A Study on the Application of a Genetic Algorithm for the Fault Recovery of Substations

Conventional substations have been developed into multi-functional automated digital substations while adopting the IEC61850 international protocol standard. However, the fault recovery technology of substations has not applied because it is difficult and requires reliability. The reliability of the power grid, fault recovery times, and recovery costs could be reduced through restoration systems based on a standard operation procedures and the use of improved technology in the substation. A genetic algorithm (GA) is an optimization tools that can be used for the fault recovery of substations in power grids. To enhance the fault recovery of a 154/22.9 kV substation in South Korea, this paper studies the application of a GA. In particular, the GA is applied to the fault recovery method considering the main transformer capacity and switch paths. First, preprocessing is performed using the switching operation state of the components of the substation. After deriving an appropriate fitness function, a fault recovery technique is designed using a GA. Then, through several simulations considering the survival rate, the mutation probability, and the fault position, the application of a GA is evaluated for the fault recovery of the substation. The evaluation results show a fast speed and accurate fault recovery.