Application of ACSA to solve single/multi objective OPF problem with multi type FACTS devices

This paper presents a multi-objective adaptive clonal selection algorithm (MOACSA) to minimise generation cost, transmission loss and voltage stability index (L-index) simultaneously. In this study multi-type voltage source converter (VSC) based flexible alternating current transmission systems (FACTS) devices such as unified power flow controller (UPFC), generalized unified power flow controller (GUPFC) and interline power flow controller (IPFC) are considered for single and multi objective optimization. In this algorithm, a non-dominated sorting and crowding distance techniques are used to find and manage Pareto optimal front. Further, a fuzzy based mechanism has been used to select best compromise solution from the Pareto set. The FACTS devices are incorporated as power injection models in optimization problem. The proposed MOACSA method has been tested on standard IEEE 30-bus test system with integration of these FACTS devices. The results are analyzed and compared with implementation of a standard nondominated sorting genetic algorithm-II (NSGA-II).