A Novel Hybrid Particle Swarm Optimizer with Multi Verse Optimizer For Global Numerical Optimization and Optimal Reactive Power Dispatch Problem

Abstract

A recent trend of research is to hybridize two and more algorithms to obtain superior solutions in the field of optimization problems. In this context, a new technique hybrid Particle Swarm Optimization (PSO)- Multiverse Optimizer (MVO) is exercised on some unconstraint benchmark test functions and the most a common problem of the modern power system named Optimal Reactive Power Dispatch (ORPD) is optimized using the novel hybrid meta-heuristic optimization algorithm Particle Swarm Optimization-Multi Verse Optimizer (HPSO-MVO) method. Hybrid PSO-MVO is combination of PSO used for exploitation phase and MVO for exploration phase in uncertain environment. Position and Speed of particle is modernised according to location of universes in each iteration. The hybrid PSO-MVO method has a fast convergence rate due to use of roulette wheel selection method. For the ORPD solution, standard IEEE-30 bus test system is used. The hybrid PSO-MVO method is implemented to solve the proposed problem. The problems considered in the ORPD are fuel cost reduction, Voltage profile improvement, Voltage stability enhancement, Active power loss minimization, and Reactive power loss minimization. The results obtained with the hybrid PSO-MVO method is compared with other techniques such as Particle Swarm Optimization (PSO) and Multi-Verse Optimizer (MVO). Analysis of competitive results obtained from HPSO-MVO validates its effectiveness compared to standard PSO and MVO algorithm.