Probabilistic Optimal Power Flow in the Presence of Uncertainties Related with Load Wind and PV Considering Different Load Models

dc.contributor.authorMahmmadsufiyan, S.
dc.contributor.authorGaonkar, D.N.
dc.date.accessioned2026-02-06T06:35:45Z
dc.date.issued2022
dc.description.abstractThe conventional Power Flow and Optimal Power Flow (OPF) consider the Power System variables as certain quantities. But the uncertain nature of real time power system variables and the increased integration of renewable energy generation lead the modern power systems to account these uncertainties in their planning and operation. This paper presents the handling of uncertainties in solving the Probabilistic Optimal Power Flow (POPF) problem in the context of operating cost minimization, by using Point Estimate Method (PEM). In this work the uncertainties related with load power, Wind and Photovoltaic (PV) are considered. And to analyze the impact of the voltage dependency nature of loads, constant current and constant impedance load models are also considered. The POPF problem is solved for IEEE-9 bus and IEEE-57 bus test systems by using PEM and the results are compared against Monte Carlo Simulation (MCS). © 2022 IEEE
dc.identifier.citationPESGRE 2022 - IEEE International Conference on "Power Electronics, Smart Grid, and Renewable Energy", 2022, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/PESGRE52268.2022.9715906
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/30023
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectBeta distribution
dc.subjectMonte Carlo Simulation (MCS)
dc.subjectPoint Estimate Method (PEM)
dc.subjectWeibull Distribution
dc.titleProbabilistic Optimal Power Flow in the Presence of Uncertainties Related with Load Wind and PV Considering Different Load Models

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