用于配电网规划的多种群免疫遗传算法

Multi-population Based Immune Genetic Algorithm for Distribution System Planning

引入免疫算子和多种群概念,提出了一种用于配电网规划的多种群免疫遗传方法。采用多个种群针对目标函数的不同方面进行优化搜索,并借鉴生物免疫机制对每个种群的染色体进行免疫算子操作。种群之间通过优秀个体转移进行交互,可有效地防止种群退化,提高种群的多样性。以年费用最小为目标建立配电网规划的数学模型,提取“单个子路造价最小”和“电阻值最小”两种疫苗,并用其指导多种群搜索,有效地克服了遗传算法早熟收敛现象。同时给出初始可行方案的生成步骤和基于支路交换思想的不可行解处理方法。求解一个10 kV配电网规划问题,计算结果表明该算法能快速获得规划问题的最优解。同简单遗传算法相比,整个算法具有更强的收敛速度和全局搜索能力,用于配电网规划是可行有效的。

Based on the conception of immune operator and multi-population, this paper proposes a multi-population based immune genetic algorithm for distribution system planning. Multi-population is applied to do optimal search from different aspects of objective function, and immune operator operations are carried out on the chromosomes of each population when introducing immune mechanism into optimal search. Each population interacts mutually by the shift of excellent individual. Therefore, it can effectively prevent population retrogression and promote diversity. In order to minimize network annual expenditure, a mathematic model is established. To apply the method, two kinds of bacterin, namely, ＂minimal single branch cost＂ and ＂minimal resistance＂ are extracted according to the analysis of established model. When they are used for guiding the multi-population search, it is effective to overcome premature of genetic algorithm. Moreover, process of generating initial feasible plans is given, and branch-exchange based method for dealing unfeasible plans is presented. An 10 kV distribution system planning is tested by the proposed algorithm. Results indicate ahtat it can obtain the optimal plans quickly. The whole algorithm has faster convergence speed and stronger overall search ability than the simple genetic algorithm, and is feasible and effective in the application of distribution system planning.