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Enhancing power grid synchronization and stability through time-delayed feedback control.

Halgurd Taher1,2, Simona Olmi1,3, Eckehard Schöll2

  • 1Inria Sophia Antipolis Méditerranée Research Centre, 06902 Valbonne, France.

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|January 23, 2020
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Summary
This summary is machine-generated.

This study uses the Kuramoto model to analyze power grid synchronization and stability. Time-delayed feedback control is proposed to maintain grid stability by managing critical nodes.

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Area of Science:

  • Power Systems Engineering
  • Nonlinear Dynamics
  • Complex Networks

Background:

  • The Kuramoto model captures essential power grid dynamics, including AC voltage phase.
  • Inertia and bimodal frequency distributions are crucial for modeling generators and loads.
  • Understanding synchronization and stability is vital for reliable power transmission.

Purpose of the Study:

  • To investigate power grid synchronization and stability using the Kuramoto phase oscillator model with inertia.
  • To identify critical nodes prone to synchronization deviations.
  • To propose and evaluate time-delayed feedback control for enhancing grid stability.

Main Methods:

  • Utilized the Kuramoto phase oscillator model with inertia and bimodal frequency distribution.
  • Identified critical nodes via solitary frequency deviations and Lyapunov vectors.
  • Applied and compared various time-delayed feedback control strategies.
  • Validated the control method on German and Italian power transmission grids.

Main Results:

  • Identified critical nodes through frequency deviations and Lyapunov exponents.
  • Demonstrated the effectiveness of time-delayed feedback control in achieving synchronization and Lyapunov stability.
  • Determined the minimum number of controlled nodes required for stability.
  • Showcased the control method's applicability across different network configurations and operating points.

Conclusions:

  • Time-delayed feedback control is an efficient strategy for maintaining power grid synchronization and stability.
  • The proposed method effectively manages critical nodes and ensures electrodynamical behavior.
  • The study provides a robust framework for enhancing the resilience of power transmission networks.