Multi-variables, single objective optimal power flow of IEEE-30 bus system using particle swarm optimisation, artificial bee colony, and cuckoo search algorithms

Abstract

Particle swarm optimisation (PSO), artificial bee colony (ABC), and cuckoo search (CS) nature-inspired algorithms used extensively to solve optimisation problems in different fields of engineering, including optimal power flow (OPF) in power distribution systems. In this paper, MATLAB software was used to optimise multi-variables including the fuel cost, power losses and voltage deviations in IEEE-30 bus system as one objective function based on PSO, ABC, CS algorithms. The ABC algorithm shows the lowest objective function of 978.78025, the best fuel cost of 830.54 ($/h), best power losses of 6.1235 (MW) and voltage deviation of 0.14417 (p.u.). While the CS algorithm showed the moderately objective function of 984.7569, PSO search algorithm has the highest objective function of 1,067.6442. These three algorithms approve each other in OPF and confirm the usage of this algorithm in combining several variables in one objective function.