1. PMU Emulator for Power System Dynamics Simulators
A. Srivastava, P. Banerjee, H. Lee,
Smart Grid Demonstration and Research Investigation Lab (SGDRIL)
Energy System Innovation center, Washington State University
Evangelos Farantatos and M. Patel
Electric Power Research Institute
Contact:
JSIS October 2017

2. Outline Introduction to PMU based model validation
Motivation and goals
Frequency based
Point of wave based
PMU Emulator interface/software
PMU Emulator Development
Modulation Test
Step Response Test
Benchmark Test of PMU Emulator
Fault case
Parameter estimation
Online small signal stability estimation
Results & Application
Summary

3. Introduction to PMU based model validation
6/27/2018
Introduction to PMU based model validation
Application of PMU measurements for model validation:
Line parameter estimation
Power Plant (Generator) Model Validation
Renewable Energy Models
SVC and STATCOM
HVDC
Load Model

4. Outline Introduction to PMU based model validation
Motivation and goals
Frequency based
Point of wave based
PMU Emulator interface/software
PMU Emulator Development
Modulation Test
Step Response Test
Benchmark Test of PMU Emulator
Fault case
Parameter estimation
Online small signal stability estimation
Results & Application
Summary

5. Motivation and goals
Phasors from Dynamic simulator and PMU cannot be compared directly due to following reasons:
• The attenuation of the digital filters in the PMU.
• The delay caused by the digital filters in the PMU.
• The length of the data window resulting averaging effect.
• Time stamping the phasors at appropriate window position.

6. Comparison of phasor output from Dynamic Simulator and PMU
Motivation and goals
PMU Emulator provide additional compensation and interface such that phasors from dynamic simulators and PMU can be compared
Comparison of phasor output from Dynamic Simulator and PMU

7. Outline Introduction to PMU based model validation
Motivation and goals
Frequency based
Point of wave based
PMU Emulator interface/software
PMU Emulator Development
Modulation Test
Step Response Test
Benchmark Test of PMU Emulator
Fault case
Parameter estimation
Online small signal stability estimation
Results & Application
Summary

8. PMU Emulator Development
Frequency based (FB) compensator for PMU Emulator
Compensating for filtering effect in frequency domain for magnitude and phase response

9. PMU Emulator Development
Point on wave based (POW) compensator for PMU Emulator
The reconstructed POW signals are multiplied with synchronously generated sine and cosine signal from a quadrature oscillator.
The two heterodyne signals are filtered using P or M class FIR filter
Transformed to polar form and time stamp at the center of the data window.
Magnitude and angle coefficients for POW mode

10. PMU Emulator Development
Error Metric
Phasors from the PMU are considered as the base value and the error of the PMU Emulator is reported w.r.t the phasors obtained from PMU
Configuration I is PMU Emulator configured in FB mode
Configuration II is PMU Emulator configured in POW mode with one cycle approximation Configuration III is PMU Emulator configured in POW mode with quarter cycle approximation.

11. PMU Emulator Development
PMU Emulator interface/software

12. Outline Introduction to PMU based model validation
Motivation and goals
Frequency based
Point of wave based
PMU Emulator interface/software
PMU Emulator Development
Modulation Test
Step Response Test
Benchmark Test of PMU Emulator
Fault case
Parameter estimation
Online small signal stability estimation
Results & Application
Summary

13. Benchmark Test for PMU Emulator
Modulation Test
Errors for modulation test (15 cycle of data window and Hamming function)

14. Benchmark Test for PMU Emulator
Step Response Test: Magnitude step from 1pu to 0.6pu and phase step from 0 deg to 20 deg. The magnitude step occurs at 1s and phase step occurs at 1.4s.
Errors for modulation test (15 cycle of data window and Hamming function)

