Hybrid Time Varying Particle Swarm Optimization and Genetic Algorithm to Solve Optimal Reactive Power Dispatch Problem

Abstract

Optimal reactive power dispatch (ORPD) is the determination of the control variable (discrete continuous combination) which affects the power supply / reactive power absorption. The aim is to reduce real power losses without exceeding the limits of their capabilities in small-scale power systems. Hybrid time varying nonlinear particle swarm optimization and genetic algorithm (HTVNLPSOGA) is applied to solve ORPD problems. The parameters of inertia weight and acceleration factors are made to change nonlinearly so that the speed of particles in the process of exploration and exploitation is more adaptive. Several comparisons with previous studies to see the capabilities of the proposed algorithm. The IEEE 14-bus system has been used to examine and test the methods presented. The simulation results show that the HTVNLPSOGA method when finding the optimal solution is capable of convergence with the number of search iterations below 10 iterations. In addition, this method is able to minimize real power losses of 12.3569 MW. The proposed method is able to reduce power losses better than previous studies on small-scale IEEE 14-bus power systems.