Turkish Journal of Electrical Engineering and Computer Sciences




The electrical power extracted from a wind energy conversion system (WECS) tends to be inconsistentdue to the intermittent nature of the wind. This issue is addressed by formulating a maximum power point tracking(MPPT) control strategy that optimizes the power extraction from the WECS under a wide range of wind speed profiles.This research article focuses on the formulation of a nonlinear neuro-adaptive backstepping integral sliding mode control(NABISMC) based MPPT strategy for a standalone, variable speed, fixed-pitch WECS equipped with a permanentmagnet synchronous generator (PMSG). The proposed paradigm is a hybrid of the conventional backstepping andthe integral sliding mode control (ISMC) based MPPT schemes. The effectiveness of the control strategy devised isguaranteed through numerical simulations carried out in Matlab/Simulink for a 3kW PMSG-WECS under a stochasticwind speed profile. Further validation is guaranteed by giving a detailed performance comparison analysis of the proposedMPPT control strategy with the conventional feedback linearization control (FBLC), proportional integral derivative(PID) control, sliding mode control (SMC), and standard neuro-adaptive integral sliding mode control (NAISMC) basedMPPT strategies, where the proposed strategy is found superior to all the stated strategies in terms of offering moreaccurate MPPT, lower steady state error, faster dynamic response and lesser chattering.


Wind energy conversion system (WECS), permanent magnet synchronous generator (PMSG), maximumpower point tracking (MPPT), variable speed wind turbine (VSWT), backstepping, integral sliding mode control (ISMC), feedforward neural network

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