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Three-phase systems have two configurations: the wye and delta. A star configuration can be three or four wires; in a delta configuration, the components are connected in a closed loop. Instantaneous power refers to the power value at a precise moment, and in a balanced three-phase system, it is constant. This is because the sum of the instantaneous powers in the three phases remains steady over time, despite individual fluctuations, due to the symmetry and phase relationship. The total...
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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Accurate parameter estimation for unbalanced three-phase system.

Yuan Chen1, Hing Cheung So1

  • 1Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong.

Thescientificworldjournal
|August 28, 2014
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Summary
This summary is machine-generated.

This study introduces a nonlinear least squares (NLS) estimator for smart grid parameter estimation. The NLS method accurately determines frequency, phase, and voltage, outperforming other techniques.

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Area of Science:

  • Electrical Engineering
  • Power Systems
  • Signal Processing

Background:

  • Smart grids are essential for modern electricity networks, often utilizing unbalanced three-phase power systems.
  • Accurate parameter estimation is crucial for the effective operation and control of these systems.

Purpose of the Study:

  • To develop and analyze an advanced parameter estimation technique for unbalanced three-phase smart grid systems.
  • To accurately estimate key parameters including frequency, phase, and voltage.

Main Methods:

  • Utilizing the α β-transformation to convert three-phase waveforms into orthogonal signals.
  • Developing a nonlinear least squares (NLS) estimator implemented via the Newton-Raphson scheme.
  • Analyzing the global convergence properties of the Newton-Raphson scheme for the NLS estimator.

Main Results:

  • The NLS estimator demonstrates accurate estimation of frequency, phase, and voltage parameters.
  • Mean square error performance of the NLS method approaches the Cramér-Rao lower bound.
  • The proposed NLS method offers superior frequency estimation accuracy compared to complex least mean square (CLMS) and augmented CLMS methods.

Conclusions:

  • The developed NLS estimator provides a robust and accurate solution for parameter estimation in unbalanced three-phase smart grids.
  • The method's performance validates its potential for enhancing smart grid control and stability.
  • Further research can explore the application of this estimator in real-time smart grid monitoring and management.