Short circuit current forecast of large scale power grid based on improving BP Artificial Neural Network combined with Genetic Algorithm

Abstract

The increasing electrical load penetration on power systems requires the development of researching on short-circuit current level for large scale power grid, and the problem of short circuit currents has become significant for the planning and operation of the power system.This paper analyses short-circuit current situation as well as the development tendency in China in detail, and proposes a new algorithm to forecast three-phase short circuit current on the basis of genetic algorithm and improved BP artificial neural network algorithm. Taking a wide range electrical network as an example, three-phase short- circuit current computation based on load flow is carried out. Two algorithms are employed to carry out short-circuit current level forecast so that weak points of short circuit current level could be found. This method can be used in basically unchanged circumstances of the grid structure to calculate short-circuit current level. The feasibility and validity of the proposed method is shown by the simulation and computation.