A novel fault location for transmission line by the combination of Particle Swarm Optimization and least squares method

Considering the aspect of two-terminal asynchronous sampling data and the uncertainty of transmission line parameters, fault location schemes for transmission line face to the problem of solving multi-dimensional nonlinear equations. For the global optimal convergence ability of particle swarm optimization (PSO) algorithm, which has been developed and put into use in many nonlinear optimization solutions, the above problems can be solved effectively. In this paper, the fault location equations including the unknown variables (line parameters, asynchronous sampling angle and fault position), are constructed and transformed into the nonlinear optimization problem. Then, the PSO based solution model for the problem is set up. However, only using PSO, the tests of the fault location find that the particles are inactive during the middle and last searching process and the deep-searching ability is not strong enough. So, after analyzing the characteristic of least squares method (LSM) , this paper proposes a novel fault location scheme, which combines the global optimal convergence ability of PSO and the fast and accurate convergence ability of LSM. The simulation results proved that the proposed scheme has higher precision and stability.