A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system

Shu Wang; Yan Xu; Zhao Yang Dong; Junhua Zhao; Weifeng Yao; Fengji Luo; Yijia Wang

doi:10.1109/PESGM.2016.7741442

A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system

Shu Wang, Yan Xu, Zhao Yang Dong, Junhua Zhao, Weifeng Yao, Fengji Luo, Yijia Wang

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

18 Citations (Scopus)

Abstract

The increasingly prevalence of electric vehicles (EVs) calls for the effective planning of the charging infrastructure. In this paper, a multi-objective, multi-stage collaborative planning model is proposed for the EV charging stations and power distribution network. The model aims to minimize the investment & operation costs of the distribution system while maximizing the annually captured traffic flow. The uncertainties of the charging loads are considered. The MOEA/D algorithm is employed to find the Pareto frontier of the model. The simulation results prove the effectiveness of the model. © 2016 IEEE.

Original language	English
Title of host publication	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Publisher	IEEE Computer Society
Volume	2016-November
ISBN (Print)	9781509041688
DOIs	https://doi.org/10.1109/PESGM.2016.7741442
Publication status	Published - 10 Nov 2016
Externally published	Yes
Event	2016 IEEE Power and Energy Society General Meeting, PESGM 2016 - Boston, United States Duration: 17 Jul 2016 → 21 Jul 2016

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2016-November
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Place	United States
City	Boston
Period	17/07/16 → 21/07/16

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

Charging station
Distribution system planning
Electric vehicle
Multi-objective optimization
Smart grid

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10.1109/PESGM.2016.7741442

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Wang, S., Xu, Y., Dong, Z. Y., Zhao, J., Yao, W., Luo, F., & Wang, Y. (2016). A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system. In 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 (Vol. 2016-November). Article 7741442 (IEEE Power and Energy Society General Meeting; Vol. 2016-November). IEEE Computer Society. https://doi.org/10.1109/PESGM.2016.7741442

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title = "A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system",

abstract = "The increasingly prevalence of electric vehicles (EVs) calls for the effective planning of the charging infrastructure. In this paper, a multi-objective, multi-stage collaborative planning model is proposed for the EV charging stations and power distribution network. The model aims to minimize the investment & operation costs of the distribution system while maximizing the annually captured traffic flow. The uncertainties of the charging loads are considered. The MOEA/D algorithm is employed to find the Pareto frontier of the model. The simulation results prove the effectiveness of the model. {\textcopyright} 2016 IEEE.",

keywords = "Charging station, Distribution system planning, Electric vehicle, Multi-objective optimization, Smart grid",

author = "Shu Wang and Yan Xu and Dong, {Zhao Yang} and Junhua Zhao and Weifeng Yao and Fengji Luo and Yijia Wang",

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Wang, S, Xu, Y, Dong, ZY, Zhao, J, Yao, W, Luo, F & Wang, Y 2016, A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system. in 2016 IEEE Power and Energy Society General Meeting, PESGM 2016. vol. 2016-November, 7741442, IEEE Power and Energy Society General Meeting, vol. 2016-November, IEEE Computer Society, 2016 IEEE Power and Energy Society General Meeting, PESGM 2016, Boston, United States, 17/07/16. https://doi.org/10.1109/PESGM.2016.7741442

A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system. / Wang, Shu; Xu, Yan; Dong, Zhao Yang et al.
2016 IEEE Power and Energy Society General Meeting, PESGM 2016. Vol. 2016-November IEEE Computer Society, 2016. 7741442 (IEEE Power and Energy Society General Meeting; Vol. 2016-November).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system

AU - Wang, Shu

AU - Xu, Yan

AU - Dong, Zhao Yang

AU - Zhao, Junhua

AU - Yao, Weifeng

AU - Luo, Fengji

AU - Wang, Yijia

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

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N2 - The increasingly prevalence of electric vehicles (EVs) calls for the effective planning of the charging infrastructure. In this paper, a multi-objective, multi-stage collaborative planning model is proposed for the EV charging stations and power distribution network. The model aims to minimize the investment & operation costs of the distribution system while maximizing the annually captured traffic flow. The uncertainties of the charging loads are considered. The MOEA/D algorithm is employed to find the Pareto frontier of the model. The simulation results prove the effectiveness of the model. © 2016 IEEE.

AB - The increasingly prevalence of electric vehicles (EVs) calls for the effective planning of the charging infrastructure. In this paper, a multi-objective, multi-stage collaborative planning model is proposed for the EV charging stations and power distribution network. The model aims to minimize the investment & operation costs of the distribution system while maximizing the annually captured traffic flow. The uncertainties of the charging loads are considered. The MOEA/D algorithm is employed to find the Pareto frontier of the model. The simulation results prove the effectiveness of the model. © 2016 IEEE.

KW - Charging station

KW - Distribution system planning

KW - Electric vehicle

KW - Multi-objective optimization

KW - Smart grid

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DO - 10.1109/PESGM.2016.7741442

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781509041688

VL - 2016-November

T3 - IEEE Power and Energy Society General Meeting

BT - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016

PB - IEEE Computer Society

T2 - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016

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ER -

Wang S, Xu Y, Dong ZY, Zhao J, Yao W, Luo F et al. A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system. In 2016 IEEE Power and Energy Society General Meeting, PESGM 2016. Vol. 2016-November. IEEE Computer Society. 2016. 7741442. (IEEE Power and Energy Society General Meeting). doi: 10.1109/PESGM.2016.7741442

A stochastic collaborative planning approach for electric vehicle charging stations and power distribution system

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Research Keywords

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