Keywords: optimal power flow, OPF, biogeography based optimisation, BBO, particle swarm optimisation, PSO, genetic algorithms, GAs, evolutionary programming, constriction factors, inertia weight, mutation, migration, simulation, differential evolution
Optimal power flow using biogeography based optimisation
This paper presents a novel biogeography based optimisation (BBO) algorithm for solving constrained optimal power flow (OPF) problems in power system. In this paper, the feasibility of the proposed algorithm is demonstrated for IEEE 30-bus and IEEE 118-bus systems with three different objective functions and it is compared to other population based optimisation techniques. A comparison of simulation results reveals better solution quality and computation efficiency of the proposed algorithm over hybrid particle swarm optimisation with constriction factor approach (PSOCFA), hybrid particle swarm optimisation with inertia weight approach (PSOIWA), real coded genetic algorithm (RGA) and differential evolution (DE) for the global optimisation of constrained OPF problems.