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用于优化微网联络线功率的混合储能容量优化方法
引用本文:肖峻,张泽群,张磐,梁海深,王成山.用于优化微网联络线功率的混合储能容量优化方法[J].电力系统自动化,2014,38(12):19-26.
作者姓名:肖峻  张泽群  张磐  梁海深  王成山
作者单位:智能电网教育部重点实验室, 天津大学, 天津市 300072
基金项目:国家高技术研究发展专项经费资助(863计划) (2011AA05A117)
摘    要:为微网配置蓄电池/超级电容器混合储能,可更好地调节微网与配电网间联络线的功率。文中提出了一种用于优化微网联络线功率的混合储能容量优化方法。首先,建立了混合储能系统的容量优化模型,以考虑储能寿命和更换的全寿命周期净现值为目标函数,以不同类型储能各自补偿频段的分界频率作为优化变量,在约束条件中详细计及了非理想储能系统的充放电效率以及实际工作中的荷电状态限制。其次,给出了采用遗传算法求解模型的步骤,在遗传算法中调用以下过程:先由分界频率计算滤波时间常数,从而实现混合储能功率分配;之后计算储能容量,再进行经济评价。最后,采用天津生态城某微网的实例进行验证,并与实际安装储能以及目前主流文献方法对比。对比结果表明,所提出的方法在达到同等补偿效果的前提下具有更好的经济性。

关 键 词:混合储能  容量优化  分界频率  遗传算法  微网(微电网)
收稿时间:2013/7/15 0:00:00
修稿时间:2014/5/23 0:00:00

A Capacity Optimization Method of Hybrid Energy Storage System for Optimizing Tie-line Power in Microgrids
XIAO Jun,ZHANG Zequn,ZHANG Pan,LIANG Haishen and WANG Chengshan.A Capacity Optimization Method of Hybrid Energy Storage System for Optimizing Tie-line Power in Microgrids[J].Automation of Electric Power Systems,2014,38(12):19-26.
Authors:XIAO Jun  ZHANG Zequn  ZHANG Pan  LIANG Haishen and WANG Chengshan
Affiliation:Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Abstract:The introduction of battery-super capacitor hybrid energy storage into the microgrid can better regulate the tie-line power between the microgrid and the distribution network. This paper proposes a capacity optimization method of hybrid energy storage system for optimizing the microgrid tie-line power. Firstly, the capacity optimization method for hybrid energy storage is modeled. The whole life cycle net present value which takes the energy storage life and replacement into account is chosen as the objective function. The boundary frequency between different compensation frequency bands of hybrid energy storage is the optimization variable. In the constraints, the charging and discharging efficiency of non-ideal energy storage system and the state of charge (SOC) are considered as well. A genetic algorithm based approach to solve the model is then given. The key steps involved in the genetic algorithm are: calculation of the time constant of filter through boundary frequency to achieve power allocation of hybrid energy storage, capacity calculation and economic evaluation. Finally, a case of a microgrid system in Tianjin Eco-friendly City is used for verification, and the comparisons with the energy storage actually installed and the method of mainstream papers are made. The results show that the proposed method delivers better economy while achieving the same compensation effect.
Keywords:hybrid energy storage  capacity optimization  boundary frequency  genetic algorithm  microgrid
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