Adaptive Phasor Estimation Algorithm Based on a Least Squares Method

Woo-Joong Kim, Soon-Ryul Nam and Sang-Hee Kang
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Woo-Joong Kim: Department of Electrical Engineering, Myongji University, Yongin 17058, Korea
Soon-Ryul Nam: Department of Electrical Engineering, Myongji University, Yongin 17058, Korea
Sang-Hee Kang: Department of Electrical Engineering, Myongji University, Yongin 17058, Korea

Energies, 2019, vol. 12, issue 7, 1-15

Abstract: This paper proposes an adaptive phasor estimation algorithm based on a least square method that can suppress the adverse effect of an exponentially decreasing DC offset component in a phasor estimation process. The proposed algorithm is composed of three stages: a basic least squares model, a time constant calculation, and an adaptive least squares model. First, we use the basic least squares model to estimate the parameter of the DC offset component in the fault current signal. This model is designed to incorporate fundamental frequency, and harmonic and constant components. Second, we use the estimated parameter to calculate the time constant of the DC offset component. Third, we redesign a least squares model that incorporates fundamental frequency, harmonic components, and exponential function of the DC offset component. Since this model incorporates the exponential function of the DC offset component contained in the fault current signal, it estimates the phasor of the correct fundamental frequency component without influence of the DC offset component. We evaluated the performance of the proposed algorithm using computer generated signals and EMTP simulation signals. The evaluation results show that the proposed algorithm can effectively suppress the adverse influence of the exponentially decaying DC offset component.

Keywords: least squares method; phasor estimation; DC offset (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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