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Online Monitoring of Dissipation Factor Dayashankar Dubey (MTech) Suhas P. Solanki, MTech

Online Monitoring of Dissipation Factor Dayashankar Dubey (MTech) Suhas P. Solanki, MTech Guide: Prof PC Pandey EE Dept, IIT Bombay. ABSTRACT

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Online Monitoring of Dissipation Factor Dayashankar Dubey (MTech) Suhas P. Solanki, MTech

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  1. Online Monitoring of Dissipation Factor Dayashankar Dubey (MTech) Suhas P. Solanki, MTech Guide: Prof PC Pandey EE Dept, IIT Bombay

  2. ABSTRACT The insulation status in HV equipment can be monitored by dissipation factor measurement. Online monitoring of dissipation factor is based on dividing the actual power by apparent power. Sampling rate lower than the power line frequency results in aliased periodic waveforms which retain the original phase relationship, and these waveforms can be processed at a relatively low computational speed. Numerical simulation has been carried out to study the effect of quantization error with different number of bits, for finding the effect of different filters used in processing, effect of harmonics, and variation in power line frequency.

  3. INTRODUCTION • Lossy Capacitor • Dissipation factor of lossy dielectric • Loss angle = , dissipation factor = tan • Parallel model Series model

  4. Monitoring of dissipation factor ▪ Insulation deterioration → increase in  ▪ Monitoring of  or dissipation factor → safe & reliable operation of HV equipment • Online monitoring of dissipation factor ▪ HV equipment need not be removed from service ▪ Insulation deterioration between scheduled checks gets detected ▪ Monitoring under actual load & temperature conditions

  5. METHODOLOGY • Signal Acquisition

  6. METHODOLOGY(contd..) For small , cos δ ≈ 1, s9 = sin δ ≈ tan δ

  7. ERROR ANALYSIS • Assumption for theoretical analysis: • Error caused by quantization noise, • Harmonics totally eliminated by LPF • RMS error in s9: • σ =2-L√(8γ/3) • where L = no. of quantization bits • & normalized cutoff frequency γ = fc/fs • For dissipation factor: 5 – 5010-3 & 1% resolution: σ = 50 10-6

  8. IMPLEMENTATION • Project objective: Verification of the technique • Through, • Numerical Simulation • Experimental setups • For two implementations • High Sampling rate for fast updates • Low sampling rate: low cost instrumentation for low update rate (based on aliasing of periodic waveforms)

  9. IMPLEMENTATION (contd..) • High sampling rate: Numerical simulation fs = 450 sa/s,: 0.005 - 0.05, γ=10-3 (for 8-bit), γ=15.53*10-4 (for 12-bit) (without band pass filter at the input)

  10. IMPLEMENTATION (contd..) • High sampling rate: Experimental setups Low voltage setup (30 Vpp) • I/V converter & res. V-divider • Acquisition with 8-bit 2-channel DSO, 5 k record length • LPF: 1 k rect. FIR filter • For D.F. of 1 - 20  10-3, Best fit line: slope = 1.044, offset = 1.863  10-4 High voltage setup (600 V) • Cap. divider for V & shunt resistor for I sensing • Acquisition with 8-bit 2-channel DSO, 50 k record length • LPF: 10 k rect. FIR filter • For D.F. of 0.05 - 1  10-3 Best fit line: slope = 1.051, offset = 5.7  10-4

  11. IMPLEMENTATION (contd..) • Low sampling rate • Sampling with fs< fo: aliasing of periodic V and I signals with frequency f = fo- fs, retaining the original phase relationship • Advantages • Low cost data acquisition system • Distributed signal acquisition units can transmit data over a serial link to central unit for processing

  12. IMPLEMENTATION (contd..) • Low sampling rate: Numerical simulation fs = 45 sa/s, : 0.005 - 0.05, γ=10-4 (for 8-bit), γ=2.48*10-4 (for 12-bit) (without band pass filter at the input)

  13. IMPLEMENTATION (contd..) • Low sampling rate: Signal acquisition card

  14. IMPLEMENTATION (contd..) • Low sampling rate: Experimental setup

  15. EFFECT OF FREQUENCY VARIATION • High sampling rate: Numerical simulation fs = 450 sa/s,: 0.005 - 0.05, L=12bit, γ=15.53*10-3 (without band pass filter at the input)

  16. EFFECT OF FREQUENCY VARIATION (contd..) • Low sampling rate: Numerical simulation fs = 45 sa/s, : 0.005 - 0.05, γ=10-5,L= 12-bit (without band pass filter at the input)

  17. EFFECT OF HARMONICS • THD in power line is around 5% • Harmonics filtering through Band pass filter (BPF) (Using IIR Chebychev-I)

  18. EFFECT OF HARMONICS (contd..) • High sampling rate: Numerical simulation fs = 450 sa/s, : 0.005 - 0.05, L=12bit, γ=15*10-3, σ = 5e-5 • Low sampling rate: Numerical simulation fs = 45 sa/s, : 0.005 - 0.05, L= 12-bit, γ=10-5, σ = 1e-5

  19. SUMMARY AND CONCLUSIONS • Direct calculation algorithm for dissipation factor m/s verified for 0.005 - 0.05 range with resolution 1% (i.e.510-5) • Implementation using high and low sampling rates • IIR Chebychev filters for m/s insensitivity to power line drift • Band pass filter for attenuating harmonics of power line freq. • High sampling rate implementation • For detecting incipient faults during tests/charging of HV equipment • Instrumentation for m/s with high update rate (~10 s): DSP with two 12-bit simultaneous sampling ADCs • Low sampling rateimplementation • For monitoring of HV equipment under normal aging process • Instrumentation for m/s with low update rate (~10 min.): signal acquisition h/w with serial data link to central unit for pro.

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