A multi-agent system based residential electric vehicle management system for grid-support service

M. S. H. Nizami, M. J. Hossain, Sohaib Rafique, Khizir Mahmud, U. B. Irshad, Graham Town

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Abstract

With a spike in popularity and sales, the electric vehicles (EVs) have revolutionized the transportation industry. As EV technology advances, the EVs are becoming more accessible and affordable. Therefore, a rapid proliferation of light-duty EVs have been noticed in the residential sector. Even though the increased charging demand of EVs is manageable in large-scale, the low-voltage (LV) residential networks might not be capable of managing localized capacity issues of large scale EV integration. Dynamic electricity tariff coupled with demand response and smart charging management can provide grid assistance to some extent. However, uncoordinated charging, if clustered in a residential distribution feeder, can risk grid assets because of overloading and can even jeopardize the reliability of the network by violating voltage constraints. This paper proposes a coordinated residential EV management system for power grid support. Charging and discharging of residential EV batteries are coordinated and optimized to address grid overloading during peak demand periods and voltage constraint violations. The EV management for grid support is formulated as a mixed-integer programming based optimization problem to minimize the inconveniences of EV owner while providing grid assistance. The proposed methodology is evaluated via a case study based on a residential feeder in Sydney, Australia with actual load demand data. The simulation results indicate the efficacy of the proposed EV management method for mitigating grid overloading and maintaining desired bus voltages.

LanguageEnglish
Title of host publicationConference proceedings 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe)
Subtitle of host publication11-14 June, 2019, Genoa, Italy
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9781728106533, 9781728106526
ISBN (Print)9781728106540
DOIs
Publication statusPublished - 2019
Event19th IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2019 - Genoa, Italy
Duration: 11 Jun 201914 Jun 2019

Conference

Conference19th IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2019
CountryItaly
CityGenoa
Period11/06/1914/06/19

Fingerprint

Electric Vehicle
Electric vehicles
Multi agent systems
Multi-agent Systems
Grid
Electric potential
Voltage
Integer programming
Low Voltage
Mixed Integer Programming
Proliferation
Electricity
Spike
Battery
Sales
Efficacy
Sector
Industry
Optimization Problem
Minimise

Cite this

Nizami, M. S. H., Hossain, M. J., Rafique, S., Mahmud, K., Irshad, U. B., & Town, G. (2019). A multi-agent system based residential electric vehicle management system for grid-support service. In Conference proceedings 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe): 11-14 June, 2019, Genoa, Italy Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EEEIC.2019.8783799
Nizami, M. S. H. ; Hossain, M. J. ; Rafique, Sohaib ; Mahmud, Khizir ; Irshad, U. B. ; Town, Graham. / A multi-agent system based residential electric vehicle management system for grid-support service. Conference proceedings 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe): 11-14 June, 2019, Genoa, Italy. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2019.
@inproceedings{cc1299c52c5940e6ad036190ff1b15cd,
title = "A multi-agent system based residential electric vehicle management system for grid-support service",
abstract = "With a spike in popularity and sales, the electric vehicles (EVs) have revolutionized the transportation industry. As EV technology advances, the EVs are becoming more accessible and affordable. Therefore, a rapid proliferation of light-duty EVs have been noticed in the residential sector. Even though the increased charging demand of EVs is manageable in large-scale, the low-voltage (LV) residential networks might not be capable of managing localized capacity issues of large scale EV integration. Dynamic electricity tariff coupled with demand response and smart charging management can provide grid assistance to some extent. However, uncoordinated charging, if clustered in a residential distribution feeder, can risk grid assets because of overloading and can even jeopardize the reliability of the network by violating voltage constraints. This paper proposes a coordinated residential EV management system for power grid support. Charging and discharging of residential EV batteries are coordinated and optimized to address grid overloading during peak demand periods and voltage constraint violations. The EV management for grid support is formulated as a mixed-integer programming based optimization problem to minimize the inconveniences of EV owner while providing grid assistance. The proposed methodology is evaluated via a case study based on a residential feeder in Sydney, Australia with actual load demand data. The simulation results indicate the efficacy of the proposed EV management method for mitigating grid overloading and maintaining desired bus voltages.",
author = "Nizami, {M. S. H.} and Hossain, {M. J.} and Sohaib Rafique and Khizir Mahmud and Irshad, {U. B.} and Graham Town",
year = "2019",
doi = "10.1109/EEEIC.2019.8783799",
language = "English",
isbn = "9781728106540",
booktitle = "Conference proceedings 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe)",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
address = "United States",

