引用本文:胡 卫,黄 纯,孙彦广,贾天云,陈祝峰,凌理远.基于人工培植杂交的配电网重构方法[J].电力自动化设备,2014,34(9):
HU Wei,HUANG Chun,SUN Yanguang,JIA Tianyun,CHEN Zhufeng,LING Liyuan.Distribution network reconfiguration based on artificial cultivated hybrid[J].Electric Power Automation Equipment,2014,34(9):
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基于人工培植杂交的配电网重构方法
胡 卫1, 黄 纯1, 孙彦广2, 贾天云2, 陈祝峰1, 凌理远1
1.湖南大学 电气与信息工程学院,湖南 长沙 410012;2.冶金自动化研究设计院,北京 100071
摘要:
基于生物学人工培植杂交思想,提出一种配电网经济性重构新算法。从配电网中找出一组基础环并对其分别编码形成一组染色体,使该组染色体先朝各自的优化方向进化,然后以一定概率杂交后,指导修正它们的进化方向,直至搜索到全局最优。该方法通过采用缩短染色体长度和多条染色体并行进化等措施,能够快速搜索到全局最优,并且使得搜索不易陷入局部最优,有效平衡了局部收敛和全局寻优速率的关系。同时还提出了基于支路分类的对不可行解进行修复的方法。IEEE 33节点和IEEE 69节点系统仿真结果验证了所提方法的可行性和有效性。
关键词:  配电  重构  人工培植杂交  遗传算法  不可行解  修复  染色体  优化
DOI:
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基金项目:国家高技术研究发展计划(863计划)资助项目(2012AA050215)
Distribution network reconfiguration based on artificial cultivated hybrid
HU Wei1, HUANG Chun1, SUN Yanguang2, JIA Tianyun2, CHEN Zhufeng1, LING Liyuan1
1.College of Electrical and Information Engineering,Hunan University,Changsha 410012,China;2.Automation Research and Design Institute of Metallurgical Industry,Beijing 100071,China
Abstract:
An algorithm based on biological ACH(Artificial Cultivated Hybrid) is proposed for the economic reconstruction of distribution network. A base loop set of the distribution network is found and coded to form a chromosome set. Each chromosome evolves in its optimal direction first,and the evolution directions are then guided by the chromosome hybridization with a certain probability until the global optimum is searched. Measures are taken,such as shortening chromosome length,performing parallel evolution,etc.,to quickly find the global optimum,avoid the local optimum and efficiently balance the relationship between local convergence and global optimization. A method based on the branch classification is proposed for the complete repair of infeasible solutions. The simulative results of IEEE 33-bus system and IEEE 69-bus system demonstrate the feasibility and effectiveness of the proposed algorithm.
Key words:  electric power distribution  reconfiguration  artificial cultivated hybrid  genetic algorithms  infeasible solution  repair  chromosome  optimization

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