1. Comparison of Voltage Harmonic Identification Methods for Single- Phase and Three-Phase Systems R. Alcaraz, E.J. Bueno, S. Cóbreces, F.J. Rodríguez, C.Girón, F. Huerta Department of Electronics. University of Alcalá (Spain) raul.alcaraz@uclm.es emilio@depeca.uah.es IECON 2006 University of AlcaláDepartment of Electronics Researching group in Electronic Engineering applied to the Renewable Energies M. Liserre Department of Electrical and Electronics Engineering Polytechnic of Bari (Italy) liserre@ieee.org

2. Contents 1.Introduction 2.Objectives 3.Single-Phase algorithms 4.Three-Phase algorithms 5.Experimental setup 6.Experimental results 7.Conclusions Department of Electronics IECON 2006 Researching group in Electronic Engineering applied to the Renewable Energies University of Alcalá

3. Contents 1.Introduction 2.Objectives 3.Single-Phase algorithms 4.Three-Phase algorithms 5.Experimental setup 6.Experimental results 7.Conclusions Department of Electronics IECON 2006 Researching group in Electronic Engineering applied to the Renewable Energies University of Alcalá

4. Introduction Department of Electronics Nonlinear loads Problem Harmonic Voltage distorsion Increased losses and heating Missoperation of protective equipment Solutions Passive filtersActive filters (AF) Isolated harmonic voltage Specific frequency Operation not limited to a certain load Resonances Inject the undesired harmonic with 180º phase shift More difficult implementation More expensive IECON 2006 Researching group in Electronic Engineering applied to the Renewable Energies University of Alcalá

5. Introduction Department of Electronics Active Filter Harmonic identification (voltage or current) Synchronization Voltage Current Identification methods Based on frequency-domain: Discrete Fourier Transform (DFT) Fast Fourier Transform (FFT) Based on system model: Kalman Filter Based on transformations of frames IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies Single-phase systems Three-phase systems

6. Contents 1.Introduction 2.Objectives 3.Single-Phase algorithms 4.Three-Phase algorithms 5.Experimental setup 6.Experimental results 7.Conclusions Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

7. Objectives Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies pulses PWM generator u DC controller Current Controller Grid voltage meas. ADC & SPLL L Harmonic identification Grid current meas. n PCC Harmonic compensation u DC C DC u DC meas. To obtain the exact information of the amplitude and phase of each harmonic. To rebuilt exactly each harmonic. Application: Active filters, feedforward of current controller for power converters.

8. Contents 1.Introduction 2.Objectives 3.Single-Phase algorithms –Detection based on DFT –Detection based on Wavelet –Detection based on Kalman Filter –Detection based on correlators in quadrature 4.Three-Phase algorithms 5.Experimental setup 6.Experimental results 7.Conclusions Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

9. Detection method based on DFT Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies c = 1 for positive seq. and -1 for negative seq. θ(k) =ω1k-π/2 is the sPLLoutput. γ is the sPLL delay The DFT of N 1 points is carried out for each sample that arrives from the grid voltage signal. The actual sample and N 1 -1 previous samples are used, and for this reason the buffer N 1 samples is necessary. As the phase changes from one sample to the following sample, it is necessary the use of a Phase Loocked Loop (PLL), which recovers the instantaneous phase of the grid signal.

10. DFT: Experimental setup Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies Perfect identification. In the worst cases, the response time is 2T 1 =40ms. Correct operation under unbalanced grid voltages. Run time depends on the identified harmonics, aprox. 120  s.

11. Wavelet Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies Multiresolution algorithms 5 levels Identification system (with family Daubechies40) The Wavelet algorithm transforms the signal under investigation into another one that includes frequency and time domain informations.

12. Wavelet: Simulation results Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies Non-correct identification. Only it is possible to recover correctly the harmonics 1 and 5.

13. Kalman Filter Department of Electronics Characteristics –Optimal and robust estimation of magnitudes of sinusoids –Ability to track time-varying parameters –Synchronization of the two control blocks in the AF State equation Measumerent equation Covarianze for w(k) and v(k) 1 st Kalman filter gain 2 nd Update estimate with harmonic measumerent z(t) 3 rd Compute error covariance 4 th Project ahead IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

14. Kalman Filter: Continuous model Department of Electronics State equation Measumerent equation State equationMeasumerent equation Constant B(k) x 1 (t) and x 2 (t) complementary x 2 (t) leads x 1 (t) 180º Constant A(k) IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

15. Kalman Filter: Discrete model with variable reference Department of Electronics s(k)= E(k)cos(ω 1 k+Φ(k)) = E(k)·cos(Φ(k))·cos(ω 1 k) - E(k)·sin(Φ(k))·sin(ω 1 k) x 1 (k)= E(k)·cos(Φ(k)) x 2 (k)= E(k)·sin(Φ(k)) In-phase component Quadrature-phase component State equation ω(k) time variation Measumerent equation v(k) high frequency noise Noise-free voltage signal s(k) (n harmonics) E i (k) and Φ i (k) amplitude of the phasor and phase of the i th harmonic n harmonic order State equation Measumerent equation B(k) time-varying vector IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

16. Kalman Filter: Discrete model with stationary reference Department of Electronics s(k)= E(k)cos(ω 1 k+Φ(k)) x 1 (k)= E(k)·cos(ω 1 k + Φ(k)) x 2 (k)= E(k)·sin(ω 1 k + Φ(k)) State equation ω(k) time variation Measumerent equation v(k) high frequency noise State equationMeasumerent equation Constant B(k) At k+1 s(k+1)=E(k+1)·cos(ω 1 k+ ω 1 +Φ(k+1))= x 1 (k+1)= x 1 (k)cos(ω 1 ) – x 2 (k)sin(ω 1 ) x 2 (k+1)= E(k+1)·sin(ω 1 k+ ω 1 +Φ(k+1))= x 2 (k+1)= x 1 (k)sin(ω1) + x 1 (k)cos(ω1) Constant A(k) IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

