基于改进免疫遗传算法的配电网网架规划

为了解决传统方法难以实现配电网网架规划组合优化的问题,针对改进免疫遗传算法具有生物免疫系统中抗体多样性的保持机制和基于抗体浓度的调节更新机制,同时又具有一般进化算法的随机搜索能力,采用改进免疫遗传算法对配电网网架规划进行求解,提高了种群的多样性和遗传算法的全局寻优能力.优化模型以网络年费用最小为优化目标,以线路传输容量、电压降、配电网的辐射性等为约束条件;根据配电网辐射性的要求,以备选网络的生成树作为初始解,从而避免了随机产生初始可行解时速度较慢的弊端.并借鉴支路交换的思想设计杂交算子和变异算子,以避免辐射性检查过程,使得算法的寻优能力大为增强.通过算例验证了该算法的有效性,同时算例结果表明该算法的计算速度比常规免疫遗传算法的计算速度有较大提高.

Distribution Network Structure Planning Based on Improved Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem,which is difficult to solve properly by using traditional optimization methods.In order to solve this problem,Improved Immune Genetic Algorithm is introduced to the distribution network optimal planning. Improved Immune Genetic Algorithm draws into the immune diversity and antibody's density mechanism to maintain the individual's diversity and remains evolution algorithm's global stochastic searching ability,so it can promote diversity and the whole optimal-searching ability of genetic algorithm.The optimal module takes the minimum annual cost as its object,and the capacity and voltage drop of feeder and the radiation of distribution network as its restrictions.According to the require of radiation of distribution network,the spanning tree of the alternative network is taken as the initial solution to speed up the calculation.And the branch-exchange method is used in designing crossover operator and mutation operator to avoid the radiation checking and enhance the optimizing ability.This algorithm has been illustrated effectively by examples,at the same time,the calculation example demonstrates that,the algorithm has higher calculation speed than the traditional immune genetic algorithm.