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多微电网互联系统的储能容量配置
引用本文:唐忠,田晨,资容涛.多微电网互联系统的储能容量配置[J].电测与仪表,2019,56(4):95-100.
作者姓名:唐忠  田晨  资容涛
作者单位:上海电力学院,上海,200090;上海电力学院,上海,200090;上海电力学院,上海,200090
基金项目:国家自然科学基金 (61107081)
摘    要:随着微电网的发展,微电网之间互联的研究逐渐兴起。为了满足多微电网系统的电能质量和运行稳定性等要求,储能系统发挥着重要作用。同时,为了实现微电网互联运行的经济性最优,需要对多微电网的储能系统进行协调容量配置。建立了层级式微电网互联模型,以传输功率损耗最低作为互联微电网之间以及微电网与大电网之间的功率交换原则,基于多微电网互联系统功率交换和分时售/购电价,建立以多微电网系统经济性最优为目标的目标函数,采用改进的粒子群算法对该模型进行优化求解,最终获得储能系统的容量配置参数。实验结果表明,在满足系统稳定性的前提下,文中提出储能系统容量配置方法使得多微电网系统的经济性更优。

关 键 词:多微电网  储能系统  容量配置  粒子群算法
收稿时间:2017/12/18 0:00:00
修稿时间:2017/12/18 0:00:00

Storage Capacity Configuration Of Interconnected Microgrids
tangzhong,tianchen and zirongtao.Storage Capacity Configuration Of Interconnected Microgrids[J].Electrical Measurement & Instrumentation,2019,56(4):95-100.
Authors:tangzhong  tianchen and zirongtao
Affiliation:Shanghai University of Electric Power,Shanghai University of Electric Power,Shanghai University of Electric Power
Abstract:With the development of microgrid, the study of inter-connection of microgrids is getting more attention. In order to ensure the power quality and operational stability of interconnected microgrids, energy storage systems play an important role. At the same time, in order to achieve the optimal operation of the interconnected microgrids, the sizes of energy storage units should be coordinated. In his paper, the model of interconnected microgrids is built via MATLAB. In addition, considering power flow between inter-microgrids, as well as between traditional power grid and micro-grid, based on lowest transmission power loss and time-sharing purchase/sale price ,the objective equation and its constrains are established, and the improved particle swarm optimization is used to solve this problem to get the configuration parameters of energy storage system. The results indicate that the method could get better economic performance under the premise of satisfying the system stability requirement.
Keywords:Inter-connected microgrid  Hybrid energy storage system  Capacity configuration  Particle swarm optimization
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