Grid Impedance Estimation Using Several Short-Term Low Power Signal Injections

Document Type : Research Article

Authors

1 Image Processing & Data Mining Lab, Shahrood University of Technology, Shahrood, Iran

2 Power Engineering Group, the University of Queensland, Queensland, Australia

Abstract

In this paper, a signal processing method is proposed to estimate the low and high-frequency impedances of power systems using several short-term low power signal injections for a frequency range of 0-150 kHz. This frequency range is very important, and thusso it is considered in the analysis of power quality issues of smart grids. The impedance estimation is used in many power system applications such as power quality analysis of smart grids and grid connected renewable energy systems. The proposed impedance estimation technique is based on applying a wideband voltage signal at a Point of Common Coupling (PCC) and then a division of the voltage to a generated current signal in a frequency range of 0-150 kHz. In a noisy system, the energy of the injected signal must be sufficient for an accurate approximation. This is the main issue in proposing a new method for the impedance estimation. In this paper, our simulation error is additive white Gaussian noise which is considered as a generic measurement noise. The proposed algorithm consists of three main parts: 1) Determining several injection signals with sufficient energy using the Genetic algorithm. At least one of the determined signals should have sufficient energy in some frequencies so that the union of these ranges is can be the universal set of estimation. 2) Injecting individuals of the signals to the grid separately, and estimating the impedance following Ohm’s law. The width of injection signals is calculated by the best chromosome in GA. 3) The fusion of estimated impedances. The simulation results show that the proposed method can properly estimate grid impedance in a wide frequency range up to 150 kHz.

Keywords

Main Subjects

References

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AUT Journal of Electrical Engineering
Volume 50, Issue 2
December 2018
Pages 169-176

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