A Novel Supervised Control Strategy for Interconnected DFIG-Based Wind Turbine Systems: MiL Validations

This work presents the overall model of the doubly fed induction generator (DFIG) and proposes a new control design for the grid side converter of the concerned DFIG plant. The system under study consists of two DFIG wind turbines which are connected to the grid by a bi-directional Z-source inverter. In order to ameliorate the DC link voltage regulation of the DFIG generation plant; particularly, a new supervised control method is introduced and is directly applied to the grid side converter (GSC). In this way, initially, by tuning two control coefficients (CCs) which forms the footprint of uncertainty (FOU), a double-input interval type-2 fuzzy logic (DIT2-FL) is designed for the GSC system. The best setting of the control coefficients for the desired performance of the concerned system is recommended and a new DIT2-FL supervised online adaptive neuro fuzzy inference system (ANFIS) is then developed accordingly. By implementing the supervised controller, the dynamic behavior of the tested wind turbines under two distinct operations for low/high wind speeds is investigated. Detailed experimental outcomes have been presented to ascertain the correctness and accuracy of the suggested control methodology. Compared with the prevalent state-of-the-art techniques, the suggested controller leads to remarkable transient improvement of closed-loop DFIG system.