Data From: Method of Modeling the Swing Equation Using Time Synchronized Measurements

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In three phase, high-voltage transmission systems, synchronous generators accelerate or decelerate to adapt to changing power transfer requirements that occur during system disturbances. In network electrical power systems, frequency changes constantly based on system dynamics. Modeling network dynamics from oscillations and transients using time-synchronized measurements can provide real-time information, including angular displacements, voltage and current phasors, frequency changes, and rate of signal system decay from positive-sequence components.

Power system voltage and current waveforms are not steady-state sinusoids, especially during system disturbances. These waveforms contain sustained harmonic and non-harmonic components. Additionally, because of faults and other switching electromagnetic transients, there may be step changes in the magnitude and phase angles of these waveforms. Resonances in the power network create additional frequencies. Other disturbances may exhibit relatively slow changes in phase angles and magnitudes due to oscillations of machine rotors during electromechanical disturbances.

Power System stability is that property of a system that enables the synchronous machines of the system to respond to a disturbance and return to normal operating conditions. To determine the system characteristics, analysis of system stability can be performed by transient, dynamic and steady-state stability studies.

The equation governing the motion of the rotor of a synchronous machine is based on an elementary principle of dynamics, where accelerating torque is the product of the moment of inertia of the rotor times its angular acceleration. During a disturbance, how the rotor will accelerate or decelerate is described in relative motion by the swing equation.

This research uses archived PMU data obtained from the Bonneville Power Administration to demonstrate a feasible technique for transient stability system analysis. This work demonstrates a practical method of using ROCOF from PMU data with a MATLAB analysis fit program to determine the system coefficients used to calculate the damping coefficient and inertia constant, which are necessary to create a practical swing equation.

The dataset supports a Master of Science (M.S.) in Electrical and Computer Engineering thesis, Method of Modeling the Swing Equation Using Time Synchronized Measurements

Thesis Advisor: Robert Bass, Ph.D


The archive contains two file types. Data fit functions are written in Matlab .m files. PMU event Data are archived as .csv files. PMU event data contain data from phasor measurement units around times of major frequency events that occurred within the Western Interconnect.

Fit Functions (.m)

  • DecayFit.m
  • FilterData.m
  • FindEventPeriod.m
  • FindMax.m
  • FitColumn.m
  • main.m

PMU Event Data (.csv)

  • Event1data.csv
  • Event2data.csv
  • Event3data.csv
  • Event4data.csv
  • Event5data.csv
  • Event6data.csv
  • Event7data.csv
  • Event8data.csv
  • Event9data.csv
  • ChiefJoBrake1Data.csv
  • ChiefJoBrake2Data.csv
  • ChiefJoBrakeData.csv


This work is marked with CC0 1.0 Universal



Persistent Identifier


DecayFit.m (1 kB)
FilterData.m (1 kB)
FindEventPeriod.m (1 kB)
FindMax.m (1 kB)
FitColumn.m (1 kB)
main.m (1 kB)
Event1data.csv (3801 kB)
Event2data.csv (3877 kB)
Event3data.csv (3864 kB)
Event4data.csv (3876 kB)
Event5data.csv (3878 kB)
Event6data.csv (3883 kB)
Event7data.csv (3873 kB)
Event8data.csv (3867 kB)
Event9data.csv (3877 kB)
Event10data.csv (3880 kB)
ChiefJoBrake1Data.csv (3879 kB)
ChiefJoBrake2Data.csv (3874 kB)
ChiefJoBrake3Data.csv (3878 kB)