Agent based aggregated behavior modelling for electric vehicle charging load

Widespread adoption of electric vehicles (EVs) would significantly increase the overall electrical load demand in power distribution networks. Hence, there is a need for comprehensive planning of charging infrastructure in order to prevent power failures or scenarios where there is a considerable de...

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Main Authors: Chaudhari, Kalpesh Subhash, Kandasamy, Nandha Kumar, Krishnan, Ashok, Ukil, Abhisek, Gooi, Hoay Beng
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2018
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Online Access:https://hdl.handle.net/10356/89511
http://hdl.handle.net/10220/44931
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-895112020-03-07T14:02:38Z Agent based aggregated behavior modelling for electric vehicle charging load Chaudhari, Kalpesh Subhash Kandasamy, Nandha Kumar Krishnan, Ashok Ukil, Abhisek Gooi, Hoay Beng School of Electrical and Electronic Engineering Agent Based Model Electric Vehicles Widespread adoption of electric vehicles (EVs) would significantly increase the overall electrical load demand in power distribution networks. Hence, there is a need for comprehensive planning of charging infrastructure in order to prevent power failures or scenarios where there is a considerable demand-supply mismatch. Accurately predicting the realistic charging demand of EVs is an essential part of the infrastructure planning. Charging demand of EVs is influenced by several factors such as driver behavior, location of charging stations, electricity pricing etc. In order to implement an optimal charging infrastructure, it is important to consider all the relevant factors which influence the charging demand of EVs. Several studies have modelled and simulated the charging demands of individual and groups of EVs. However, in many cases, the models do not consider factors related to the social characteristics of EV drivers. Other studies do not emphasize on economic elements. This paper aims at evaluating the effects of the above factors on EV charging demand using a simulation model. An agent-based approach using NetLogo is employed in this paper to closely mimic the human aggregate behaviour and its influence on the load demand due to charging of EVs. NRF (Natl Research Foundation, S’pore) Accepted version 2018-06-01T05:25:15Z 2019-12-06T17:27:20Z 2018-06-01T05:25:15Z 2019-12-06T17:27:20Z 2018 Journal Article Chaudhari, K. S., Kandasamy, N. K., Krishnan, A., Ukil, A., & Gooi, H. B. Agent Based Aggregated Behavior Modelling For Electric Vehicle Charging Load. IEEE Transactions on Industrial Informatics, in press. 1551-3203 https://hdl.handle.net/10356/89511 http://hdl.handle.net/10220/44931 10.1109/TII.2018.2823321 en_US IEEE Transactions on Industrial Informatics © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TII.2018.2823321]. 13 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Agent Based Model
Electric Vehicles
spellingShingle Agent Based Model
Electric Vehicles
Chaudhari, Kalpesh Subhash
Kandasamy, Nandha Kumar
Krishnan, Ashok
Ukil, Abhisek
Gooi, Hoay Beng
Agent based aggregated behavior modelling for electric vehicle charging load
description Widespread adoption of electric vehicles (EVs) would significantly increase the overall electrical load demand in power distribution networks. Hence, there is a need for comprehensive planning of charging infrastructure in order to prevent power failures or scenarios where there is a considerable demand-supply mismatch. Accurately predicting the realistic charging demand of EVs is an essential part of the infrastructure planning. Charging demand of EVs is influenced by several factors such as driver behavior, location of charging stations, electricity pricing etc. In order to implement an optimal charging infrastructure, it is important to consider all the relevant factors which influence the charging demand of EVs. Several studies have modelled and simulated the charging demands of individual and groups of EVs. However, in many cases, the models do not consider factors related to the social characteristics of EV drivers. Other studies do not emphasize on economic elements. This paper aims at evaluating the effects of the above factors on EV charging demand using a simulation model. An agent-based approach using NetLogo is employed in this paper to closely mimic the human aggregate behaviour and its influence on the load demand due to charging of EVs.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Chaudhari, Kalpesh Subhash
Kandasamy, Nandha Kumar
Krishnan, Ashok
Ukil, Abhisek
Gooi, Hoay Beng
format Article
author Chaudhari, Kalpesh Subhash
Kandasamy, Nandha Kumar
Krishnan, Ashok
Ukil, Abhisek
Gooi, Hoay Beng
author_sort Chaudhari, Kalpesh Subhash
title Agent based aggregated behavior modelling for electric vehicle charging load
title_short Agent based aggregated behavior modelling for electric vehicle charging load
title_full Agent based aggregated behavior modelling for electric vehicle charging load
title_fullStr Agent based aggregated behavior modelling for electric vehicle charging load
title_full_unstemmed Agent based aggregated behavior modelling for electric vehicle charging load
title_sort agent based aggregated behavior modelling for electric vehicle charging load
publishDate 2018
url https://hdl.handle.net/10356/89511
http://hdl.handle.net/10220/44931
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