relation: https://khub.utp.edu.my/scholars/5482/
title: AR-based algorithms for short term load forecast
creator: Baharudin, Z.
creator: Azman Zakariya, M.
creator: HarisMdKhir, M.
description: Short-term load forecast plays an important role in planning and operation of power systems. The accuracy of the forecast value is necessary for economically efficient operation and effective control of the plant. This study describes the methods of Autoregressive (AR) Burg's and Modified Covariance (MCOV) in solving the short term load forecast. Both algorithms are tested with power load data from Malaysian grid and New South Wales, Australia. The forecast accuracy is assessed in terms of their errors. For the comparison the algorithms are tested and benchmark with the previous successful proposed methods. © Maxwell Scientific Organization, 2014.
publisher: Maxwell Science Publications
date: 2014
type: Article
type: PeerReviewed
identifier:   Baharudin, Z. and Azman Zakariya, M. and HarisMdKhir, M.  (2014) AR-based algorithms for short term load forecast.  Research Journal of Applied Sciences, Engineering and Technology, 7 (6).  pp. 1037-1043.  ISSN 20407459     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893356756&doi=10.19026%2frjaset.7.384&partnerID=40&md5=c90c06570131e567ba4e81713d4579c7
relation: 10.19026/rjaset.7.384
identifier: 10.19026/rjaset.7.384