Three-vector based Low-complexity Model Predictive Direct Power Control Strategy for Doubly Fed Induction Generator - 2017

PROJECT TITLE :

Three-vector based Low-complexity Model Predictive Direct Power Control Strategy for Doubly Fed Induction Generator - 2017

ABSTRACT:

This paper proposes a 3-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. During this paper, an elaborated analysis of the DFIG mathematical model is made and then the feasibility of 1- and 2-vector-based mostly LC-MPDPC methods for DFIG are analyzed. But, using these approaches, the steady-state errors can't be eliminated fully. So, a 3-vector-primarily based LC-MPDPC is additional proposed to eliminate the ability error. Each simulation and experimental results indicate that the proposed 3-vector-based mostly LC-MPDPC will significantly improve the steady-state performance and achieve a mistake-free control. Furthermore, its dynamic performance remains satisfactory compared with one- and two-vector-based LC-MPDPC.

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