Procedural simulation method for aggregating charging load model of private electric vehicle cluster

The usage of each private electric vehicle (PrEV) is a repeating behavior process composed by driving, parking, discharging and charging, in which PrEV shows obvious procedural characteristics. To analyze the procedural characteristics, this paper proposes a procedural simulation method. The method...

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Main Authors: Mingfei Ban, Jilai Yu
Format: Article
Language:English
Published: IEEE 2015-01-01
Series:Journal of Modern Power Systems and Clean Energy
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9018446/
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spelling doaj-40a9a5e6eb594306b429ff1e821c86902021-04-23T16:11:59ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202015-01-013217017910.1007/s40565-015-0125-z9018446Procedural simulation method for aggregating charging load model of private electric vehicle clusterMingfei Ban0Jilai Yu1Harbin Institute of Technology,Harbin,HLJ,China,150001Harbin Institute of Technology,Harbin,HLJ,China,150001The usage of each private electric vehicle (PrEV) is a repeating behavior process composed by driving, parking, discharging and charging, in which PrEV shows obvious procedural characteristics. To analyze the procedural characteristics, this paper proposes a procedural simulation method. The method aggregates the behavior process regularity of the PrEV cluster to model the cluster's charging load. Firstly, the basic behavior process of each PrEV is constructed by referring the statistical datasets of the traditional private non-electric vehicles. Secondly, all the basic processes are set as a simulation starting point, and they are dynamically reconstructed by several constraints. The simulation continues until the steady state of charge (SOC) distribution and behavior regularity of the PrEV cluster are obtained. Lastly, based on the obtained SOC and behavior regularity information, the PrEV cluster's behavior processes are simulated again to make the aggregating charging load model available. Examples for several scenarios show that the proposed method can improve the reliability of modeling by grasping the PrEV cluster's procedural characteristics.https://ieeexplore.ieee.org/document/9018446/Electric vehicle (EV)Private electric vehicle (PrEV)Charging load modelState of charge (SOC)Procedural simulationCluster
collection DOAJ
language English
format Article
sources DOAJ
author Mingfei Ban
Jilai Yu
spellingShingle Mingfei Ban
Jilai Yu
Procedural simulation method for aggregating charging load model of private electric vehicle cluster
Journal of Modern Power Systems and Clean Energy
Electric vehicle (EV)
Private electric vehicle (PrEV)
Charging load model
State of charge (SOC)
Procedural simulation
Cluster
author_facet Mingfei Ban
Jilai Yu
author_sort Mingfei Ban
title Procedural simulation method for aggregating charging load model of private electric vehicle cluster
title_short Procedural simulation method for aggregating charging load model of private electric vehicle cluster
title_full Procedural simulation method for aggregating charging load model of private electric vehicle cluster
title_fullStr Procedural simulation method for aggregating charging load model of private electric vehicle cluster
title_full_unstemmed Procedural simulation method for aggregating charging load model of private electric vehicle cluster
title_sort procedural simulation method for aggregating charging load model of private electric vehicle cluster
publisher IEEE
series Journal of Modern Power Systems and Clean Energy
issn 2196-5420
publishDate 2015-01-01
description The usage of each private electric vehicle (PrEV) is a repeating behavior process composed by driving, parking, discharging and charging, in which PrEV shows obvious procedural characteristics. To analyze the procedural characteristics, this paper proposes a procedural simulation method. The method aggregates the behavior process regularity of the PrEV cluster to model the cluster's charging load. Firstly, the basic behavior process of each PrEV is constructed by referring the statistical datasets of the traditional private non-electric vehicles. Secondly, all the basic processes are set as a simulation starting point, and they are dynamically reconstructed by several constraints. The simulation continues until the steady state of charge (SOC) distribution and behavior regularity of the PrEV cluster are obtained. Lastly, based on the obtained SOC and behavior regularity information, the PrEV cluster's behavior processes are simulated again to make the aggregating charging load model available. Examples for several scenarios show that the proposed method can improve the reliability of modeling by grasping the PrEV cluster's procedural characteristics.
topic Electric vehicle (EV)
Private electric vehicle (PrEV)
Charging load model
State of charge (SOC)
Procedural simulation
Cluster
url https://ieeexplore.ieee.org/document/9018446/
work_keys_str_mv AT mingfeiban proceduralsimulationmethodforaggregatingchargingloadmodelofprivateelectricvehiclecluster
AT jilaiyu proceduralsimulationmethodforaggregatingchargingloadmodelofprivateelectricvehiclecluster
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