摘要
提出了改进的多种群遗传算法并将其应用于配电网规划。根据优化目标数学模型确定统一目标函数和多个子目标函数,并将其作为父、子种群的适应度评价函数,用迁徙算子决定父子种群的联系程度。采用“0”和“1”逐线逐点方式对馈线和变电站进行编码,并构成网架的染色体。用变电站的容载比作为约束条件决定变电站的负荷规模。在此基础上提出了包括孤链、闭环、孤岛的修复方案,将遗传操作所产生的非辐射性网络修复成辐射性网络。该方法可以处理同时涉及变电站和馈线优化的多目标配电网规划问题。算例结果表明了该方法的有效性。
An improved poly-population genetic algorithm (PPGA) is proposed and applied to distribution network planning. According to the mathematical model of the optimal objective the unified objective function and some sub-objective functions are determined and used as the adaptability degree evaluation function for parent and descendant populations. The migration operator is used to determine the correlation between parent and descendant populations. The feeders and substations are encoded by '0' and '1' with line-by-line and point-by-point mode, so the chromosome of the distribution network is constructed. Taking the capacity to load ratio as the constraint condition, the load scale of substation is resolved. On this basis a restoration scheme including the isolated chain, closed loop and isolated nodes, restores the non-radial network generated by genetic operation to radial network. The proposed method can process multi-objective distribution network planning concerning to the optimization of substations and feeders simultaneously. The results from calculation examples show that the proposed method is effective.
出处
《电网技术》
EI
CSCD
北大核心
2005年第7期36-40,55,共6页
Power System Technology
基金
国家自然科学基金资助项目(50277039)。~~
关键词
配电网规划
变电站
馈线
辐射性
算例
目标函数
负荷
优化目标
决定
规模
Correlation methods
Electric power systems
Electric power transmission
Genetic algorithms
Mathematical models
Optimization
