[1]樊一娜,梁伟,黄渝清,等.基于IGA 的配电系统运行损耗与可靠性优化[J].郑州大学学报(工学版),2019,40(05):58-63.[doi:10.13705/j.issn.1671-6833.2019.05.009]
　Fan Yina,Liang Wei,Huang Yuqing,et al.Optimization of operation loss and reliability of power distribution system based on IGA[J].Journal of Zhengzhou University (Engineering Science),2019,40(05):58-63.[doi:10.13705/j.issn.1671-6833.2019.05.009]
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基于IGA 的配电系统运行损耗与可靠性优化()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
40卷
期数:
2019年05期
页码:
58-63
栏目:
出版日期:
2019-10-23

文章信息/Info

Title:
Optimization of operation loss and reliability of power distribution system based on IGA
作者:
樊一娜; 梁伟; 黄渝清; 赵东初; 陈圣博; 李明
北京师范大学珠海分校工程技术学院，广东珠海519087；山东省聊城市水利勘测设计院，山东聊城252061 ；复旦大学信息科学与工程学院，上海200433
Author(s):
Fan Yina 1; Liang Wei 2; Huang Yuqing 1; Jo Dong Chu 1; Chen Shengbo 1; Li Ming 
1. School of Engineering Technology, Beijing Normal University Zhuhai Campus; 2. Liaocheng Water Conservancy Survey and Design Institute, Shandong Province; 3. School of Information Science and Engineering, Fudan University
关键词:
遗传算法; 损失最小化; 网络重构; 可靠性; 电力服务
Keywords:
genetic algorithm ;  loss minimization ;  network reconfiguration ;  reliability ;  service restoration
DOI:
10.13705/j.issn.1671-6833.2019.05.009
文献标志码:
A
摘要:
提出了 一种兼顾径向功率分配系统(RDS)的可靠性和效率的优化方案，目的是在网络重构 (DNR)的过程中使有功功率的损耗降低到最小.本文实质上是基于改进后遗传算法的网络分支故障分 析，即在暂态过程中重点分析保护系统对故障和恢复系统的响应.具体方法是首先采用基于分支可靠性 的非连续蒙特卡罗仿真方法对网络结构的可靠性进行预测，然后利用遗传算法，进行可实现的结构重构 和高效搜索.此外，本文在无投资的情况下分析了 RDS,将这种算法应用在一个69条线路的网络上，实 验结果证明了改进遗传算法的优越性.
Abstract:
This study focused on an optimization method that combined simultaneously the reliability and the efficiency of radial power distribution systems ( RDS) , minimized active energy losses, through a process of network reconfiguration. The study based on the failure analysis on network branches, with a special concern on the protection system response to faults and the service restoration procedures, in the emergency state. A non-sequential Monte Carlo simulation based on the branch reliability was used to evaluate reliability of the network configurations. Due to a large number of possible configurations and the need of an effcient search, the optimization was made through an improved genetic algorithm (IGA) . In a first step, the method analyed the RDS considering the absence of investment, and in a second step, the possibility of placing a limited number of new tie-switches in certain branches, according to the definitions made by a decision maker. The effectiveness of the proposed methodology was demonstrated through the analysis of a 69 bus RDS and by comparison against other reported methodologies.

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更新日期/Last Update: 2019-10-26