Power control of wind energy conversion system under multiple operating regimes with deep residual recurrent neural network: theory and experiment

This paper makes a research for the speed control of wind turbine system under multiple operating regimes, which also studied the sleep residual recurrent neural network method in this work. We aim at designing deep residual recurrent neural network robust controllers, which guarantee the existence of the multiple regime system poles in some predefined zone and wind speed precise tracking. Moreover, the feedback gains which guarantee desired speed tracking performance are obtained by solving the Lyapunov stability functions. The results are applied to a directly driven wind energy conversion experiment systems and the numerical experiment, comparing with the existing results, shows the satisfactory performance of the proposed method.