Optimal Planning of Electric Vehicle Charging Stations Location Based on Hybrid Particle Swarm Optimization

Zhe Ci Tang; Chun Lin Guo; Peng Xin Hou; Yu Bo Fan; Dong Ming Jia

doi:10.4028/www.scientific.net/AMR.724-725.1355

Paper Titles

Effect of Excess Air Ratio on Idle Performance of a HCNG (H₂+CNG) Engine with Different Hydrogen Blend Ratios
p.1336

Effect of Ignition Timing and Excess Air Ratio on Combustion Characteristic of Linear Engine
p.1340

Impact of Peak and Valley Period Partition on Load Curve of Distribution System with EV
p.1344

Influence of Piston Initial State on HCCI Combustion in Micro Free-Piston Engine Using Experiment Images and CFD Analysis
p.1350

Optimal Planning of Electric Vehicle Charging Stations Location Based on Hybrid Particle Swarm Optimization
p.1355

Power Generation System by Vehicle on the Downhill of Expressway
p.1361

Safety Research and Lightweight Design of Electric Vehicle Battery Protection Device
p.1366

Study on Zn-PANi Battery Characteristics Used for Electric Vehicles
p.1374

The Economic Benefit of Electric Taxi Based on Total Ownership Cost Model
p.1379

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 724-725Optimal Planning of Electric Vehicle Charging...

Optimal Planning of Electric Vehicle Charging Stations Location Based on Hybrid Particle Swarm Optimization

Abstract:

In order to determine the layout of electric car charging stations, a model for optimizing charging stations location is developed after charging-demand districts are divided, the number of electric vehicles and the center of each charging district are ready. This model takes the minimization of electric vehicles charging stations total cost which includes initial fixed investment costs, operating costs and charging costs as the objective function, some related constraints which include service radius, capacity of charging station etc. are considered. Particle swarm optimization based on hybridization is proposed to solve this problem. The example verifies feasibility of this method.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 724-725)

Pages:

1355-1360

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.724-725.1355

Citation:

Cite this paper

Online since:

August 2013

Authors:

Zhe Ci Tang, Chun Lin Guo, Peng Xin Hou, Yu Bo Fan, Dong Ming Jia

Keywords:

Charging Stations Location, Electric Vehicle (EV), Hybrid Particle Swarm Optimization, Optimal Planning

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Qitang Wu, Progresses in "Ten Cities & Thousand Units" Plan, in: New Energy Vehicles, 2009 (24):15-19．

Google Scholar

[2] United States Energy Information Administration．International energy outlook 2010-highlights, 2010．

Google Scholar

[3] SCOTLAND W W F. The Role of Electric Vehicles in Scotiand's Low Carbon Future, 2010.

Google Scholar

[4] Chunyang Wu, Canbing LI, Li Du, et.a1. Automation of Electric Power Systems, 2010, 34(24): 36-39.

Google Scholar

[5] Fengquan Zhou, Zhanwei Lian, Xiaolei Wang, et.a1. Power System Protection and Control, 2010, 38(21): 63-66.

Google Scholar

[6] Yulong Ren, Lefeng Shi, Qian Zhang, et.a1. Automation of Electric Power Systems, 2011, 35(14): 53-57.

Google Scholar

[7] Ruqi Li, Haoyi Su, Automation of Electric Power Systems, 2011, 35(14): 58-61.

Google Scholar

[8] Carpinelli G, Cwlli G, Pilo F, et.a1. in: Distributed Generation Siting and Sizing under Uncertainty, IEEE Porto Power Tech Proceedings, September 10-13, 2001, Porto, Portugal: 1-7.

DOI: 10.1109/ptc.2001.964856

Google Scholar

[9] Ling Li, Yanqing Li, Yuhai Yao, Man Ge, East China Electric Power, Vol. 39, No. 6, Jun. 2011.

Google Scholar

[10] Zhipeng Liu, Fushuan Wen, Yusheng Xue, eta1, Automation of Electric Power Systems, 2012, 36(3): 54-59.

Google Scholar

[11] BERGH F V D, An Analysis of Particle Swarm Optimizer, South Africa: University of Pretoria, 2002.

Google Scholar