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Related Concept Videos

Routh-Hurwitz Criterion I01:15

Routh-Hurwitz Criterion I

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Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
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Pole and System Stability01:24

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The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
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Plotting and Calibrating the Root Locus01:19

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Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is...
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Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

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In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
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A kurtosis-ESPRIT algorithm for RealTime stability assessment in droop controlled microgrids.

Adham Osama1, Abdallah F El-Hamalawy2, Mohammed E Ammar2

  • 1Advanced Power and Energy Center (APEC), Electrical Engineering Department, Khalifa University, Abu Dhabi, UAE. 100059837@ku.ac.ae.

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|January 13, 2025
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Summary

This study introduces Kurtosis-Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) for analyzing inverter-based microgrids (IBMGs). The method accurately identifies dominant modes using real-time data, outperforming existing techniques in various conditions.

Keywords:
Distributed generationDroop controlESPRIT techniqueKurtosis measureLow-frequency oscillationsMicrogridsSmall-signal stability

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Area of Science:

  • Electrical Engineering
  • Power Systems
  • Control Systems

Background:

  • Existing analytical models for droop-controlled microgrids are computationally intensive and fail to account for real-time parameter and operational variations.
  • Accurate real-time analysis of inverter-based microgrids (IBMGs) is crucial for stability and performance.
  • Dominant mode identification is essential for understanding microgrid dynamics.

Purpose of the Study:

  • To propose a novel method, Kurtosis-Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), for identifying dominant modes in droop-controlled IBMGs.
  • To utilize local real-time measurements for mode estimation, overcoming limitations of complex analytical models.
  • To introduce a kurtosis measure for assessing signal characteristics and mode prominence.

Main Methods:

  • A short-duration disturbance is applied to the active power droop gain of a selected distributed generator (DG).
  • Dominant system modes are estimated from local real-time measurements using the ESPRIT algorithm.
  • A kurtosis measure is employed to evaluate signal quality and the significance of estimated modes.

Main Results:

  • The proposed Kurtosis-ESPRIT method demonstrates higher estimation accuracy compared to Prony, Matrix Pencil, and Subspace Identification techniques.
  • The algorithm exhibits robust performance in noisy environments, under varying load conditions, and with different network configurations.
  • Validation through MATLAB/SIMULINK simulations and OPAL-RT controller-in-the-loop experiments confirms the effectiveness and real-time applicability.

Conclusions:

  • The Kurtosis-ESPRIT approach provides an effective and computationally efficient solution for real-time dominant mode identification in droop-controlled IBMGs.
  • The method's robustness and accuracy make it suitable for practical microgrid monitoring and control applications.
  • This technique enhances the ability to analyze and manage microgrid stability under dynamic operating conditions.