TITLE:
Hybrid Swarm Algorithm for Multiobjective Optimal Power Flow Problem
AUTHORS:
K. Rajalashmi, S. U. Prabha
KEYWORDS:
Multiobjective, OPF, Optimization, Hybrid
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.11,
September
8,
2016
ABSTRACT: Optimal power flow problem
plays a major role in the operation and planning of power systems. It assists
in acquiring the optimized solution for the optimal power flow problem. It
consists of
several objective functions and constraints. This paper solves the
multiobjective optimal power flow problem using a new hybrid technique by combining
the particle swarm optimization and ant colony optimization. This hybrid method overcomes the drawback in local
search such as stagnation and premature convergence and also enhances the
global search with chemical communication signal. The best results are
extracted using fuzzy approach from the hybrid algorithm solution. These
methods have been examined with the power flow objectives such as cost, loss
and voltage stability index by individuals and multiobjective functions. The
proposed algorithms applied to IEEE 30 and IEEE 118-bus
test system and the results are analyzed and validated. The proposed algorithm
results record the best compromised solution with minimum execution time
compared with the particle swarm optimization.