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AuthorAlzaareer, Khaled
AuthorSaad, Maarouf
AuthorMehrjerdi, Hasan
AuthorAl-Masri, Hussein M.K.
AuthorAl-Shetwi, Ali Q.
AuthorAsber, Dalal
AuthorLefebvre, Serge
Available date2022-11-14T10:49:11Z
Publication Date2022
Publication NameInternational Journal of Electrical Power and Energy Systems
ResourceScopus
Resource2-s2.0-85120360932
URIhttp://dx.doi.org/10.1016/j.ijepes.2021.107799
URIhttp://hdl.handle.net/10576/36347
AbstractSensitivity Analysis plays a significant role in voltage prediction and control of power networks. However, the classical sensitivity methods require significant computation time. As active distribution networks require real-time implementation for voltage control, reducing the computation time becomes a necessary task for network operators, especially in the context of optimization techniques. This work develops a new analytical and fast voltage sensitivity analysis method via the derivative of the nodal quantities (power, current and voltage) with respect to power injections. The proposed method mainly depends on the construction of the ABCD matrix. The values of the matrix elements remain the same regardless of the bus on which the power is injected. Thus, it has a high potential to be implemented in online applications. To make a complete separation between the sensitivities to active and the sensitivities to reactive power injections, the analytical formulations are expressed in Cartesian coordinates. A radial distribution network including several DG units is used to verify and assess the proposed sensitivity method under different scenarios. 2021 Elsevier Ltd
SponsorThis work was supported by the National Priorities Research Program under Grant 11S-1125-170027 from the Qatar National Research Fund (a member of Qatar Foundation).
Languageen
PublisherElsevier
SubjectCartesian coordinates
DG units
Jacobian matrix
Sensitivity analysis
Smart power networks
Voltage control
TitleNew voltage sensitivity analysis for smart distribution grids using analytical derivation: ABCD model
TypeArticle
Volume Number137
dc.accessType Abstract Only


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