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New multivariate linear regression real and reactive branch flow models for volatile scenarios

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dc.contributor.authorAppalasamy S.en_US
dc.contributor.authorJones O.D.en_US
dc.contributor.authorMoin N.H.en_US
dc.contributor.authorSin T.C.en_US
dc.contributor.authorid57092686500en_US
dc.contributor.authorid57205913427en_US
dc.contributor.authorid6507487566en_US
dc.contributor.authorid55363559700en_US
dc.date.accessioned2023-05-29T05:59:48Z
dc.date.available2023-05-29T05:59:48Z
dc.date.issued2015
dc.descriptionElectric load flow; Least squares approximations; Regression analysis; Branch flow; flexible; Multivariate linear regressions; Power flow equations; Power systems operation; Prediction accuracy; robust; Underlying factors; Linear regressionen_US
dc.description.abstractNonlinearity of power flow equations is one of the major underlying factors in a power systems operation complexity. The need for a robust and less complex models rises in a volatile, dynamic and real time scenario. This paper introduces new empirical models using multivariate linear regression (MLR) methods with least squares for both real and reactive branch flows. The models do not make prior assumptions and do not depend on a particular base case. Instead they are trained on either simulated or historical data. Tests using the IEEE 14 bus system show that given similar input variables to DC models, the MLR models performs significantly better. They also show that the MLR models have good prediction accuracy in scenarios with high volatility. � 2015 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7285669
dc.identifier.doi10.1109/PESGM.2015.7285669
dc.identifier.scopus2-s2.0-84956854686
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84956854686&doi=10.1109%2fPESGM.2015.7285669&partnerID=40&md5=1b99eebb0482525366daa30ceae3c770
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22242
dc.identifier.volume2015-September
dc.publisherIEEE Computer Societyen_US
dc.sourceScopus
dc.sourcetitleIEEE Power and Energy Society General Meeting
dc.titleNew multivariate linear regression real and reactive branch flow models for volatile scenariosen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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