15. Outline Introduction to PMU based model validation
Motivation and goals
Frequency based
Point of wave based
PMU Emulator interface/software
PMU Emulator Development
Modulation Test
Step Response Test
Benchmark Test of PMU Emulator
Fault case
Parameter estimation
Online small signal stability estimation
Results & Application
Summary

16. Results & Application
Fault case
Generator 1
Generator 2
MVA
615
100
Inertia
5.148
0.3
Damping 2
0.1
Tdo’
7.4
3.2
Machine parameters: Two machines are used with following features. Machine 1 is very heavy as compared to Machine 2, so any disturbance in the system results in large oscillations to Machine 2 with respect to Machine 1
The fault is created at Bus 3 for 100ms and 0.1pu fault level. The system kV is 69kV, so fault impedance is 4.761ohm.
The clearing of fault results in oscillation in the system of around 2.1Hz.

17. Results & Application
Fault case
Voltage TVE for Fault scenario

18. Results & Application
Fault case
Current TVE for Fault scenario

19. Results & Application Parameter estimation
Model Parameter Estimation Framework

20. Magnitude Step response for Model Parameter Estimation
Results & Application
Parameter estimation
Gain and time constant are unknowns while other parameters are known
Magnitude Step response for Model Parameter Estimation

21. Results & Application
Parameter estimation

22. Results & Application Online small signal stability estimation
Eigenvalues shows that PMU Emulator is closer to PMU as compared to dynamic simulator

23. Outline Introduction to PMU based model validation
Motivation and goals
Frequency based
Point of wave based
PMU Emulator interface/software
PMU Emulator Development
Modulation Test
Step Response Test
Benchmark Test of PMU Emulator
Fault case
Parameter estimation
Online small signal stability estimation
Results & Application
Summary

24. 6/27/2018
Summary
The FB mode of PMU emulator linearly approximates the non-linear behavior of the PMU, while POW mode of PMU emulator mimics the non-linear behavior of the PMU.
PMU Emulator tested with modulation test case and step input test case.
The magnitude and phase response of the POW mode of PMU emulator is closer to the PMU response.
The quarter cycle approximation of POW mode PMU Emulator performs better than the one cycle approximation of POW mode for modulation test case. However, the step change test does not result in much difference of the two POW modes.
The voltage and current TVE are plotted for fault scenario. POW mode with one cycle approximation performs better than FB mode.
The improvement in model parameter estimation and online small signal stability assessment using PMU Emulator is also demonstrated.
Template C Plain-crimson-bright

25. Contact: anurag.k.srivastava@wsu.edu
6/27/2018
Contact:
Template I-Aqua curve

26. Backup Slides
Voltage Angle response for Fault scenario

27. Backup Slides
Current Angle response for Fault scenario

28. Backup Slides
Voltage Magnitude response for Fault scenario

29. Backup Slides
Current Magnitude response for Fault scenario

30. Backup Slides

31. Backup Slides
PMU Emulator USE CASES: Online small signal stability assessment
The estimation of the modes for small signal stability assessment using PMU measurements consists of following steps [*]:
• Select time interval for analyzing phasor data after the fault clearing.
• Buffer voltage phase angle and frequency of the reference bus and the target bus  for the selected time interval.
• Construct the Hankel matrix based on the measurement.
• Construct the input matrix for the control action (zero for post fault condition) and stack below the state transition matrix to form augumented matrix.
• Perform LQ decomposition of the augmented matrix.
• Select the non zeros lower right partition of the LQ decomposition
• Perform singular value decomposition of the non zeros lower right sub-matrix from previous step.
• Construct the extended observability matrix using the span of the column space of non zeros lower right sub-matrix.
• Estimate the state transition matrix from the extended observability matrix.
• Calculate the eigenvalues of the state transition matrix. The real part of the eigenvalues is the damping and imaginary part is the frequency of the particular mode.
[*] P. Chusovitin and A. Pazderin. Small-signal stability monitoring using pmu. In IEEE International Energy Conference (ENERGYCON), pages 267–272, May 2014.