A new technique for computation of closest saddle-node bifurcation point of power system using real coded genetic algorithm

Estimation of voltage stability margin is essential for operation of the system with an adequate security margin. In this paper, a new technique to determine the worst case loading margin, i.e., shortest distance to voltage instability is developed. The problem of determining the closest saddle-node bifurcation point (CSNBP) is formulated as an optimization problem and solved using Real Coded Genetic Algorithm (RCGA). The method is capable of handling various operational constraints and can determine the CSNBP accurately even if the transfer limit surface is not smooth. The proposed approach has been applied on a simple radial system, IEEE 14-bus and IEEE 57-bus systems. The developed method has been compared with the method based on Particle Swarm Optimization. Simulation results show the validity and feasibility of the proposed method.

► Real Coded GA method for CSNBP.
► Applied on three different systems.
► Capable of dealing with operational constraints.
► Global minimum distance to voltage collapse.