TY  - JOUR
T1  - Hybrid BFOA–PSO Approach for Damping Power System Oscillations by Using Facts Devices
AU - Ali, E.S. AU - Abd-Elazim, S.M. 
JO  - Journal of Engineering and Applied Sciences
VL  - 8
IS  - 3
SP  - 89
EP  - 96
PY  - 2013
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2013.89.96
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2013.89.96
KW  - Hybrid algorithm
KW  -particle swarm optimization
KW  -bacterial foraging
KW  -SSSC
KW  -damping oscillations
AB  - Social foraging behaviour of <I>Escherichia coli</I> bacteria 
  has recently been explored to develop a novel algorithm for optimization and 
  control. One of the major driving forces of Bacterial Foraging Optimization 
  Algorithm (BFOA) is the chemotactic movement of a virtual bacterium that models 
  a trial solution of the optimization problem. However during the process of 
  chemotaxis, the BFOA depends on random search directions which may lead to delay 
  in reaching the global solution. This study comes up with a hybrid approach 
  involving Particle Swarm Optimization (PSO) and BFOA algorithm called Bacterial 
  Swarm Optimization (BSO) for designing Static Synchronous Series Compensator 
  (SSSC) in a power system. In BSO, the search directions of tumble behaviour 
  for each bacterium are oriented by the individual’s best location and the global 
  best location of PSO. The proposed hybrid algorithm has been extensively compared 
  with BFOA and PSO. Simulation results have shown the validity of the proposed 
  BSO in tuning SSSC compared with BFOA and PSO. Moreover, the results are presented 
  to demonstrate the effectiveness of the proposed controller to improve the power 
  system stability over a wide range of loading conditions.
ER  -