A novel fast-charging stations locational planning model for electric bus transit system

Wu，Xiaomei1; Feng，Qijin1; Bai，Chenchen2; Lai，Chun Sing1,3; Jia，Youwei4; Lai，Loi Lei1

2021-06-01

10.1016/j.energy.2021.120106

ENERGY   影响因子和分区

0360-5442

1873-6785

With more electric buses, the optimal location of charging station plays an important role for bus electrification. This paper proposes a location planning model of electric bus fast-charging stations for the electric bus transit system, that takes the bus operation network and the distribution network into account. The model 1) simulates the operation network of electric buses thoroughly to obtain the charging demand of electric buses and 2) takes into account of the absorption capacity of distribution network and other constraints in the siting and capacity determination stage. The objective of the model is to minimize the sum of the construction cost, operation and maintenance costs, travel cost to charging stations, and the cost of power loss for charging stations at established bus terminus. The Affinity Propagation method is adopted to cluster the bus terminuses in order to obtain a preliminary number of charging stations. Subsequently, the Binary Particle Swarm Optimization algorithm is used to optimize the site selection and capacity. Finally, the model is applied to simulate and analyze the bus operation network of a coastal city in South China. The case study shows that the model can effectively optimize the layout of bus charging stations for the city.

Affinity propagation Binary particle swarm optimization Fast-charging station Location planning

SCI ; EI

英语

其他

China Southern Power Grid: Research on deployment of ebuses charging stations in Yangjiang City considering transportation network[GDKJ031700KK52180001] ; Department of Finance and Education of Guangdong Province[2016 [202]] ; National Natural Science Foundation of China[72071100] ; Education Department of Guangdong Province: New and Integrated Energy System Theory and Technology Research Group[2016KCXTD022]

Thermodynamics ; Energy & Fuels

Thermodynamics ; Energy & Fuels

WOS:000640521200013

PERGAMON-ELSEVIER SCIENCE LTD

20210909998114

Electric automobiles ; Fast charging (Batteries) ; Location ; Particle swarm optimization (PSO) ; Site selection

Automobiles:662.1 ; Heavy Duty Motor Vehicles:663.1 ; Computer Software, Data Handling and Applications:723

ENGINEERING

2-s2.0-85101567281

Scopus

1.Department of Electrical Engineering,School of Automation,Guangdong University of Technology,Guangzhou,510006,China
2.Department of Statistics and Data Science,Southern University of Science and Technology,Shenzhen,518055,China
3.Brunel Institute of Power Systems,Department of Electronic and Electrical Engineering,Brunel University London,London,UB8 3PH,United Kingdom
4.Department of Electrical and Electronic Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Wu，Xiaomei,Feng，Qijin,Bai，Chenchen,et al. A novel fast-charging stations locational planning model for electric bus transit system[J]. ENERGY,2021,224.

Wu，Xiaomei,Feng，Qijin,Bai，Chenchen,Lai，Chun Sing,Jia，Youwei,&Lai，Loi Lei.(2021).A novel fast-charging stations locational planning model for electric bus transit system.ENERGY,224.

Wu，Xiaomei,et al."A novel fast-charging stations locational planning model for electric bus transit system".ENERGY 224(2021).