Pareto Solution Set of Tram Hybrid Energy Storage System Capacity Allocation Based on Improved Convex Optimization

被引：0
|
作者：
An X. [1 ]
Yang Z. [1 ]
Wang Y. [1 ]
Lin F. [1 ]
Zhou H. [1 ]
机构：
[1] School of Electrical Engineering, Beijing Jiaotong University, Beijing
来源：
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2020年 / 35卷 / 14期
关键词：
Capacity configuration; Convex optimization; Hybrid energy storage system; Pareto solution set; Tramcar;
D O I：
10.19595/j.cnki.1000-6753.tces.190712
中图分类号：
学科分类号：
摘要：
Capacity allocation affects the operational feasibility and economic benefits of hybrid electric tram, which is the basic link in the design of hybrid electric system. Energy management strategy (EMS) and capacity allocation are coupled and influenced each other. Based on this characteristic, an improved convex (CVX) optimization algorithm for collaborative optimization of capacity allocation and energy management strategy is proposed. Firstly, the feasible region of capacity allocation is solved, and a family of equal weight lines is constructed in the feasible region. Under each equal weight line, the optimal group point of capacity allocation and EMS with minimum energy consumption is found. The dual-objective Pareto frontier of hybrid power system weight and energy consumption is obtained. Compared with the single energy storage system, the hybrid energy storage system is light in weight and small in volume. It is suitable for the situations with strict requirements on weight and volume. The simulation comparison shows that the EMS of collaborative optimization is efficient and the power distribution is reasonable. © 2020, Electrical Technology Press Co. Ltd. All right reserved.
引用
收藏
页码：3116 / 3125
页数：9
相关论文
共 26 条
  • [1] Ratniyomchai T, Tricoli P, Hillmansen S., Recent developments and applications of energy storage devices in electrified railways, IET Electrical Systems in Transportation, 4, 1, pp. 9-20, (2014)
  • [2] Mir L, Etxeberria-Otadui I, Arenaza I P D, Et al., A supercapacitor based light rail vehicle: system design and operations modes, IEEE Energy Conversion Congress and Exposition, pp. 1632-1639, (2009)
  • [3] Lhomme W, Delarue P, Barrade P, Et al., Design and control of a supercapacitor storage system for traction applications, IEEE Industry Applications Conference, Fourtieth IAS Annual Meeting, (2005)
  • [4] Fernandez L M, Garcia P, Garcia Carlos Andres, Et al., Hybrid electric system based on fuel cell and battery and integrating a single DC/DC converter for a tramway, Energy Conversion and Management, 52, 5, pp. 2183-2192, (2011)
  • [5] Zhang Chunjiang, Dong Jie, Liu Jun, Et al., A control strategy for battery-ultracapacitor hybrid energy storage system, Transactions of China Electro-technical Society, 29, 4, pp. 334-340, (2014)
  • [6] (2018)
  • [7] Zhu Feiqin, Yang Zhongping, Lin Fei, Et al., Research on acceleration-time-prediction-based energy manage-ment and optimal sizing of onboard energy manage-ment system for modern trams, Transactions of China Electrotechnical Society, 32, 23, pp. 158-166, (2017)
  • [8] Mesbahi T, Khenfri F, Rizoug N, Et al., Combined optimal sizing and control of Li-ion battery/ supercapacitor embedded power supply using hybrid particle swarm-nelder-mead algorithm, IEEE Transactions on Sustainable Energy, 8, 1, pp. 59-73, (2017)
  • [9] Shen Junyi, Dusmez S, Khaligh A., Optimization of sizing and battery cycle life in battery/ultracapacitor hybrid energy storage systems for electric vehicle applications, IEEE Transactions on Industrial Informatics, 10, 4, pp. 2112-2121, (2014)
  • [10] Herrera V I, Gaztanaga H, Milo A, Et al., Optimal energy management of a battery-supercapacitor based light rail vehicle using genetic algorithms, IEEE Energy Conversion Congress and Exposition, pp. 1359-1366, (2015)
123