Optimal Reactive Power Dispatch Using Quasi-Oppositional Biogeography-Based Optimization

In this paper, quasi-oppositional biogeography based-optimization (QOBBO) for optimal reactive power dispatch (ORPD) is presented. The proposed methodology determines control variable settings such as generator terminal voltages, tap positions of the regulating transformer and the Var injection of the shunts compensator, for real power loss minimization in the transmission system. The algorithm's performance is studied with comparisons of canonical genetic algorithm (CGA), five versions of particle swarm optimization (PSO), local search based self-adaptive differential evolution (L-SADE), seeker optimization algorithm (SOA), biogeography based optimization (BBO) on the IEEE 30-bus and IEEE 57-bus power systems. The simulation results show that the proposed QOBBO approach performed better than the other listed algorithms and can be efficiently used for the ORPD problem.