Quantum annealing algorithm for fault section location in distribution networks

As the last link of the power system, the distribution network is responsible for ensuring stable power consumption and improving power quality. Therefore, a more reliable and fast fault section location(FSL) method is essential for the stable operation and optimization of distribution networks. In this context, this paper adopts an effective method to apply the quantum annealing algorithm(QA) based on the quantum tunneling mechanism to the distribution network fault section location problem. A quantum Hamiltonian function consisting of potential and kinetic energy terms is constructed based on the theoretical knowledge of QA. Among them, FSL objective function is mapped to the potential energy term, and the transverse magnetic field is introduced to construct the kinetic energy term, which can realize the quantum tunneling effect and approximate or even reach the global optimal solution. Based on the quantum Hamiltonian function construction, this paper modifies some parameters in the QA framework to propose an improved quantum annealing algorithm(IQA) to improve the accuracy. In the two test systems of IEEE 33-node distribution network and IEEE 33-node distribution network with distributed generation sources(DGs), QA and IQA are compared and analyzed with other intelligent algorithms using the average number of iterations and localization accuracy as indicators. We find that QA is more likely to obtain the global optimal solution compared with the simulated annealing algorithm(SA). IQA can search for faulty sections with 100% accuracy and the least number of average iterations in both single power distribution networks and distribution networks containing DGs. Under the scenarios of fault signal distortion and increasing fault sections, IQA shows superb competitive advantages by exhibiting good fault tolerance performance, global optimal search capability and stability.