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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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 |
_version_ |
1721512524476579840 |