17. Kalman Filter: Identification Systems Department of Electronics Identification block Stationary referenceVariable reference and SPLL IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

18. Kalman Filter: Identification Systems Department of Electronics Variable reference and SPLL B(k) depends on w 1 k! Solution: SPLL High peak voltages during transitory by the grid disturbances! Variable reference and Time shift IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

19. Kalman Filter: Identification Systems Department of Electronics Variable reference and Time shift k = k 1 + k 2 k 2  delay between grid starts up and identification system is connected to the grid s(k)= E(k)cos(ω 1 k+ω 1 k 2 +Φ(k)) x 1 (k)= E(k)·cos(Φ M (k)) x 2 (k)= E(k)·sin(Φ M (k)) Φ 1 (k)=Φ M (k) IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

20. Kalman Filter: Experimental Results Department of Electronics CONTINUOUSDISCRETE MODEL STATIONARY REFERENCE DISCRETE MODEL VARIABLE REFERENCE IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies Selection of Kalman filter parameters

21. Correlators in quadrature Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies To make the system faster and simpler, the correlators in quadrature will be implemented by means of adapted filters,which are characterized to have an impulsive response h(k) =s(N 1 -k), being s(k) the signal that the corresponding correlator uses in the detection. Therefore, the impulsive responses of the used filters to identify the harmonic n are:

22. Contents Department of Electronics 1.Introduction 2.Objectives 3.Single-Phase algorithms 4.Three-Phase algorithms Synchronous Reference Methods (SRF) Instantaneous Reactive Power Theory (IRPT) 5.Experimental setup 6.Experimental results 7.Conclusions IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

23. Synchronous Reference Method (SRF) Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies HPF

24. Instantaneous Reactive Power Theory (IRPT) Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies When the grid voltage signal is unbalanced, a non-correct harmonic identification is produced. Due to the dq-components rotating in opposite directions, the voltage and current fundamental harmonic produce a dc-component plus ac-component in the instantaneous power therefore, harmonic distortion can not be recovered with a HPFand the inverse Park Transform

25. Contents Department of Electronics 1.Introduction 2.Objectives 3.Single-Phase algorithms 4.Three-Phase algorithms 5.Experimental setup 6.Experimental results 7.Conclusions IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

26. Experimental Setup Department of Electronics DSP  TMS320C6713 with ADCs MAX1309 of 12 bits DIGILAB 2E Link Board Interface Board TMS320C6713 DSK Optical transmitters Optical receivers ADCs Relays Digital Signal Processing Acquisition card Glue logic IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

27. Contents Department of Electronics 1.Introduction 2.Objectives 3.Single-Phase algorithms 4.Three-Phase algorithms 5.Experimental setup 6.Experimental results 7.Conclusions IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

28. Experimental results: Comparison Criterions Department of Electronics Improvement Factor (IF) balanced grid unbalanced grid frequency deviations < 0.1% Transient Response Quality Related with the maximum peak level identified during a transitory due to disturbance in the grid PF=V pident /V pgrid  <15 IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies Run Time Time that algorithms takes in its execution Transient Response Time TRT Delay between a disturbance in the grid voltage and the system harmonic identification  <100 ms

29. Experimental results: Kalman Filter Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

30. Experimental results: Single-Phase Systems Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies Balanced grid voltages Unbalanced grid voltages Drift frequency 0.1Hz Transient Response Time Transient Response Quality

31. Experimental results: Three-Phase Systems Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies Balanced grid voltages Unbalanced grid voltages Drift frequency 0.1Hz Transient Response Time Transient Response Quality Run Time

32. Contents Department of Electronics 1.Introduction 2.Objectives 3.Single-Phase algorithms 4.Three-Phase algorithms 5.Experimental setup 6.Experimental results 7.Conclusions IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

33. Conclusions In the present work, an overview and comparison of different techniques for harmonics identification in single-phase and three-phase systems has been achieved. As contribution, some modifications have been made on existing methods. Also, for the case of single-phase, the method based on correlators in quadrature have been proposed for the first time. The identification technique more suitable for each situation depends the characteristics of the environment where this is used. For single-phase the identification technique, that better results obtains, is the based on FFT and sPLL, since it obtains the best factors IF, TRT and PF. On the other hand, for the three-phase systems, experimental results and simulation show that the synchronous harmonic dq-frame method (with the utilization of transformations realized in sPLL) is the best solution. This technique permits a selective filtering, obtains a correct operation with balanced, unbalanced grid signals, has an excellent dynamic response (as transient time and transient quality) and very reduced algorithm execution time. The analysis have been validated by simulations and experimental results carried out with the digital signal processor TMS320C6713. Department of Electronics IECON 2006 University of Alcalá Researching group in Electronic Engineering applied to the Renewable Energies

34. Comparison of Voltage Harmonic Identification Methods for Single- Phase and Three-Phase Systems R. Alcaraz, E.J. Bueno, S. Cóbreces, F.J. Rodríguez, C.Girón, F. Huerta Department of Electronics. University of Alcalá (Spain) raul.alcaraz@uclm.es emilio@depeca.uah.es IECON 2006 University of AlcaláDepartment of Electronics Researching group in Electronic Engineering applied to the Renewable Energies M. Liserre Department of Electrical and Electronics Engineering Polytechnic of Bari (Italy) liserre@ieee.org ACKNOWLEDGMENTS This work has been financied by the Spanish administration (ENE2005-08721-C04-01)