Small selection of a suitable optimization tool to

Small signal stability is
a challenging task for a recent power system network interconnected by weak tie
lines and continuously subjected to different disturbances. This stability
issue is addressed here in term of low frequency oscillations in the range of
0.2 to 3Hz observed in an extended PS(power system) network1.Power system
stabilizer(PSS) has been very popular to damp these oscillation but, with
variation in operating conditions, the performance of PSS may vary2.With the
inclusion of power semiconductor technology, FACTS devices are becoming more
popular for enhancing stability and improving controllability of PS3,4,5,6.
As per researches the PSS based on FACTS devices are more superior in
comparison to conventional PSS 7,8, 9. UPFC is a versatile member of FACTS
family with three controllable variables, which are magnitude, phase angle of
series injected voltage and reactive current drawn by shunt voltage source
converter (VSC). Wang 10 has addressed linear 
Heffron-phillips transfer  function
model with UPFC for small signal stability assessment. But a systematic process
to design UPFC based damping controller has been reported in11.In this work,
the optimal controller parameters were designed by conventional approach.
However the most important decisive task is online tuning of controller
parameter and which can be better obtained by a suitable optimization
technique12.So the next important task is selection of a suitable
optimization tool to handle the problem. The evolution in nature has given
impulse to different promising optimization techniques employing population
based search. PSO is a simple, efficient and robust optimization technique and
already being used to optimize damping controller parameter 13, 14. But, it
is prone to premature convergence and while handling heavy constrained
optimization problem. It may trap in local optima. The differential evolution
(DE) technique has been implemented for optimal location parameter setting and
damping controller parameter tuning based on SSSC and reactive power management
15, 16.

metaheuristics algorithms are gaining much popularity because they are simple,
can be easily implemented and inspired by natural phenomenon like behaviour of
animals. Also they need less parameters to tune with straight forward
property17.The GWO has been reported in17, which has been influenced by the
idea and strategy of Grey wolves in their hunting process. GWO technique has
been used in 18 to design damping controller with lead-lag controller.
Different hybrid techniques are also proposed in current literatures to design
damping controller like hGA-GSA in19 and DE-GWO in20 where lead-lag
controllers and dual controllers have been implemented. The GWO can provide
good balance in exploration and exploitation, but it may trap in local optima
due to dependency on certain mechanism 21. Hence the performance of GWO has
been modified in 21, where the searching agent’s movement in searched space
has been modified. This modified version of GWO has been utilized here to
design damping controller and again the earlier lead-lag controller has been
modified with PI controller for optimum efficacy of controller.In this work
modified GWO has been proposed to tune UPFC base PI-lead-lag   controller.