Electric bus fleet size and mix problem with optimization of charging infrastructure

被引:253
作者
Rogge, Matthias [1 ,2 ]
van der Hurk, Evelien [3 ]
Larsen, Allan [3 ]
Sauer, Dirk Uwe [1 ,2 ,4 ]
机构
[1] Rhein Westfal TH Aachen, Inst Power Elect & Elect Drives ISEA, Chair Electrochem Energy Convers & Storage Syst, Jaegerstr 17-19, D-52066 Aachen, Germany
[2] JARA Energy, Juelich Aachen Res Alliance, Julich, Germany
[3] Tech Univ Denmark, DTU Management Engn, Lyngby, Denmark
[4] Rhein Westfal TH Aachen, EON Energy Res Ctr, Inst Power Generat & Storage Syst PGS, Aachen, Germany
关键词
Electric bus scheduling; Charger scheduling; Transportation system modeling; Infrastructure planning; TCO optimization; Genetic algorithm; VEHICLE SCHEDULING PROBLEM; ALTERNATIVE FUEL; PUBLIC TRANSPORT; ELECTRIFICATION; ENERGY; EMISSIONS; IMPACTS; OPTIONS; DESIGN; SYSTEM;
D O I
10.1016/j.apenergy.2017.11.051
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
Battery electric buses are seen as a well-suited technology for the electrification of road-based public transport. However, the transition process from conventional diesel to electric buses faces major hurdles caused by range limitations and required charging times of battery buses. This work addresses these constraints and provides a methodology for the cost-optimized planning of depot charging battery bus fleets and their corresponding charging infrastructure. The defined problem covers the scheduling of battery buses, the fleet composition, and the optimization of charging infrastructure in a joint process. Vehicle schedule adjustments are monetized and evaluated together with the investment and operational costs of the bus system. The resulting total cost of ownership enables a comparison of technical alternatives on a system level, which makes this approach especially promising for feasibility studies comprising a wide range of technical concepts. Two scenarios of European cities are analyzed and discussed in a case study, revealing that the cost structure is influenced significantly by the considered bus type and its technical specifications. For example, the total energy consumption of the considered lightweight bus is up to 32% lower than the total consumption of the high range bus, although the deadheading mileage increases. However, the total costs of ownership for operating both bus types are relatively close, due to the increased fleet size and driver expenses required for the lightweight bus system. The case study furthermore reveals that a mixed fleet of different bus types could be advantageous depending on the operational characteristics of the bus route.
引用
收藏
页码:282 / 295
页数:14
相关论文
共 45 条
[1]  
[Anonymous], 2013, MATLAB REL 2013A, P488
[2]  
[Anonymous], 2009, INT BUSINESS MACHINE
[3]  
BYD Europe B.V, 2015, EBUS12 BYD EUR BV
[4]  
California Air Resources Board, 2017, ADV CLEAN T IN PRESS
[5]  
Chen J., 2013, 13 SWISS TRANSP RES
[6]  
Duin J, 2013, EUROPEAN TRANSPORT, V54, P9
[7]  
Eberspacher, 2017, DRIV SEAT AIR COND P
[8]   Optimization of transit bus fleet's life cycle assessment impacts with alternative fuel options [J].
Ercan, Tolga ;
Zhao, Yang ;
Tatari, Omer ;
Pazour, Jennifer A. .
ENERGY, 2015, 93 :323-334
[9]  
Falkenauer E., 1998, Genetic algorithms and grouping problems, chichester
[10]   Routing a mixed fleet of electric and conventional vehicles [J].
Goeke, Dominik ;
Schneider, Michael .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 245 (01) :81-99