基于可行解搜索和自适应免疫算法的配网重构

为提高配网重构的计算速度及效率，将自适应免疫算法（adaptive immune algorithm，AIA）用于配网重构；在此基础上结合GENOCOPⅢ（genetica algorithm for numerical optimization of constrained problems）算法对AIA进行改进，提出了对不可行解进行修复的AINOCOP（adaptive immune algorithm for numerical optimization of constrained problem）算法用于配网重构，该方法综合了AIA的双层优化特点以及GENOCOPⅢ的可行解搜索方法；在基因的编码技术上，基于启发式规则，采用方便的十进制编码策略．将多种方法用于69节点系统的配网重构计算，GA、IA、AIA和AINOCOP的平均迭代次数分别为300、30、25次和12次，连续运算50次，AIA和AINOCOP在50代内可得到最优解的次数分别为8次和15次．

Distribution Network Reconfiguration Based on Feasible Solution Search and Adaptive Immune Algorithm

Aiming at increasing the calculation efficiency and speed of distribution network reconfiguration, adaptive immune algorithm （AIA）is applied to distribution network reconfiguration;based on that, a new method named AINOCOP, which combines AIA with the co-evolutionary method of GENOCOP Ⅲ （genetic algorithm for numerical optimization of constrained problems） is further presented to repair the infeasible solution for the distribution network reconfiguration. The AINOCOP integrates the bi-level optimization of AIA with the feasible solution search of GENOCOP Ⅲ. On the aspect of the gene coding technology, based on the heuristic rule, a simple decimalization coding method is adopted. The test results of the 69 nodes system show that the average iteration times of GA, IA, AIA and AINOCOP are 300, 30, 25 and 12, respectively. During the 50 times calculation, the times to gain the optimal solution by AIA and AINOCOP are 8 and 15, respectively. All the results demonstrate the feasibility and effectiveness of the proposed method.