Comparative Evaluation of Basic Probabilistic Load Flow Methods with Wind Power Integration

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dc.contributor.authorSingh, V.
dc.contributor.authorMoger, T.
dc.contributor.authorJena, D.
dc.date.accessioned2026-02-06T06:35:57Z
dc.date.issued2021
dc.description.abstractThe unprecedented penetration of distributed energy resources (DERs) such as wind power generations (WPGs) poses tremendous challenges for for the planning and maintenance of power systems due to their intermittent and uncertain nature. This paper mainly focuses on comparing basic probabilistic load flow (PLF) techniques when WPGs are integrated into the existing power grid. Considering loads and WPGs as random inputs, the performance of the cumulant method (CM) and point estimation method (PEM) are analyzed with respect to Monte-Carlo method for higher precision and less computational time. Case-studies are carried out on sample 10-bus and SR 72-bus equivalent systems. Simulation results demonstrated that 2n+1 PEM provides the best performance when dealing with high level of uncertainty associated with input variables. © 2021 IEEE.
dc.identifier.citation3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies, ICEPE 2020, 2021, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/ICEPE50861.2021.9404524
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/30164
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectAnalytical methods
dc.subjectApproximate methods
dc.subjectMonte-Carlo simulation
dc.subjectProbabilistic load flow
dc.titleComparative Evaluation of Basic Probabilistic Load Flow Methods with Wind Power Integration

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