Electric bus charging scheduling problem considering charging infrastructure integrated with solar photovoltaic and energy storage systems

被引:0
|
作者
Liu, Xiaohan [1 ,2 ]
Yeh, Sonia [3 ]
Ploetz, Patrick [4 ]
Ma, Wenxi [1 ]
Li, Feng [1 ]
Ma, Xiaolei [1 ,5 ]
机构
[1] Beihang Univ, Sch Transportat Sci & Engn, Beijing 100191, Peoples R China
[2] Chalmers Univ Technol, Dept Architecture & Civil Engn, S-41296 Gothenburg, Sweden
[3] Chalmers Univ Technol, Dept Space Earth & Environm, S-41296 Gothenburg, Sweden
[4] Fraunhofer Inst Syst & Innovat Res ISI, Breslauer Str 48, D-76139 Karlsruhe, Germany
[5] Minist Educ, Key Lab Intelligent Transportat Technol & Syst, Beijing 100191, Peoples R China
关键词
Bus charging scheduling; Solar photovoltaic energy; Peak net charging power; Mixed integer linear program; Carbon emissions; RANGE;
D O I
10.1016/j.tre.2024.103572
中图分类号
F [经济];
学科分类号
02 ;
摘要
Bus fleet electrification is crucial in reducing urban mobility carbon emissions, but it increases charging demand on the power grid. This study focuses on a novel battery electric bus (BEB) charging scheduling problem involving solar photovoltaic (PV) and battery energy storage facilities. A mixed integer linear programming model is formulated to schedule BEB charging and control solar PV energy simultaneously. The model handles a range of realistic considerations, including heterogeneous BEBs regarding battery capacities, peak net charging power costs, flexible charging powers, and multi-route-multi-depot scheduling. A key point of our model is the introduction of variable charging power decisions designed to align BEB charging demands with solar PV production. The optimization objective is to minimize the sum of charging costs, carbon emission costs, energy storage costs, and revenue (negative cost) from solar PV energy sales. The model empowers public transport agencies to swiftly generate daily BEB charging schedules given daily solar and weather variations. A case study is performed in Beijing, China, utilizing actual bus trajectory data, weather conditions, solar irradiance, and detailed built environment data of bus depots. The results show that the proposed model can significantly reduce the operating cost and shift the charging loads by improving solar PV energy utilization.
引用
收藏
页数:17
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