Small selection of a suitable optimization tool to

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Last updated: December 31, 2019

Small signal stability isa challenging task for a recent power system network interconnected by weak tielines and continuously subjected to different disturbances.

This stabilityissue is addressed here in term of low frequency oscillations in the range of0.2 to 3Hz observed in an extended PS(power system) network1.Power systemstabilizer(PSS) has been very popular to damp these oscillation but, withvariation in operating conditions, the performance of PSS may vary2.With theinclusion of power semiconductor technology, FACTS devices are becoming morepopular for enhancing stability and improving controllability of PS3,4,5,6.

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As per researches the PSS based on FACTS devices are more superior incomparison to conventional PSS 7,8, 9. UPFC is a versatile member of FACTSfamily with three controllable variables, which are magnitude, phase angle ofseries injected voltage and reactive current drawn by shunt voltage sourceconverter (VSC). Wang 10 has addressed linear Heffron-phillips transfer  functionmodel with UPFC for small signal stability assessment. But a systematic processto 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 controllerparameter and which can be better obtained by a suitable optimizationtechnique12.

So the next important task is selection of a suitableoptimization tool to handle the problem. The evolution in nature has givenimpulse to different promising optimization techniques employing populationbased search. PSO is a simple, efficient and robust optimization technique andalready being used to optimize damping controller parameter 13, 14. But, itis prone to premature convergence and while handling heavy constrainedoptimization problem. It may trap in local optima. The differential evolution(DE) technique has been implemented for optimal location parameter setting anddamping controller parameter tuning based on SSSC and reactive power management15, 16.

                                  Recently,metaheuristics algorithms are gaining much popularity because they are simple,can be easily implemented and inspired by natural phenomenon like behaviour ofanimals. Also they need less parameters to tune with straight forwardproperty17.The GWO has been reported in17, which has been influenced by theidea and strategy of Grey wolves in their hunting process. GWO technique hasbeen used in 18 to design damping controller with lead-lag controller.Different hybrid techniques are also proposed in current literatures to designdamping controller like hGA-GSA in19 and DE-GWO in20 where lead-lagcontrollers and dual controllers have been implemented. The GWO can providegood balance in exploration and exploitation, but it may trap in local optimadue to dependency on certain mechanism 21.

Hence the performance of GWO hasbeen modified in 21, where the searching agent’s movement in searched spacehas been modified. This modified version of GWO has been utilized here todesign damping controller and again the earlier lead-lag controller has beenmodified with PI controller for optimum efficacy of controller.In this workmodified GWO has been proposed to tune UPFC base PI-lead-lag   controller.    

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