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

Algorithms; 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 obj...

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Main Authors: Tan K.M., Ramachandaramurthy V.K., Yong J.Y.
Other Authors: 56119108600
Format: Article
Published: Elsevier Ltd 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-226502023-05-29T14:11:29Z Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm Tan K.M. Ramachandaramurthy V.K. Yong J.Y. 56119108600 6602912020 56119339200 Algorithms; 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 development Vehicle 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 Ltd Final 2023-05-29T06:11:29Z 2023-05-29T06:11:29Z 2016 Article 10.1016/j.energy.2016.07.008 2-s2.0-84978883538 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978883538&doi=10.1016%2fj.energy.2016.07.008&partnerID=40&md5=8d5007f6e3d069f79e79760042c92bb0 https://irepository.uniten.edu.my/handle/123456789/22650 112 1060 1073 Elsevier Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Algorithms; 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 development
author2 56119108600
author_facet 56119108600
Tan K.M.
Ramachandaramurthy V.K.
Yong J.Y.
format Article
author Tan K.M.
Ramachandaramurthy V.K.
Yong J.Y.
spellingShingle Tan K.M.
Ramachandaramurthy V.K.
Yong J.Y.
Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm
author_sort Tan K.M.
title Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm
title_short Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm
title_full Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm
title_fullStr Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm
title_full_unstemmed Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm
title_sort optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm
publisher Elsevier Ltd
publishDate 2023
_version_ 1806428428698648576