Application of quantum immune algorithm for fault-section estimation

Aiming at problems of multiple solutions in the existing optimizing models for power fault-section estimation, the improved model was established considering the influence of the reclosure, the different protection and joint influence between main and backup protections. Besides, quantum immune algorithm was 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, so rapid convergence, small populations and good global search capability characterize the performance of 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.