Graph Laplacian Spectrum and Primary Frequency Regulation: Preprint

Changhong Zhao, Linqi Guo, Steven Low

Research output: Contribution to conferencePaper


We present a framework based on spectral graph theory that captures the interplay among network topology, system inertia, and generator and load damping in determining overall power grid behavior and performance. Specifically, we show that the impact of network topology on a power system can be quantified through the network Laplacian eigenvalues, and such eigenvalues determine the grid robustness against low frequency disturbances. Moreover, we can explicitly decompose the frequency signal along scaled Laplacian eigenvectors when damping-intertia ratios are uniform across buses. The insight revealed by this framework suggests why load-side participation in frequency regulation not only makes the system respond faster, but also helps lower the system nadir after disturbance. Finally, by presenting a new controller specifically tailored to suppress high frequency disturbances, we demonstrate that our results can provide useful guidelines in the controller design for load-side primary frequency regulation. We simulate the improved controller on the IEEE 39-bus New England interconnection system to illustrate its robustness against high frequency oscillation compared to both the conventional droop control and a recent controller design.
Original languageAmerican English
Number of pages11
StatePublished - 2019
EventIEEE Conference on Decision and Control - Miami, Florida
Duration: 17 Dec 201819 Dec 2018


ConferenceIEEE Conference on Decision and Control
CityMiami, Florida

Bibliographical note

See NREL/CP-5D00-73482 for paper as published in IEEE proceedings

NREL Publication Number

  • NREL/CP-5D00-71124


  • electric power grids
  • frequency regulation
  • graph Laplacian spectrum
  • performance


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