Iterative Frequency Estimation Based on MVDR Spectrum

Abstract

Frequency estimation is an important task in a power system since the frequency deviation is a yardstick for the power system abnormal operating conditions. This paper presents a new frequency-estimation algorithm based on the minimum variance distortionless response spectrum that has advantages of accuracy, fast convergence, and modest complexity. To reduce complexity without a trade off of accuracy, an iterative searching method is introduced. An adaptive step-size method is also introduced to reduce gradient noise. Complexity of the proposed algorithm is <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> ) or <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) depending on environments where <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> is the dimension of correlation matrix. When compared with other conventional adaptive algorithms, simulation results show that the proposed algorithm improves convergence speed, and has lower frequency estimation error in cases of high signal-to-noise ratio.