Rooted Tree Optimization for Backstepping Power Control of DFIG Wind Turbine: dSPACE Implementation

Abstract

This work is devoted to a new contribution to the field of optimization and control of a wind energy conversion system (WECS). A Rooted Tree Optimisation (RTO) will be applied to the non-linear adaptive Backstepping technique to improve its robustness and performance. The non-linear Backstepping control was carried out to control the powers of the doubly-fed induction generator (DFIG) connected to the electrical network by two converters (network side and machine side). Initially, a review of the wind power system was presented. Then, an exhaustive explanation of the Backstepping technique based on the Lyapunov stability and the optimization method was reported. Subsequently, a validation on the Matlab & Simulink environment was carried out to test the performance and robustness of the proposed model. The last part of this work was dedicated to the experiment of the Backstepping adaptive algorithm on a test bench using the dSPACE-DS1104 card, to prove the performance of the system. The results obtained of this work either by follow-up or robustness tests or by experimental validation show a great improvement in terms of performance compared to other control techniques.

Fuzzy sliding mode power control for wind power generation systems connected to the grid

“…The equation for the wind power recoverable by the wind turbine is [10]− [13]: The total kinetic power in the wind turbine is:…”