}

Nizami, MSH, Hossain, MJ, Rafique, S, Mahmud, K, Irshad, UB & Town, G 2019, A multi-agent system based residential electric vehicle management system for grid-support service. in Conference proceedings 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe): 11-14 June, 2019, Genoa, Italy. Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, 19th IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2019, Genoa, Italy, 11/06/19. https://doi.org/10.1109/EEEIC.2019.8783799

A multi-agent system based residential electric vehicle management system for grid-support service. / Nizami, M. S. H.; Hossain, M. J.; Rafique, Sohaib; Mahmud, Khizir; Irshad, U. B.; Town, Graham.

Conference proceedings 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe): 11-14 June, 2019, Genoa, Italy. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2019.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

TY - GEN

T1 - A multi-agent system based residential electric vehicle management system for grid-support service

AU - Nizami, M. S. H.

AU - Hossain, M. J.

AU - Rafique, Sohaib

AU - Mahmud, Khizir

AU - Irshad, U. B.

AU - Town, Graham

PY - 2019

Y1 - 2019

N2 - With a spike in popularity and sales, the electric vehicles (EVs) have revolutionized the transportation industry. As EV technology advances, the EVs are becoming more accessible and affordable. Therefore, a rapid proliferation of light-duty EVs have been noticed in the residential sector. Even though the increased charging demand of EVs is manageable in large-scale, the low-voltage (LV) residential networks might not be capable of managing localized capacity issues of large scale EV integration. Dynamic electricity tariff coupled with demand response and smart charging management can provide grid assistance to some extent. However, uncoordinated charging, if clustered in a residential distribution feeder, can risk grid assets because of overloading and can even jeopardize the reliability of the network by violating voltage constraints. This paper proposes a coordinated residential EV management system for power grid support. Charging and discharging of residential EV batteries are coordinated and optimized to address grid overloading during peak demand periods and voltage constraint violations. The EV management for grid support is formulated as a mixed-integer programming based optimization problem to minimize the inconveniences of EV owner while providing grid assistance. The proposed methodology is evaluated via a case study based on a residential feeder in Sydney, Australia with actual load demand data. The simulation results indicate the efficacy of the proposed EV management method for mitigating grid overloading and maintaining desired bus voltages.

AB - With a spike in popularity and sales, the electric vehicles (EVs) have revolutionized the transportation industry. As EV technology advances, the EVs are becoming more accessible and affordable. Therefore, a rapid proliferation of light-duty EVs have been noticed in the residential sector. Even though the increased charging demand of EVs is manageable in large-scale, the low-voltage (LV) residential networks might not be capable of managing localized capacity issues of large scale EV integration. Dynamic electricity tariff coupled with demand response and smart charging management can provide grid assistance to some extent. However, uncoordinated charging, if clustered in a residential distribution feeder, can risk grid assets because of overloading and can even jeopardize the reliability of the network by violating voltage constraints. This paper proposes a coordinated residential EV management system for power grid support. Charging and discharging of residential EV batteries are coordinated and optimized to address grid overloading during peak demand periods and voltage constraint violations. The EV management for grid support is formulated as a mixed-integer programming based optimization problem to minimize the inconveniences of EV owner while providing grid assistance. The proposed methodology is evaluated via a case study based on a residential feeder in Sydney, Australia with actual load demand data. The simulation results indicate the efficacy of the proposed EV management method for mitigating grid overloading and maintaining desired bus voltages.

UR - http://www.scopus.com/inward/record.url?scp=85070827013&partnerID=8YFLogxK

U2 - 10.1109/EEEIC.2019.8783799

DO - 10.1109/EEEIC.2019.8783799

M3 - Conference proceeding contribution

SN - 9781728106540

BT - Conference proceedings 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe)

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

ER -

Nizami MSH, Hossain MJ, Rafique S, Mahmud K, Irshad UB, Town G. A multi-agent system based residential electric vehicle management system for grid-support service. In Conference proceedings 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe): 11-14 June, 2019, Genoa, Italy. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2019 https://doi.org/10.1109/EEEIC.2019.8783799