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储能式有轨电车能量管理策略多目标优化
引用本文:杨继斌,张继业,宋鹏云.储能式有轨电车能量管理策略多目标优化[J].电源学报,2017,15(5):137-143.
作者姓名:杨继斌  张继业  宋鹏云
作者单位:西南交通大学牵引动力国家重点实验室, 成都 610031,西南交通大学牵引动力国家重点实验室, 成都 610031,西南交通大学牵引动力国家重点实验室, 成都 610031;西南民族大学电气信息工程学院, 成都 610041
基金项目:国家自然科学基金资助项目(11572264)
摘    要:研究了以电网、动力电池和超级电容为动力电源的储能式混合动力有轨电车。首先介绍该类有轨电车的混合动力系统结构,提出一种基于系统工作模式的逻辑门限式能量管理策略,通过多个控制参数实现工作模式的切换。针对能量管理策略中控制参数的不确定性,将整车车载电源的最小配置成本以及列车运行的能耗、准时性、准地点停车作为优化目标,应用多目标遗传算法对影响列车动力性能的主要能量管理策略控制参数进行了优化分析。结果表明,优化后列车的牵引运行能耗减少了约6.8%,再生制动能量的回收率提高了约2.4%。同时,通过优化得到了电源的最小配置,为电源的冗余配置提供参考。

关 键 词:储能式有轨电车  能量管理  多目标优化  遗传算法
收稿时间:2017/5/29 0:00:00
修稿时间:2017/9/11 0:00:00

Multi-objective Optimization of Energy Management Strategy for A Tramway with Onboard Energy Storage System
YANG Jibin,ZHANG Jiye and SONG Pengyun.Multi-objective Optimization of Energy Management Strategy for A Tramway with Onboard Energy Storage System[J].Journal of power supply,2017,15(5):137-143.
Authors:YANG Jibin  ZHANG Jiye and SONG Pengyun
Affiliation:State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China,State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China and State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China;College of Electrical & Information Engineering, Southwest Minzu University, Chengdu 610041, China
Abstract:A tramway with an onboard energy storage system is studied with catenary, battery and ultracapacitor as power supply. The structure of tramway hybrid system is introduced, an energy management strategy is proposed based on system operation mode, switching from a number of control parameters. Due to the uncertainty of the control parameters in the energy management strategy, the multi-objective genetic algorithm(GA) is applied to optimize the contr-ol parameters in the control strategy, the minimum cost of energy storage system, the energy consumption of tramway operation, punctuality and tramway precision stop are taken as the optimization goals. Optimization results show that the traction operation energy consumption of the optimized tramway is reduced by about 6.8%, and the recovery rate of regenerative braking energy is increased by about 2.4%. Meanwhile, the minimum configuration of the energy storage system is obtained by optimization, which provides the reference for the redundant configuration of the power system.
Keywords:tramway with energy storage system  energy management strategy  multi-objective optimization  genetic algorithm (GA)
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