Probabilistic Load Flow in a Transmission System Integrated with Photovoltaic Generations

Simple item page
dc.contributor.authorPrusty, B.
dc.contributor.authorJena, D.
dc.date.accessioned2026-02-06T06:37:46Z
dc.date.issued2019
dc.description.abstractThis paper compares the performance (solution accuracy and computational efficiency) of two hybrid methods (HMs) for probabilistic load flow (PLF) considering a mixture of discrete as well as correlated Gaussian and non-Gaussian input random variables. The PLF is accomplished on IEEE 118-bus test system with photovoltaic arrays installed at specific buses. The results of the HMs are compared with that of the existing methods such as combined cumulant and Gram-Charlier method, combined cumulant and Cornish-Fisher method, dependent discrete convolution method, and Monte Carlo simulation. © 2019, Springer Nature Singapore Pte Ltd.
dc.identifier.citationLecture Notes in Electrical Engineering, 2019, Vol.553, , p. 1159-1168
dc.identifier.issn18761100
dc.identifier.urihttps://doi.org/10.1007/978-981-13-6772-4_101
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/31211
dc.publisherSpringer Verlag service@springer.de
dc.subjectHybrid method
dc.subjectPhotovoltaic generation
dc.subjectProbabilistic load flow
dc.subjectTransmission system
dc.titleProbabilistic Load Flow in a Transmission System Integrated with Photovoltaic Generations

Files

Collections

Conference Papers