Three-Vector-Based Low-Complexity Model Predictive Direct Power Control Strategy for Doubly Fed Induction Generators

Abstract

This paper proposes a three-vector-based low-complexity model predictive direct power control (LC-MPDPC) strategy for doubly fed induction generators (DFIGs) in wind energy applications. Previous studies have applied one- and two-vector-based LC-MPDPC strategies for ac/dc converters with a satisfactory control performance. In this paper, an elaborated analysis of the DFIG mathematical model is made and then the feasibility of one- and two-vector-based LC-MPDPC strategies for DFIG are analyzed. However, using these approaches, the steady-state errors cannot be eliminated completely. Thus, a three-vector-based LC-MPDPC is further proposed to eliminate the power error. Both simulation and experimental results indicate that the proposed three-vector-based LC-MPDPC can significantly improve the steady-state performance and achieve an error-free control. In addition, its dynamic performance remains satisfactory compared with one- and two-vector-based LC-MPDPC.