Outline

1. Monitoring of Active Distribution Networks in Steady State and Transient Conditions by means of accurate synchrophasors measurements Mario Paolone ÉcolePolytechniqueFédérale se Lausanne - EPFL

2. Introduction PMU requirements for power distribution network applications Proposed algorithm for the synchrophasor estimation PMU prototype based on the NI Compact Rio Application examples and experimental activities Conclusions Outline

3. Evolution of distribution networks passive  active major changes in their operational procedures; main involved aspect is the network monitoring; massive use of advanced and smarter monitoring tools that would result into faster and reliable real-time state estimation; possible use of distributed measurement of synchrophasors based on the use of phasor measurement units (PMUs). Introduction

4. In transmission networks WAMS (Wide Area Monitoring Systems) are typically based on the measurements of bus voltages synchrophasorsrealized by means of Remote Terminal Units typically synchronized by means of the Universal Time Code – Global Positioning System. Peculiar characteristics of distribution networks lower p.u.l.inductances with non-negligible R; low power flows values; high harmonic distortion levels. PMU requirements for power distribution network applications Improved accuracy of synchrophasors measurements

5. PMU requirements for power distribution network applications Total Vector Error (TVE) (**):magnitude of the difference between the theoretically true phasor and the estimated one, in per unit of the true phasor magnitude. 60 Hz Δθ (**) IEEE Standard for Synchrophasors for Power Systems, IEEE Std. C37.118, 2005

6.  synchrophasor #2  synchrophasor #1 PMU requirements for power distribution network applications Estimated phasor errors: RMS: ΔE phase: Δθ phase angle difference between phasors : δΔδ=2∙Δθ

7.  synchrophasor #2  synchrophasor #1 PMU requirements for power distribution network applications

8. Proposed algorithm for the synchrophasor estimation Structure of the developed algorithm for the synchrophasor estimation Sampling of the waveforms (voltage/current), within a GPS-PPS tagged window T (e.g. 80 ms, i.e. 4 cycles at 50 Hz), starting in correspondence of the GPS-PPS wave-front. Identification of the fundamental frequency tone within a specific frequency window Δf(i.e. f0 ± Δf). Reconstruction in time-domain of the identified fundamental frequency toneand improved estimation of the dynamic phasor amplitude, phase and frequency.

9. Proposed algorithm for the synchrophasor estimation Input signal: Discrete Fourier Transform Problems related to the identification of the fundamental frequency tone: spectral leakage effects caused by the finite length of time window T; identification of the correct frequency value that may fall between two subsequent frequency values provided by the DFT.

10. Proposed algorithm for the synchrophasor estimation Problem a: simple solution by applying a proper windowing Problem b: HP: since the number of samples N per time window T is very large (fsampling=100 kHz >> f0=50-60 Hz);  the sine function in the denominator of the Dirichlet kernel DN(ϑ) can be approximated by its argument: Also, the following approximation applies:

11. Proposed algorithm for the synchrophasor estimation These assumption led to a linear expression of GH(kΔf)that allows to express Δbin as: Where a e b are the highest and the second highest tone magnitudes in the discrete spectrum GH. Once Δbin is known, the complex amplitude of the fundamental frequency tone S1 at frequency f0 is given by: The knowledge of f0 and S1 allows to reconstruct the fundamental frequency tone in the time domain in order to improve its phase estimation.

12. Proposed algorithm for the synchrophasor estimation

13. PMU prototype basedon the NI Compact Rio

14. Application examplesand experimental activities PXI-based system for the generation of reference signals used for the experimental characterization Time-Sync accuracy ±100 ns with 13 ns standard deviation 16-bit resolution, sampling frequency: 100 MS/s, carrier frequencies with 355 nHz resolution and PXI time synchronization skew < 20 ps 18-bit resolutioninputsat 500 kS/s, analog input accuracy 980 μV over ±10 V input range (acciracy of 0.01%)

15. Application examplesand experimental activities Accuracy assessment with reference to steady-state signals (phase error) Single tone signal (50 Hz) Distorted signal (spectrum of std. EN 50160)

16. Application examplesand experimental activities Steady-state signals (single-tone and distorted) Note that the 3σ of the GPS card is ±100 ns  31.410-6 rad @ 50 Hz

17. Application examplesand experimental activities Frequency-varying signals Std.dev of the synchrophasor phase estimation with reference to 10 s frequency sweep ramp from 47 Hz to 53 Hz

18. Application examplesand experimental activities Accuracy assessment with reference to electromechanical transients Procedure: Calculation of signal waveforms (bus voltages) within the EMTP-RV environment; • analog-generation of fault transient waveforms by means of the PXI reference signal generator system. National Instruments PXI Arb 6289 cRio PMUs EMTP-RV network model

19. Application examplesand experimental activities

20. Application examplesand experimental activities Voltage phasors measured by PMU

21. Application examplesand experimental activities PMU application example (real scale) • 80 MW power plant:two aeroderivative gas turbine (GT) units and a steam turbine unit (ST) in combined cycle; • PP connected to a 132 kV substation feeding a urban medium voltage (MV) distribution network; • PP substation is linked, by means of a cable line, to the 132 kV substation that feeds 15 feeders of the local medium voltage (15 kV) distribution network and provides also the connection with the external transmission network throughout circuit breaker BR1.

22. Application examplesand experimental activities Distribution network voltage phasors angles differences during the islanding

23. Conclusions • The use of PMUs in active distribution networks requires the definition of improved performances of these devices compared to those available in the international standard (e.g. IEEE C37.118). • The developed PMU prototype allows to: • identify the fundamental frequency tone with accuracy levels adequate for distribution network applications; • obtain accuracy levels not influenced by the harmonic distortion of the analysed signals and by their time-varying characteristics.