A Comparative Study of GA, PSO and Big Bang-Big Crunch Optimization Techniques for Optimal Placement of SVC

Dr. H. K. Verma; Cheshta Jain; Arun Rathore; Priyanka Gupta

In a power system, at heavily loaded conditions, there is always a probability of line outage and consequent voltage instability issues. So that the problem of enhancing the voltage profile and decreasing power losses in electrical systems is a task that must be solved in an optimal way. This optimality can be easily achieved by efficient usage of existing facilities along with installing FACTS devices. This paper presents a comparative study of various optimization techniques such as Genetic Algorithm, Particle Swarm Optimization (PSO) and Big Bang-Big Crunch algorithm for optimal placement of Static VAr Compensator (SVC) to improve voltage stability and to considering cost function. The effectiveness of the proposed algorithms have been tested in IEEE-14 Bus test system and it has also been observed that the proposed algorithm can be applied to larger systems and do not suffer with computational difficulties.

Select Volume / Issues:

• Volume 3 Issue 3, May 2012

Year:

2012

Type of Publication:

Article

Keywords:

Big Bang - Big Crunch BB-BC; Genetic AlgorithmGA; Particle Swarm OptimizationPSO; SVC Placement

Journal:

IJECCE

Volume:

3

Number:

3

Pages:

466-472

Month:

May