Random fully connected layered 1D CNN for solving the Z-bus loss allocation problem

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dc.authorid0000-0003-2371-8173en_US
dc.authorid0000-0003-1840-9958
dc.contributor.authorSindi, Hatem
dc.contributor.authorNour, Majid
dc.contributor.authorRawa, Muhyaddin
dc.contributor.authorÖztürk, Şaban
dc.contributor.authorPolat, Kemal
dc.date.accessioned2021-06-23T19:55:03Z
dc.date.available2021-06-23T19:55:03Z
dc.date.issued2021
dc.departmentBAİBÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractPower loss allocation methods should be efficient enough to meet the needs of the customers on the bus and effectively calculate the losses from generators and consumers. In order to perform these tasks, a highly robust model is essential to distinguish between the effects of multi-consumers. This study presents a novel convolutional neural network (CNN) architecture that is highly effective for z-bus loss allocation. The proposed CNN architecture that uses the Z-bus matrix as input is 1D. Unlike traditional 1D CNN architectures in the literature, the fully connected layer (FCL) of the proposed method is randomized. Unlike Traditional FCL layers, randomized FCL's input weights and biases are not needed to be tuned. This makes the proposed 'Randomized Fully Connected Layered 1D CNN' architecture relatively fast and straightforward. Proposed Randomized Fully Connected Layered 1D CNN is trained in an end-to-end manner with a regression task for robust loss allocation. The performance of it is higher than other state-of-the-art methods. In addition to the fact that the proposed method's regression performance is very promising, the classifier performance is quite satisfactory thanks to the changes to be made in its output.en_US
dc.identifier.doi10.1016/j.measurement.2020.108794
dc.identifier.issn0263-2241
dc.identifier.issn1873-412X
dc.identifier.scopus2-s2.0-85097180003en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.measurement.2020.108794
dc.identifier.urihttps://hdl.handle.net/20.500.12491/10716
dc.identifier.volume171en_US
dc.identifier.wosWOS:000614791100003en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPolat, Kemal
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofMeasurementen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLoss Allocationen_US
dc.subject1D CNNen_US
dc.subjectRandomized FCLen_US
dc.subjectZ-busen_US
dc.subjectPower Lossesen_US
dc.titleRandom fully connected layered 1D CNN for solving the Z-bus loss allocation problemen_US
dc.typeArticleen_US

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