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dc.contributor.authorAhmed, Toqeer
dc.contributor.authorMian Qaisar, Saeed
dc.contributor.authorWaqar, Asad
dc.contributor.authorHussain, Tanveer
dc.contributor.authorIqbal, Ahsan
dc.date.accessioned2023-03-13T07:44:58Z
dc.date.available2023-03-13T07:44:58Z
dc.date.issued2022-12-30
dc.identifier.doihttps://doi.org/10.1109/ICIT56493.2022.9989003en_US
dc.identifier.urihttp://hdl.handle.net/20.500.14131/607
dc.descriptionThis work is funded by the Effat University under the grant number (UC#9/2June2021/7.2-21(3)5)en_US
dc.description.abstractElectric vehicles (EVs) always integrate into the utility grid via power electronics interfaces like voltage source converters (VSCs). The VSCs manage the power flow between the utility grid and the EVs in bidirectional mode depending upon various conditions. However, the smooth transition of the bidirectional mode depends upon the controller used to drive the references of the VSC. In this paper, the transient performance of the VSC in vehicle- to-grid (V2G) and grid- to-vehicle( G 2V) EVs application is tested under voltage sag/swell using the fractional order sliding mode control (FOSMC). The primary focus is to manage the power flow between the utility grid and the EVs based on the state of charge (SOC) of the EV battery and the ampacity of the utility grid under grid transients. A simulation model with a utility grid, VSC, and an EV battery has been modeled at 180kVAR, 400V, and 50 Hz distribution feeder. The stability analysis of FOSMC has been ensured with the Lyapunov candidate function. The results of the proposed control have been compared with the classical PI control. It has been noticed that the proposed control is robust in terms of speedy tracking, fast convergence, and finest damping.en_US
dc.description.sponsorshipEffat Universityen_US
dc.publisherIEEEen_US
dc.subjectElectric vehicles; voltage source converters; vehicle- to-grid; grid- to-vehicle; fractional order sliding mode control; state of chargeen_US
dc.titleTransient Performance of Voltage Source Converter in V2G and G2V Electric Vehicles Applicationen_US
dc.contributor.researcherExternal Collaborationen_US
dc.subject.KSAENERGYen_US
dc.title.projectLoad Prediction for Electric Vehicles Charging in Smart Griden_US
dc.source.indexScopusen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.conference.name2022 International Conference on IT and Industrial Technologies (ICIT)en_US
dc.conference.date2022-10-03


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