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dc.contributor.authorRajanarayan, Prusty, B.
dc.contributor.authorJena, D.
dc.date.accessioned2020-03-30T10:22:53Z-
dc.date.available2020-03-30T10:22:53Z-
dc.date.issued2019
dc.identifier.citationLecture Notes in Electrical Engineering, 2019, Vol.553, , pp.1159-1168en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8855-
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.en_US
dc.titleProbabilistic Load Flow in a Transmission System Integrated with Photovoltaic Generationsen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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