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Embedded Implementation of Power System Monitoring Algorithms. Raymond McNamara , 09505075 Electrical Energy Systems FYP Presentation , January 2013. Introduction. Develop & implement numerous algorithms in real-time for monitoring and control of power systems. - PowerPoint PPT Presentation
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Embedded Implementation of Power System Monitoring Algorithms
Raymond McNamara, 09505075Electrical Energy Systems
FYP Presentation, January 2013
Introduction• Develop & implement numerous algorithms in
real-time for monitoring and control of power systems.
• Artificial signal generation on Matlab.• Compare filter-bank approaches with spectral
analysis approaches.(Performance and complexity)
• Port and evaluate the algorithm to a suitable real-time embedded platform.
• Develop & evaluate functionality for a suitable closed-loop control algorithm in Matlab.
• Port & evaluate closed-loop control algorithm to real-time embedded platform.
Research
• Looking at limits of class C equipment(Lighting equipment)• Accuracy of 1% replicating that of the ADE7880 Energy Meter
Reference: www.ieee.li
Harmonic Max. % of Current
n %A
2 2
3 30
5 10
7 7
9 5
11 n 39 3
Filter Bank Approach
Fast Fourier Transform method
Notch Filter
• Added to remove the peak at the first harmonic component with magnitude 1.
0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04-100
-50
0
50
Normalized Frequency ( rad/sample)
Pha
se (
degr
ees)
0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04-20
-10
0
10
Normalized Frequency ( rad/sample)
Mag
nitu
de (
dB)
Frequency Response of the Notch Filter
Transfer function for the filter:
>>freqz(Numerator Coefficients, Denominator Coefficients)
0.7 0.8 0.9 1 1.1 1.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
Real Part
Imag
inar
y P
art
Zplane Pole-Zero Diagram for the Notch Filter
0 500 1000 1500 20000
20
40
60
80
100
120
140
160
180
Number of samples
Mag
nitu
de o
f Y
(t)
FFT of signal after Notch filter and IIR filter
Second order system IIR filter(Resonator)
• Filters each harmonic separately.• Removes gain.• First 2000 samples removed due to filter
implementation. Transfer function for the filter:
0 100 200 300 400 500 6000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1Filter with gain removed
0 500 1000 1500 2000 2500 3000 3500
-50
0
50
100
150
200
250
300
350
400
450
Number of samples
Mag
nitu
de o
f Y(t)
FFT of signal after Notch filter and IIR filter
2000 4000 6000 8000 10000 12000 14000
0
100
200
300
400
500
600
Number of samples
Mag
nitu
de o
f Y
(t)
FFT of signal after Notch filter and IIR filter
2000 4000 6000 8000 10000 12000
0
100
200
300
400
500
600
700
Number of samples
Mag
nitu
de o
f Y
(t)
FFT of signal after Notch filter and IIR filter
50 Hz
1000 Hz 1950Hz
Gain removed
=1
Fast Fourier transform Method
• Zero-padding with next nearest power of 2 greater than the number of original samples ( 66536 instead of 51000).
0 500 1000 1500 2000 2500 3000 3500 4000 4500 50000
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Frequency(Hz)
Mag
nitu
de
Magnitude Frequency Response after FFT
0 500 1000 1500 2000 2500 3000 3500 4000 4500 50000
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Frequency(Hz)
Mag
nitu
de
Magnitude Frequency Response after FFT
Performance and Computational Complexity
• Assuming 5 seconds and 51000 samples. (5 x 51000) = 255,000.
• Notch & IIR Filter – 6 & 4 multiplies and 4 & 2 adds.(1 & 39 harmonics respectively) =1 (255,000x6)+39(255,000x4)mul & 1 (255,000x4) & 39(255,000x2)adds.
• Total = 41310000 + 20910000= 62,220,000.• FFT and inverse= 2(2Nlog2N) = 18,319,340• Multiplication : 4N = 1,020,000• Total = 19339340. • Saving of 68.9% with FFT
Future Plans
• Sort out Zero-padding within the FFT to make the algorithim more efficient with the DSP chip.
• Select a DSP chip that will have the capability of handling the data.
• Hopefully all going well, implement a closed control loop to monitor and adjust.
Conclusion
• For futher information about the project: http://harmonicalgorithm.wordpress.com/
• Thank you for your time and I hope you have enjoyed the presentation.
• Any Questions?