Publication:
Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm

Simple item page
dc.citedby26
dc.contributor.authorTan K.M.en_US
dc.contributor.authorRamachandaramurthy V.K.en_US
dc.contributor.authorYong J.Y.en_US
dc.contributor.authorid56119108600en_US
dc.contributor.authorid6602912020en_US
dc.contributor.authorid56119339200en_US
dc.date.accessioned2023-05-29T06:11:29Z
dc.date.available2023-05-29T06:11:29Z
dc.date.issued2016
dc.descriptionAlgorithms; Charging (batteries); Curve fitting; Electric load flow; Electric power systems; Electric vehicles; Energy management systems; Optimization; Reactive power; Real time control; Scheduling; Vehicles; Voltage control; Voltage regulators; Battery chargers; Bidirectional power flow; Multi objective algorithm; Optimization algorithms; Reactive power compensation; Real-time implementations; Revolutionary technology; Vehicle to grids; Electric power transmission networks; algorithm; electric vehicle; electricity supply; energy flow; energy planning; energy use; optimization; technological developmenten_US
dc.description.abstractVehicle to grid is a revolutionary technology that allows energy exchange between electric vehicles and power grid for mutual advantages. The implementation of appropriate vehicle to grid energy management system can maximize the potential of electric vehicles to provide grid ancillary services. This paper proposes an optimal vehicle to grid planning and scheduling by utilizing a novel double layer multi-objective algorithm. This optimization algorithm utilizes the grid-connected electric vehicles to perform peak load shaving and load levelling services to minimize the power grid load variance in the first layer optimization. Meanwhile, the second layer optimization minimizes the reactive power compensation for grid voltage regulation and therefore, optimizes the vehicle to grid charger's capacitor sizing. The second layer optimization algorithm utilizes an approximated formula from the simulation of a vehicle to grid charger. The proposed vehicle to grid optimization algorithm considers various power grid and electric vehicle constraints for practicality purpose. With the real time implementation of the proposed algorithm, the optimization results show that the power load curve is effectively followed the preset constant target loading, while the grid voltage is successfully regulated to the predetermined voltage level with minimal amount of reactive power supply from the optimal charger's capacitor. � 2016 Elsevier Ltden_US
dc.description.natureFinalen_US
dc.identifier.doi10.1016/j.energy.2016.07.008
dc.identifier.epage1073
dc.identifier.scopus2-s2.0-84978883538
dc.identifier.spage1060
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84978883538&doi=10.1016%2fj.energy.2016.07.008&partnerID=40&md5=8d5007f6e3d069f79e79760042c92bb0
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22650
dc.identifier.volume112
dc.publisherElsevier Ltden_US
dc.sourceScopus
dc.sourcetitleEnergy
dc.titleOptimal vehicle to grid planning and scheduling using double layer multi-objective algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
Files
Collections
SCOPUS