Application of nature-inspired algorithm for solving large- scale optimal power flow problem

Abstract

The conventional techniques for solving optimal power flow (OPF) problems usually become comparatively less effective, and the computational difficulties increase significantly with increasing network size and complexity. To overcome the shortcomings of the conventional techniques, nature-inspired methods like the particle swarm optimization (PSO) method have been developed and applied to OPF problems in the recent years. This paper is hinged on the need to adopt these heuristic approaches in solving power flow problems in the Nigeria power system. This was demonstrated in this thesis, by implementing the conventional Newton Raphson method and a nature-inspired method, the particle swarm optimization technique in the IEEE 14 Bus network and validating the efficacy of the results gotten from the two methods on the Nigeria 330kV 52-Bus network to show the superior performance of the PSO technique. The results from the implementation of the PSO algorithm showed that the total active power and reactive power losses were substantially reduced to 175.1MW and 81.4MVAR and the system time of convergence was faster and occurred after 2 iterations at 2.03seconds. Thus it could be seen that the PSO algorithm have proved to exhibit a superior performance for optimisation of a large power system at a better speed of convergence when compared with the Newton Raphson method.