Support vector machine based transient stability identification in distribution system with distributed generation

Due to the increased penetration of distributed generations in distribution systems, transient stability is one of the major concerns to be analyzed. This article presents a support vector machine based approach for transient stability detection using post-disturbance signals extracted from the optimally located distributed generations in a distribution system having distributed generation. Initially, distributed generations are placed optimally, and their optimal sizes are found with objectives of loss reduction and reliability improvement for various distributed generation penetration levels, system configurations, and system loading conditions. Various asymmetrical and symmetrical faults at different locations in the system are simulated to calculate the critical clearing times. The post-disturbance values of terminal voltage, active power, reactive power, and speed obtained from the distributed generations for both stable and unstable cases are used as input features of the support vector machine for finding the transient stability status. The dynamic simulations are carried out on IEEE 33-node and IEEE 69-node radial distribution test systems with four distributed generations, modeled in DIgSILENT power factory software (DIgSILENT GmbH, Germany). The proposed support vector machine based approach predicts the post-disturbance transient stability of the distribution system accurately.