Comparative study of Pareto optimal multi objective cuckoo search algorithm and multi objective particle swarm optimization for power loss minimization incorporating UPFC

Abstract

The Flexible AC Transmission System (FACTS) devices are being commissioned in electrical power systems across the globe owing to the vast array of benefits they offer. The optimal performance of the FACTS devices can be harnessed only if they are installed at a strategic location. In this paper, the authors suggest the merit of multiobjective cuckoo search (MOCS) algorithm in mitigation of transmission losses by strategically installing unified power flower controller (UPFC) at an optimal location. Active power loss and reactive power loss reduction is the multiobjective optimization considered for the study. The Pareto-optimal technique is employed to extract the Pareto-optimal solution for the multiobjective problem considered. The Fuzzy logic method is utilized to yield the best-compromise solution from the pool of Pareto-optimal solution. The proposed approach is tested on a standard IEEE 30 bus test system. Furthermore, the efficacy of the MOCS algorithm is demonstrated by comparing the results with that of multiobjective particle swarm optimization (MOPSO).