Charging Station and Power Network Planning for Integrated Electric Vehicles (EVs)

被引：37

作者：

Liu, Guozhong ^{[1
]}

Kang, Li ^{[1
]}

Luan, Zeyu ^{[2
]}

Qiu, Jing ^{[2
]}

Zheng, Fenglei ^{[3
]}

机构：

[1] Dongguan Univ Technol, Sch Elect Engn & Intelligentizat, Dongguan 523808, Peoples R China

[2] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW 2006, Australia

[3] Dongguan Power Supply Bur, Dongguan 523808, Peoples R China

来源：

ENERGIES | 2019年 / 12卷 / 13期

关键词：

electrical vehicles; charging station planning; traffic flow; power loss; multi-objective optimization; OPTIMIZATION; AGGREGATOR; LOCATION; STRATEGY; MODEL;

D O I：

10.3390/en12132595

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The optimal location and size of charging stations are important considerations in relation to the large-scale application of electric vehicles (EVs). In this context, considering that charging stations are both traffic service facilities and common electric facilities, a multi-objective model is built, with the objectives of maximizing the captured traffic flow in traffic networks and minimizing the power loss in distribution networks. There are two kinds of charging stations that are considered in this paper, and the planning of EV charge stations and distribution networks is jointly modelled. The formulated multi-objective optimization problem is handled by a fuzzy membership function. The genetic algorithm (GA) is used to solve the objective function. In case studies, a 33-node distribution system and a 25-node traffic network are used to verify the effectiveness of the proposed model. The location and capacity of two kinds of charging stations are designed in the case studies, after which the impact of the battery on the captured traffic flow is analyzed as well.

引用

页数：22

共 46 条

[1]

Abul'Wafa AR, 2017, PROC INT MID EAST P, P337, DOI 10.1109/MEPCON.2017.8301203

[2]

[Anonymous], 2011, P IEEE 2011 ENERGY T, DOI DOI 10.1109/ENERGYTECH.2011.5948504

[3]

[Anonymous], 2018, ENERGIES, DOI [DOI 10.3390/EN11051125, DOI 10.3390/en11051125]

[4]

[Anonymous], 2002, Vehicle-to-grid demonstration project: Grid regulation ancillary service with a battery electric vehicle

[5] Plug-in hybrid electric vehicle charge pattern optimization for energy cost and battery longevity [J].

Bashash, Saeid ;

Moura, Scott J. ;

Forman, Joel C. ;

Fathy, Hosam K. .

JOURNAL OF POWER SOURCES, 2011, 196 (01) :541-549

[6]

Ben-Zvi D., 2011, Proceedings of the Seventh International Research Forum on Statistical Reasoning, Thinking, and Literacy (SRTL7), P1

[7] Optimized Bidding of a EV Aggregation Agent in the Electricity Market [J].

Bessa, Ricardo J. ;

Matos, Manuel A. ;

Soares, Filipe Joel ;

Pecas Lopes, Joao A. .

IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (01) :443-452

[8] Analysis of plug-in hybrid electric vehicle utility factors [J].

Bradley, Thomas H. ;

Quinn, Casey W. .

JOURNAL OF POWER SOURCES, 2010, 195 (16) :5399-5408

[9] Management of Electric Vehicle Charging to Mitigate Renewable Generation Intermittency and Distribution Network Congestion [J].

Caramanis, Michael ;

Foster, Justin M. .

PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009), 2009, :4717-4722

[10] Plant-Made Biologics [J].

Chen, Qiang ;

Santi, Luca ;

Zhang, Chenming .

BIOMED RESEARCH INTERNATIONAL, 2014, 2014

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