摘要
针对电网故障模型中原有故障目标函数存在多解的问题,综合考虑了重合闸、不同保护以及主后备保护之间的相互关系对目标函数的影响,建立了新的目标函数。同时,针对遗传算法所需种群多,收敛速度慢等缺点,提出了一种基于量子免疫算法的故障诊断方法。该算法采用量子比特编码染色体,利用克隆算子和量子门来引导变异,使得当前最优个体的信息能够很容易扩大到下一代,具有种群规模小,收敛速度快,全局寻优能力强的特点。实验表明,改进的模型是合理的,量子免疫算法综合性能优于传统的遗传算法,说明该算法是可行的。
Aimed at problems of multiple solutions in the used optimizing models for grid fault diagnosis,an improved model is established considering the influence of the reclosure,the different protection and joint influence between main and backup protections.Also,quantum immune algorithm is presented for fault model in order to overcome many populations and slow convergence of genetic algorithm.Quantum immune algorithm codes the chromosome by quantum bit probability,and makes the populations evolve by clonal selection and quantum rotation gate,which makes current best individual information can be easily extended to the next generation,so rapid convergence,small populations and good global search capability are the characteristics of the quantum immune algorithm.Test results show that,the improved model is logical and quantum immune algorithm has better comprehensive performance than genetic algorithm,which proves that the algorithm is feasible.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2010年第10期22-25,30,共5页
Power System Protection and Control
关键词
电网
故障诊断
改进模型
量子免疫算法
克隆选择
量子门
power systems
fault diagnosis
improved model
quantum immune algorithm
clonal selection
quantum rotation gate
