Finite-Set Model Predictive Power Control with Common Mode Voltage Elimination for an Asymmetrical Double-Star Induction Generator Wind Energy Conversion System
Publish place: majlesi Journal of Electrical Engineering، Vol: 17، Issue: 3
Publish Year: 1402
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_MJEE-17-3_016
تاریخ نمایه سازی: 4 مهر 1402
Abstract:
The Finite-Set Model Predictive Power Control (FS-PPC) is one of the most intriguing model predictive approaches for the induction machine. This control is successful because it operates without weight coefficients and does not require the rotor flux position, as in the Predictive Torque Control (FS-PTC) and the Predictive Current Control (FS-PCC), respectively. A simple extension to the double-star induction generator results in significant current harmonics and common mode voltage. To fix these issues, this paper proposes an improved FS-PPC applied to an asymmetric double-star induction generator based wind energy conversion system by introducing two concepts: (a) the virtual voltage vector (VVV), in order to eliminate the (x, y) components of the stator currents. (b) the zero common mode voltage vectors (ZCMV), to eliminate the common mode voltage. A simulation of the developed ZCMV-FS-PPC system control is created in MATLAB/Simulink. The results show the effectiveness of this approach with CMV equal to zero and negligible (x, y) components of the stator currents. Moreover, the elimination of the CMV not only avoids its damage but also reduces the computation by ۵۰%.
Keywords:
Predictive power control , virtual voltage vector , zero common mode voltage , double-star induction generator , Wind Energy Conversion System
Authors
Yanis Hamoudi
Laboratoire de Maitrise des Energies Renouvelables (LMER), Faculte de Technologie, Universite de Bejaia, ۰۶۰۰۰ Bejaia, Algeria
Hocine Amimeur
Laboratoire de Maitrise des Energies Renouvelables (LMER), Faculte de Technologie, Universite de Bejaia, ۰۶۰۰۰ Bejaia, Algeria.
Sabrina Nacef
Laboratoire de Maitrise des Energies Renouvelables (LMER), Faculte de Technologie, Universite de Bejaia, ۰۶۰۰۰ Bejaia, Algeria.