Optimized Sliding Mode Regulation based on PSO Algorithm for Nonlinear DFIG-WT

Abstract

The inherent growth of the nonlinear eects, wind-speed swing and parametersuncertainty are challenges in the modern power system based on wind turbines that includesa doubly fed induction generator (DFIG-WT). In addition to being subject to voltage dropconditions, makes it necessary to design reliable control units to meet the system nominalpower. According to these considerations, a new rotor-aspect current control revolve on activeandreactive-power (Ps-Qs) control is suggested by using a sliding mode technique via discreteparticle swarm optimization control (RPSMC-PSO) based on the recurrent construction ofneural network RNN for the nonlinear DFIG-WT. Based on features of the low-degree Taylorapproximation principle, the RNN is reconstructed to simplify the optimization problem of thePSO to generate the optimal sliding switch signals. The main advantage of this technique isto force the quasi-chatter behavior of SMC for the nonlinear system to be close to the optimalsliding trajectory in a few steps and less calculation burden of algorithm. Thus, the controllaw guarantees the general stability of the system and also attenuates the unimportant chatterimpacts. Also, the suggested control approach is compared against standard control as SMC andPI controller (Proportional-Integral). Moreover, a 1.5 MW DFIG is inspected to validate thedynamic results of open source of FAST turbine model. The dynamic results show preference of RPSMC-PSO in terms of the dynamic effectiveness of the DFIG-WT under numerous dynamicinvestigations comparing with the standard control approaches.