Battery-powered electric buses are gaining popularity as an energy-efficient and emission-free alternative for bus fleets. However, battery electric buses continue to struggle with concerns related to their limited driving range and time-consuming recharging processes. Fast-charging technology, which utilizes dwelling time at bus stops or terminals to recharge buses in operation employing high power, can raise battery electric buses to the same level of capability as their diesel counterparts in terms of driving range and operating time. To develop an economical and effective battery electric bus system using fast-charging technology, fast-charging stations must be strategically deployed. Moreover, due to the instability of traffic conditions and travel demands, the energy consumption uncertainty of buses should also be considered. This study addresses the planning problem of fast-charging stations that is inherent in a battery electric bus system in light of the energy consumption uncertainty of buses. A robust optimization model that represents a mixed integer linear program is developed with the objective of minimizing the total implementation cost. The model is then demonstrated using a real-world bus system. The performances of deterministic solutions and robust solutions are compared under a worst-case scenario. The results demonstrate that the proposed robust model can provide an optimal plan for a fast-charging battery electric bus system that is robust against the energy consumption uncertainty of buses. The trade-off between system cost and system robustness is also addressed.
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Beijing Inst Technol, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
Beijing Huashang Sanyou New Energy Technol Co Ltd, Beijing 271000, Peoples R ChinaBeijing Inst Technol, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
Ding, Xiaowei
Zhang, Weige
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Beijing Jiaotong Univ, Sch Elect Engn, Beijing 100044, Peoples R ChinaBeijing Inst Technol, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
Zhang, Weige
Wei, Shaoyuan
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机构:
Sunwoda Elect Co Ltd, Shenzhen 518108, Peoples R China
South China Univ Technol, Sch Elect Power, Guangzhou 510641, Peoples R ChinaBeijing Inst Technol, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
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Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R ChinaTsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
Duan, Xiaoyu
Chen, Huimiao
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Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R ChinaTsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
Chen, Huimiao
Song, Yiwen
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Beijing Univ Posts & Telecommun, Sch Comp Sci & Technol, Beijing, Peoples R ChinaTsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
Song, Yiwen
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Hu, Zechun
Song, Yonghua
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Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
Univ Macau, State Key Lab Internet Things Smart City, Taipa, Macau Sar, Peoples R ChinaTsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
机构:
Transportation Engineering College, Dalian Maritime University, Dalian,116026, China
School of Transportation and Logistics, Dalian University of Technology, Dalian,116024, China
Department of Business and Administration, ILMA University, Karachi, PakistanTransportation Engineering College, Dalian Maritime University, Dalian,116026, China
Ullah, Irfan
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Liu, Kai
Layeb, Safa Bhar
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LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunis, TunisiaTransportation Engineering College, Dalian Maritime University, Dalian,116026, China
Layeb, Safa Bhar
Severino, Alessandro
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Department of Civil Engineering and Architecture, University of Catania, Catania,95123, ItalyTransportation Engineering College, Dalian Maritime University, Dalian,116026, China