Hybrid sliding neural network controller of a direct driven vertical axis wind turbine

This study aims to propose a robust hybrid sliding mode artificial neural network control (SM-ANN) scheme for controlling the stator power (active/reactive) of doubly fed induction generator (DFIG)-based direct drive vertical axis wind turbine (VAWT) system under real-world scenario speed that will be installed in Adrar region (Saharan zone) Algeria. The SM-ANN VAWT power. chattering phenomenon is most significant disadvantage associated with (SMC). In order find solution this issue, (ANN) method was applied pick appealing part SMC. MATLAB/Simulink used do an evaluation, after which controller being suggested compared both traditional (SM) and proportional-integral (PI) controllers. results simulation demonstrated recommended has good performance terms enhancing quality energy delivered network. comparison SM PI controllers, have long history use. Notwithstanding fact there DFIG parameter fluctuation present.