next generation of power and energy measuring techniquesprojects.npl.co.uk/power_energy/docs/1605...
TRANSCRIPT
REPUBLIC OF SLOVENIA
MINISTRY OF HIGHER EDUCATION, SCIENCE AND TECHNOLOGYMETROLOGY INSTITUTE OF THE REPUBLIC OF SLOVENIA
EMRP 2007
Next generation of power and
energy measuring techniques
‘Power & Energy’
WP4
by Rado Lapuh, MIRS/SIQ
P. Clarkson, P. Wright, J. Hällström, U. Pogliano
22-23 March 2011, Delft
Accurate Analysis Algorithms in Support
of Power Quality
ContentContent
�Social and scientific challenge
�Existing solutions
�Project team achievements
�Improving state-of-the-art
�Applications, impact & benefit
�Social and scientific challenge
�Existing solutions
�Project team achievements
�Improving state-of-the-art
�Applications, impact & benefit
Social and scientific challenge
Social and scientific challenge
IssuesIssues
�Power losses
�EMI, RFI
�Billing
�Stability
�Power losses
�EMI, RFI
�Billing
�Stability
RequirementsRequirements
�Real time
�Accuracy
�Real time
�Accuracy
Scientific challenge
Accurate measurement of ac waveformsAccurate measurement of ac waveforms
�By developing highly accurate voltage and current transducers
�By developing precision sampling devices
�By developing algorithms to accurately analyze these waveforms and determine power quality parameters
�By developing highly accurate voltage and current transducers
�By developing precision sampling devices
�By developing algorithms to accurately analyze these waveforms and determine power quality parameters
Conversion Sampling Analysis
HV, HC LV Digital Result
Algorithm’s requirementsAlgorithm’s requirements
�THD > 80%
�SNR < 60 dB
�> 2 periods
�> 100 samples
�THD > 80%
�SNR < 60 dB
�> 2 periods
�> 100 samples
Scientific challenge
-1.5
-1
-0.5
0
0.5
1
1.5
0 100 200 300 400 500
Time (samples)
No
rma
lis
ed
Vo
lta
ge
-1.5
-1
-0.5
0
0.5
1
1.5
No
rma
lis
ed
Cu
rre
nt
VoltageCurrent
UK railway power line
Algorithm’s requirementsAlgorithm’s requirements
�asynchronous operation
�noise performance at the theoretical minimum
�practically insensitive to harmonic distortions
�insensitive to power quality related disturbances
�asynchronous operation
�noise performance at the theoretical minimum
�practically insensitive to harmonic distortions
�insensitive to power quality related disturbances
Scientific challenge
Existing solutions
AlgorithmAlgorithm ProPro ConsCons
FFTFFT � fastest� fastest � not asynchronous� not asynchronous
interpolated DFTinterpolated DFT� fast� fast � sensitive to noise,
� requires longer records
� sensitive to noise,
� requires longer records
4PSF4PSF� accurate
� standardised
� accurate
� standardised� very sensitive for
harmonic distortions
� very sensitive for harmonic distortions
multi-harmonicmulti-harmonic� accurate,
� insensitive to harmonic distortions
� accurate,
� insensitive to harmonic distortions
� very slow� very slow
Project team achievements
Two (three) algorithms developedTwo (three) algorithms developed
�PSFE – Phase Sensitive Frequency Estimator (developed in SIQ)
�PSFEi – interpolated PSFE (developed in SIQ)
�TDIS – Time Domain Interpolation and Scanning (developed in NPL)
�PSFE – Phase Sensitive Frequency Estimator (developed in SIQ)
�PSFEi – interpolated PSFE (developed in SIQ)
�TDIS – Time Domain Interpolation and Scanning (developed in NPL)
Improving state-of-the-art
Frequency estimationFrequency estimation
�Algorithms typically estimate
� frequency,
� amplitude,
� phase
�Most important (and demanding) is
� frequency
�Algorithms typically estimate
� frequency,
� amplitude,
� phase
�Most important (and demanding) is
� frequency
Improving state-of-the-art
Noise performanceNoise performance
10 10010
-8
10-7
10-6
10-5
10-4
10-3
10-2
Cycles per record
RM
SE
(f)/
f (H
z/H
z)
CRLB
3pDFT
4PSF
PSFEi
TDIS
2
0 50 100 15010
-12
10-10
10-8
10-6
10-4
10-2
SNR (dB)
RM
SE
(f)
/ f
(Hz/
Hz)
CRLB
3pDFT
4PSF
PSFEi
TDIS
Improving state-of-the-art
Harmonic distortionsHarmonic distortions
0 20 40 60 80 100 120 14010
-8
10-6
10-4
10-2
THD (%)
|∆
f/f|
ma
x (H
z/H
z)
3pDFT
4PSF
PSFEi
TDIS
Improving state-of-the-art
Dips + HarmonicsDips + Harmonics
0 10 20 30 40 50 60 70 80
10-6
10-4
10-2
100
Dip depth (%)
|∆
f/f|
ma
x (H
z/H
z)
3pDFT
4PSF
PSFEi
TDIS
Improving state-of-the-art
Flicker + HarmonicsFlicker + Harmonics
1 2 3 4 5 6 710
-6
10-5
10-4
10-3
10-2
Flicker case
|∆
f/f|
ma
x (H
z/H
z)
3pDFT
4PSF
PSFEi
TDIS
(IEC 61000-4-15)
Improving state-of-the-art
Time consumptionTime consumption
�Record length: 10 000 samples
�Processor used: 2 GHz Core2Duo
�Environment: MATLAB
�Record length: 10 000 samples
�Processor used: 2 GHz Core2Duo
�Environment: MATLAB
3pDFT3pDFT
3,3 ms3,3 ms
4PSF4PSF
14 ms14 ms
PSFEPSFE
17 ms17 ms
PSFEiPSFEi
21 ms21 ms
TDISTDIS
114 ms114 ms
Improving state-of-the-art
Other comparisonsOther comparisons
�PSFE compared to 7 independent algorithms in 2009 (I2MTC). The statement for PSFE was:
Good and stable overall performance close to theoretical limits
�PSFE compared to 7 independent algorithms in 2009 (I2MTC). The statement for PSFE was:
Good and stable overall performance close to theoretical limits
Czech Technical University in Prague
University of Ljubljana
Slovenian Institute for Quality and Metrology
University of Perugia
University of Trento
Instituto de Telecomuni-cações
VrijeUniversiteitBrussel
Applications, impact & benefit
�power-quality instrumentation
�grid instrumentation
� calibration platform for emerging instrumentation
�power-quality instrumentation
�grid instrumentation
� calibration platform for emerging instrumentation
PositivePositiveApplicationsApplications
�better power related measurements
�better control over grid pullution
� key tools for Metrology for Smart Grids initiative
�better power related measurements
�better control over grid pullution
� key tools for Metrology for Smart Grids initiative
� industry
�power grid operators
�general public
� industry
�power grid operators
�general public
PositivePositiveImpactImpact
PositivePositiveBenefitBenefit
