Joint optimization of electric bus charging and energy storage system scheduling

被引:4
|
作者
Zhong, Lingshu [1 ]
Zeng, Ziling [2 ]
Huang, Zikang [3 ]
Shi, Xiaowei [4 ]
Bie, Yiming [5 ]
机构
[1] Sun Yat Sen Univ, Sch Syst Sci & Engn, Guangzhou 510399, Peoples R China
[2] Chalmers Univ Technol, Dept Architecture & Civil Engn, SE-41296 Gothenburg, Sweden
[3] South China Univ Technol, Sch Civil Engn & Transportat, Guangzhou 510641, Peoples R China
[4] Univ Wisconsin Milwaukee, Dept Civil & Environm Engn, Milwaukee, WI 53211 USA
[5] Jilin Univ, Sch Transportat, Changchun 130012, Peoples R China
基金
中国国家自然科学基金;
关键词
electric vehicle; energy storage; mixed integer nonlinear programming; Monte Carlo simulations; public transit; BATTERY DEGRADATION;
D O I
10.1007/s42524-024-3102-2
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The widespread use of energy storage systems in electric bus transit centers presents new opportunities and challenges for bus charging and transit center energy management. A unified optimization model is proposed to jointly optimize the bus charging plan and energy storage system power profile. The model optimizes overall costs by considering battery aging, time-of-use tariffs, and capacity service charges. The model is linearized by a series of relaxations of the nonlinear constraints. This means that we can obtain the exact solution of the model quickly with a commercial solver that is fully adapted to the time scale of day-ahead scheduling. The numerical simulations demonstrate that the proposed method can optimize the bus charging time, charging power, and power profile of energy storage systems in seconds. Monte Carlo simulations reveal that the proposed method significantly reduces the cost and has sufficient robustness to uncertain fluctuations in photovoltaics and office loads.
引用
收藏
页码:676 / 696
页数:21
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