Design of Optimal Backstepping Control for a Wind Power Plant System Using the Adaptive Weighted Particle Swarm Optimization

Abstract

This paper proposes a nonlinear optimal Backstepping method for controlling the doubly-fed induction generator used in wind energy conversion and obtainingmaximum power. The grid is connected directly to the stator. The rotor, on the other hand, is connected to the grid via two bidirectional converters. This work aims to regulate active and reactive power while maintaining a unit power factor using the proposed controller. The Lyapunov function guarantees the stability of the system. The most challenging aspect of Backstepping is determining the best positive constants, which are critical to the system performance. This process becomes more complex, especially when the generator parameters are uncertain or when the wind profile varies. As a result, optimizing the gains is an essential aspect of the controller design. The particle swarm optimization method is suggested for determining the optimum Backstepping constants. The performance and robustness of the proposed method are investigated and compared to the Conventional Backstepping and the Proportional-Integral Control strategies of a 5 MW wind power plant system under parameter variations and quickly changing wind speed profiles. Matlab/Simulink makes it possible to get results. The advised methodology ensures the tracking system's robust stability and reduces the response time to 1.8 (m s). Furthermore, it guarantees a negligible static error