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考虑削峰填谷的电气化铁路混合储能系统容量优化配置
引用本文:张育维,胡海涛,耿安琪,陈俊宇,葛银波,王科.考虑削峰填谷的电气化铁路混合储能系统容量优化配置[J].电力自动化设备,2023,43(2):44-50.
作者姓名:张育维  胡海涛  耿安琪  陈俊宇  葛银波  王科
作者单位:西南交通大学 电气工程学院,四川 成都 611756
基金项目:国家自然科学基金面上项目(52077179);国家自然科学基金青年项目(52107126);中央高校基本科研业务费专项资金资助项目(2682021ZTPY065)
摘    要:随着我国电气化铁路的快速发展,能耗问题日益突出,极大影响了铁路的运营效益。为提升铁路的经济效益,通过混合储能系统实现再生制动能量的回收利用,在此基础上,提出了一种考虑削峰填谷的电气化铁路混合储能系统能量管理策略,通过控制储能的充放电阈值实现对铁路负荷的削峰填谷。基于此能量管理策略建立电气化铁路混合储能系统全寿命周期的经济性优化模型,以储能充放电阈值与容量配置参数为优化变量,以全寿命周期的最大净收益为优化目标,对混合储能系统经济性进行优化。采用改进的粒子群优化算法求解具体算例。通过算例分析与方案对比,验证了所提方法的有效性。

关 键 词:电气化铁路  削峰填谷  混合储能系统  容量配置

Capacity optimization configuration of hybrid energy storage system for electrified railway considering peak load shifting
ZHANG Yuwei,HU Haitao,GENG Anqi,CHEN Junyu,GE Yinbo,WANG Ke.Capacity optimization configuration of hybrid energy storage system for electrified railway considering peak load shifting[J].Electric Power Automation Equipment,2023,43(2):44-50.
Authors:ZHANG Yuwei  HU Haitao  GENG Anqi  CHEN Junyu  GE Yinbo  WANG Ke
Affiliation:College of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China
Abstract:The rapid development of Chinese electrified railway leads to the critical energy consumption issue, which greatly affects the railway operational benefits. To improve the economic benefits, the recovery and utilization of regenerative braking energy are realized through the hybrid energy storage system. On this basis, an energy management strategy for the electrified railway hybrid energy storage system considering peak load shifting is proposed, which achieves the peak load shifting for railway load by controlling the charging and discharging threshold of energy storage devices. Based on the proposed energy management strategy, an economic optimization model for the full life cycle of the electrified railway hybrid energy storage system is established. This model takes the charging and discharging thresholds and the capacity configuration parameters as the optimization variables, and the maximum net income throughout the full life cycle as the optimization objective, so as to optimize the economy of hybrid energy storage system. The improved particle swarm optimization algorithm is used to solve a specific case. The effectiveness of the proposed method is verified by the case study and the comparison analysis with other schemes.
Keywords:electrified railway  peak load shifting  hybrid energy storage system  capacity configuration
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