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文章摘要
模拟植物多向生长的配电网重构算法
Plant multi-direction growth simulation algorithm for distribution network reconfiguration
Received:July 20, 2015  Revised:November 20, 2015
DOI:
中文关键词: 配电网重构  植物生长模拟算法  多向生长  随机搜索
英文关键词: distribution network reconfiguration, plant growth simulation algorithm, multi-direction growth, random search
基金项目:《基于植物向光性生长机制的电力系统方法》(50747025);《基于化学反应算法的配电系统优化规划和运行》(51167012)
Author NameAffiliationE-mail
Kong Lingfei* Nanchang University toffykong@163.com 
Wang Chun Nanchang University cwang_ncu_cn@163.com 
Xiong Yun Nanchang University 629100683@qq.com 
Huang Hui Nanchang University jjdchuanghui@163.com 
Wang Ning Nanchang University 541258669@qq.com 
Yan Zhaoyun Jiangxi Provincial Electric Design Institute yzy6198@126.com 
Li Yuanhao Nanchang University 546712995@qq.com 
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中文摘要:
      应用植物多向生长模拟算法求解配电网络静态重构问题。在植物生长过程中,其总体形态处处蕴涵着分形的性质。从优化数学角度来看,生长点对应优化问题的控制变量;树干和树枝构成控制变量解空间;光照条件最好点对应目标函数最优解;树根对应控制变量初始值。因而植物向光性生长机制可用于求解配电网络重构的整数规划问题。植物多向生长模拟算法在基本的植物生长模拟算法基础上对植物形态素浓度的求解进行了改进,且增加了新枝的随机生长方向;同时从丰富随机生长方向的角度进一步改进了植物多向生长模拟算法。在算法计算过程中以基本环路作为控制变量,采用3个经典测试系统IEEE16、IEEE33、PG&E69和3个大型实际网络Taipower84、Bus119、Bus136作为算例进行重构计算,结果表明植物多向生长模拟算法具有良好的全局寻优能力,且可行解的多样性使算法收敛速度加快。
英文摘要:
      Plant multi-direction growth simulation algorithm (PMGSA) was applied to solve distribution network static reconfiguration problem. In the process of plant growth, its overall form contains fractal nature. From optimization mathematical perspective, growing point corresponding control variables, tree trunks and branches constitute solution space, light conditions with the best point corresponding optimal solution, roots corresponding initial value. So PMGSA can be used to solve the integer programming problem of distribution network reconfiguration. PMGSA, which is based on basic plant growth simulation algorithm, improves the calculation of the phytohormone and increases the random growth direction of new branch. At the same time, PMGSA was improved by enriching the random growth direction. Basic loop was selected as control variable. The reconfiguration results of three typical testing systems including IEEE16, IEEE33, PG&E69, and three large real networks including Taipower84, Bus119 and Bus136 show that plant multi-direction growth simulation algorithm has good global optimization capability and the diversity of feasible solutions enables convergence speed faster.
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