Application of Improved Quantum Genetic Algorithm in Fault Location of Distribution Network

This paper introduces an improved quantum genetic algorithm for fixing the slow convergence happened while genetic algorithms dealing with the complex grid. Improvements comprise improving gradient descent method to dynamically adjust the rotation angle mechanism and quantum catastrophe. Meanwhile, this article builds a new mathematical model which utilizes linear algebraic operations to replace the original logic operations with a new modeling method for the reason that bidirectional flow caused by power distribution added DGs can lead the traditional fault location method to failure. Using 33-node system with DGs as the simulation model, compared with Genetic Algorithm (GA) and Quantum Genetic Algorithm (QGA), the Improved Quantum-inspired Genetic Algorithm (IQGA) algorithm cannot only locate the faulty feeder accurately, but also has a faster convergence rate and a stronger fault tolerance than the other two algorithms.