A novel hybrid GWO-PSO optimization technique for optimal reactive power dispatch problem solution

This paper provides an application of the hybrid Grey Wolf Optimization and Particle Swarm Optimization (GWO-PSO) method to reach a solution to the optimal reactive power dispatch (ORPD) problem in the scope of electric power networks. PSO is a swarm based meta-heuristic optimization algorithm whose target is to seek the best solution to a problem by moving particles in a specific exploration field. On the other hand, GWO is a meta-heuristic optimization technique which is inspired by grey wolves. In this article, GWO is hybridized with a PSO method to improve the progress of the GWO. There are two objectives minimized in this research study to improve the electric power network performance. They are: 1) power losses in the transmission systems, and 2) the deviation of voltages at the load buses. The problem of ORPD has many restrictions on the networks which must be considered during the solution. The hybrid GWO-PSO is proven as an effective optimization technique when seeking the global best solution to an optimization problem. The success of the introduced hybrid technique is verified utilizing more than one standard IEEE test system. A valuation to the introduced technique is performed by comparing it with other optimization techniques stated through the literature. The simulation results confirm that the usage of the hybrid GWO-PSO techniques causes an observable improvement in a wide scale of the electric power networks behavior.