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.
