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Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration

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dc.contributor.authorNagi F.en_US
dc.contributor.authorAzwin A.en_US
dc.contributor.authorBoopalan N.en_US
dc.contributor.authorRamasamy A.K.en_US
dc.contributor.authorMarsadek M.en_US
dc.contributor.authorAhmed S.K.en_US
dc.contributor.authorid56272534200en_US
dc.contributor.authorid57201882059en_US
dc.contributor.authorid57211414491en_US
dc.contributor.authorid16023154400en_US
dc.contributor.authorid26423183000en_US
dc.contributor.authorid25926812900en_US
dc.date.accessioned2023-05-29T09:36:22Z
dc.date.available2023-05-29T09:36:22Z
dc.date.issued2022
dc.description.abstractRenewable energy sources and EV growth brings new challenges for grid stabilization. Smart grid techniques are required to reconfigure and compensate for load fluctuation and stabilize power losses and voltage fluctuation. Numerical tools are available to equip the smart grid to deal with such challenges. Distribution Feeder reconfiguration and reactive voltage injection to the disturbed grid are some of the techniques employed for the purpose. However, either reconfiguration or injection alone is used commonly for this purpose. In this study, both techniques are applied to EV penetration as load and compared. A balanced IEEE 33 Radial network is used in this study and selected branches with high power losses are targeted for the reactive voltage injection and Minimum Spanning tree techniques (MST). EV charging loads are usually modelled with time base distribution which requires times base power flow analysis for reactive power injection. A comparison between coordinated, reconfiguration, and reactive voltage injection shows differences in power losses, voltage distortion, and cost saving. The analysis is carried out with an integer linear programming technique for coordinated charging, a minimum spanning tree for network reconfiguration, and genetic optimization for reactive power injection. Besides, all power flow analyses are carried out with the Backward/Forward sweep method. The information would help lowering power losses, grid stabilization, and charging station infrastructure planning. � 2022 by the authors.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo3221
dc.identifier.doi10.3390/electronics11193221
dc.identifier.issue19
dc.identifier.scopus2-s2.0-85139848309
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85139848309&doi=10.3390%2felectronics11193221&partnerID=40&md5=8caeec2fd3028a52a4ea0ea5956df460
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26728
dc.identifier.volume11
dc.publisherMDPIen_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleElectronics (Switzerland)
dc.titleComparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetrationen_US
dc.typeArticleen_US
dspace.entity.typePublication
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