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Frequency-Adaptive Stationary-Reference-Frame Grid Voltage Sequence Detector for Distributed Generation Systems

delete2011-09-01
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PRE
AI
E
Eider Robles *
J
Josep Pou
S
Salvador Ceballos
J
Jordi Zaragoza
J
José Luis Martín Martín
I
Ibanez, Pedro
DOI:10.1109/TIE.2010.2098352delete
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Abstract

Abstract

En 中文
This paper proposes a stationary-frame sequence detector (SFSD) structure for determining the positive sequence in three-phase systems. The structure includes the use of the Clarke transformation and moving average filters (MAFs). The positive-sequence phase angle can be obtained from the alpha-beta components; however, such a detection becomes inaccurate if the grid voltages are unbalanced and/or distorted. The MAF is used to filter the nonideal components. Performance of the MAF is analyzed mathematically for a proper selection of the window width of the optimal filter in this application. The time delay introduced by MAFs is constant and known; hence, this may be compensated. The proposed detector structure allows fast detection of the grid voltage positive sequence (within one grid voltage cycle). The MAF completely eliminates any oscillation multiple of the frequency for which it is designed; thus, this algorithm can overcome the presence of imbalances or harmonics in the electrical grid. Furthermore, it includes a simple frequency estimator that makes the SFSD frequency adaptive and is capable of operating under large frequency changes. The entire SFSD is verified through simulation and experiment, showing very good performance even under several extreme grid voltage conditions.
Keywords:
Frequency estimation
grid-connected converters
moving average filter (MAF)
sequence detector
stationary reference frame
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Journal

IEEE Transactions on Industrial Electronics cover
IEEE Transactions on Industrial Electronics
IF:
7.2
Papers:
1.8W
Citations:
9.8W

Organization

U
university of basque country
Scholars:
1.9W
Papers: 1.6W
Citations: 17
U
universitat politecnica de catalunya
Scholars:
1.9W
Papers: 1.6W
Citations: 17