PROJECT TITLE :
Three-vector based Low-complexity Model Predictive Direct Power Control Strategy for Doubly Fed Induction Generator - 2017
ABSTRACT:
This paper proposes a three-vector-based mostly 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 2-vector-primarily based LC-MPDPC methods for ac/dc converters with a satisfactory control performance. During this paper, an elaborated analysis of the DFIG mathematical model is made and then the feasibility of one- and two-vector-primarily based LC-MPDPC strategies for DFIG are analyzed. However, using these approaches, the steady-state errors can not be eliminated utterly. Therefore, a 3-vector-primarily based LC-MPDPC is more proposed to eliminate the ability error. Each simulation and experimental results indicate that the proposed 3-vector-primarily based LC-MPDPC will considerably improve the steady-state performance and achieve a slip-up-free control. Moreover, its dynamic performance remains satisfactory compared with one- and 2-vector-based LC-MPDPC.
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