edu.my/6163/
• المؤسسة: Universiti Teknologi Petronas

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.