Hybrid biogeography-based optimisation for optimal power flow incorporating FACTS devices

Abstract

This paper presents hybrid biogeography–based optimisation (BBO) technique to solve optimal power flow (OPF) in power system incorporating flexible AC transmission systems (FACTS). The proposed hybrid method combines the BBO algorithm with the differential evolution (DE) to improve the performance of the conventional BBO and DE algorithms. Here, BBO is the main optimiser, while the DE is used to fine tune the solution of the BBO algorithm. Two types of FACTS devices namely, thyristor–controlled series capacitor (TCSC) and thyristor–controlled phase shifter (TCPS) are considered in this paper. The proposed method is implemented with MATLAB and tested on modified IEEE 30–bus system in five different cases. The simulation results show that the proposed HDE–BBO algorithm is effective, fast and accurate in finding the optimal parameter settings for FACTS devices to solve OPF problems. The proposed HDE–BBO method gives better solution quality compared to particle swarm optimisation with inertia weight approach (PSOIWA), real coded genetic algorithm (RGA), differential evolution (DE) and conventional BBO. The simulation study also shows that FACTS devices are capable of providing an economically attractive solution to power system problems.