Coordinated tuning of IPFC and PSS to improve power system stability using BFO

The Bacterial Foraging (BF) optimization algorithm imitates the foraging behavior of Escherichia coli (E. coli) bacteria that exist in human intestine, whose foraging habit is modeled as a distributed optimization process. This paper applies the BF algorithm to design optimal controllers of a single-machine-infinite-bus (SMIB) system equipped with an interline power flow controller (IPFC). The system is described by a set of nonlinear equations. The BF algorithm is used to tune the parameters of the IPFC control signals in the nonlinear optimization process. The controllers are optimally tuned to stabilize the system, increase system damping, and improve the steady-state response when the system is subjected to different disturbances. Simulations will demonstrate that the optimal BF-based controllers can significantly stabilize the system and efficiently damp low frequency oscillations under severe disturbances. The results are compared to the results obtained using the genetic algorithm (GA) to show the effectiveness of using BF to attain a global optimal solution of the design problem.