Key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation

Abstract Growing penetration of Electric Vehicles (EV) and Distributed Generation (DG) is driving sharper peaks in demand and supply, which, if poorly managed, manifest as over‐ or undervoltage and disrupt grid service quality. Smart charging schemes reschedule EV charging load according to factors...

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Autores principales: John W. Heron, Hongjian Sun, Omid Alizadeh‐Mousavi, Andrew Crossland
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Lenguaje:EN
Publicado: Wiley 2021
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Acceso en línea:https://doaj.org/article/019e3881b8fc4196955fdfb96860e349
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spelling oai:doaj.org-article:019e3881b8fc4196955fdfb96860e3492021-11-13T03:16:47ZKey performance‐cost tradeoffs in smart electric vehicle charging with distributed generation2515-294710.1049/stg2.12041https://doaj.org/article/019e3881b8fc4196955fdfb96860e3492021-12-01T00:00:00Zhttps://doi.org/10.1049/stg2.12041https://doaj.org/toc/2515-2947Abstract Growing penetration of Electric Vehicles (EV) and Distributed Generation (DG) is driving sharper peaks in demand and supply, which, if poorly managed, manifest as over‐ or undervoltage and disrupt grid service quality. Smart charging schemes reschedule EV charging load according to factors such as grid stability, price signals, etc. It remains unclear how to do this while meeting the diverging needs and expectations of multiple concerned participants. This paper proposes two smart charging schemes for secondary voltage control in the distribution network and analyses performance‐cost tradeoffs relating to key players in the Smart Grid. To support these schemes, a distributed communications architecture is designed that jointly minimises traffic burden, computation load and investment in Information and Communications Technology (ICT) hardware. Scheme I (Smart Curtailment), curtails load and DG for peak shaving. Scheme II (Smart Correction) optimises cost‐efficiency for subscribing users by maximising power transfer during off‐peak hours or when renewable energy is high. Performance of both schemes is consolidated statistically under almost 6 months of practical input profiles. Dramatic improvements in EV & DG capacity are demonstrated and key performance‐cost tradeoffs relating to Voltage Control, Peak Shaving, User Inconvenience, CO2 Emissions and ICT Deployment Cost are identified.John W. HeronHongjian SunOmid Alizadeh‐MousaviAndrew CrosslandWileyarticleElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIET Smart Grid, Vol 4, Iss 6, Pp 561-581 (2021)
institution DOAJ
collection DOAJ
language EN
topic Electrical engineering. Electronics. Nuclear engineering
TK1-9971
spellingShingle Electrical engineering. Electronics. Nuclear engineering
TK1-9971
John W. Heron
Hongjian Sun
Omid Alizadeh‐Mousavi
Andrew Crossland
Key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation
description Abstract Growing penetration of Electric Vehicles (EV) and Distributed Generation (DG) is driving sharper peaks in demand and supply, which, if poorly managed, manifest as over‐ or undervoltage and disrupt grid service quality. Smart charging schemes reschedule EV charging load according to factors such as grid stability, price signals, etc. It remains unclear how to do this while meeting the diverging needs and expectations of multiple concerned participants. This paper proposes two smart charging schemes for secondary voltage control in the distribution network and analyses performance‐cost tradeoffs relating to key players in the Smart Grid. To support these schemes, a distributed communications architecture is designed that jointly minimises traffic burden, computation load and investment in Information and Communications Technology (ICT) hardware. Scheme I (Smart Curtailment), curtails load and DG for peak shaving. Scheme II (Smart Correction) optimises cost‐efficiency for subscribing users by maximising power transfer during off‐peak hours or when renewable energy is high. Performance of both schemes is consolidated statistically under almost 6 months of practical input profiles. Dramatic improvements in EV & DG capacity are demonstrated and key performance‐cost tradeoffs relating to Voltage Control, Peak Shaving, User Inconvenience, CO2 Emissions and ICT Deployment Cost are identified.
format article
author John W. Heron
Hongjian Sun
Omid Alizadeh‐Mousavi
Andrew Crossland
author_facet John W. Heron
Hongjian Sun
Omid Alizadeh‐Mousavi
Andrew Crossland
author_sort John W. Heron
title Key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation
title_short Key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation
title_full Key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation
title_fullStr Key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation
title_full_unstemmed Key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation
title_sort key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation
publisher Wiley
publishDate 2021
url https://doaj.org/article/019e3881b8fc4196955fdfb96860e349
work_keys_str_mv AT johnwheron keyperformancecosttradeoffsinsmartelectricvehiclechargingwithdistributedgeneration
AT hongjiansun keyperformancecosttradeoffsinsmartelectricvehiclechargingwithdistributedgeneration
AT omidalizadehmousavi keyperformancecosttradeoffsinsmartelectricvehiclechargingwithdistributedgeneration
AT andrewcrossland keyperformancecosttradeoffsinsmartelectricvehiclechargingwithdistributedgeneration
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