Graph Laplacian Spectrum and Primary Frequency Regulation

Changhong Zhao, Linqi Guo, Steven Low

Research output: Contribution to conferencePaper

23 Scopus Citations


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 the overall 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-inertia ratios are uniform across buses. The insight revealed by this framework partially explains why load-side participation in frequency regulation not only makes the system respond faster, but also helps lower the system nadir after a 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. This improved controller is simulated on the IEEE 39-bus New England interconnection system to illustrate its robustness against high frequency oscillations compared to both the conventional droop control and a recent controller design.
Original languageAmerican English
Number of pages8
StatePublished - 2019
Event2018 IEEE Conference on Decision and Control (CDC) - Miami Beach, Florida
Duration: 17 Dec 201819 Dec 2018


Conference2018 IEEE Conference on Decision and Control (CDC)
CityMiami Beach, Florida

Bibliographical note

See NREL/CP-5D00-71124 for preprint

NREL Publication Number

  • NREL/CP-5D00-73482


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


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