Asset Management and the Role of Power Quality on Electrical Treeing in Epoxy Resin

A thesis submitted to The University of Manchester

for the degree of Doctor of Philosophy

in the Faculty of Engineering and Physical Sciences

2009

Sanjay Bahadoorsingh

School of Electrical and Electronic Engineering

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Table of Contents List of tables ...................................................................................................................... 6 List of figures..................................................................................................................... 7 List of abbreviations ....................................................................................................... 11 List of abbreviations ....................................................................................................... 11 Abstract............................................................................................................................ 12 Declaration....................................................................................................................... 13 Copyright ......................................................................................................................... 13 Acknowledgements......................................................................................................... 14 Dedication ........................................................................................................................ 14 1. Introduction................................................................................................................ 15

1.1. Supergen V - AMPerES ....................................................................................... 15 1.2. Background .......................................................................................................... 15 1.3. An interpretation of insulation ageing................................................................... 16 1.4. Space charge ....................................................................................................... 19

1.4.1. Electroluminescence ..................................................................................... 19 1.5. Partial discharges................................................................................................. 20 1.6. Water trees........................................................................................................... 21

1.6.1. Transition from water trees to electrical trees................................................ 22 1.7. Electrical trees...................................................................................................... 23

1.7.1. Electrical tree types ....................................................................................... 24 1.7.2. Electrical tree initiation................................................................................... 25

1.8. Power quality and electrical ageing...................................................................... 26 1.8.1. The role of harmonics.................................................................................... 27 1.8.2. Modelling electrical stress with harmonic content ......................................... 30 1.8.3. Impact of harmonics on electrical ageing ...................................................... 32

1.9. Low voltage ageing .............................................................................................. 39 1.9.1. Influence of ageing factors ............................................................................ 39 1.9.2. Discussion ..................................................................................................... 42

1.10. Literature review findings ..................................................................................... 44 1.11. Asset management overview ............................................................................... 44 1.12. Asset management approaches .......................................................................... 46

1.12.1. Condition monitoring...................................................................................... 46 1.12.2. Reliability centered maintenance................................................................... 46 1.12.3. Complimentary roles of condition monitoring and reliability centered

maintenance .................................................................................................. 47 1.13. State of the art asset management ...................................................................... 48

1.13.1. General industry ............................................................................................ 48 1.13.2. Rail industry................................................................................................... 49 1.13.3. Aerospace industry........................................................................................ 51 1.13.4. Power industry............................................................................................... 52

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1.13.5. Discussion ..................................................................................................... 54 1.14. The future of asset management - PAS 55 .......................................................... 56

1.14.1. Key principles of PAS 55 ............................................................................... 56 1.14.2. PAS 55 in the energy sector .......................................................................... 57

1.15. Review of asset management .............................................................................. 58 1.16. Aims and objectives ............................................................................................. 60 1.17. Thesis structure.................................................................................................... 60

2. A multifactor framework linking insulation ageing to asset management .......... 61 2.1.1. Overview........................................................................................................ 61 2.1.2. Asset management........................................................................................ 61 2.1.3. Material state ................................................................................................. 62 2.1.4. Stress factors................................................................................................. 64 2.1.5. Ageing mechanisms ...................................................................................... 66 2.1.6. Measurands................................................................................................... 67 2.1.7. Multifactor framework .................................................................................... 69 2.1.8. Application ..................................................................................................... 72 2.1.9. Discussion ..................................................................................................... 73

3. Development of experimental method and equipment .......................................... 75 3.1. Test equipment..................................................................................................... 78

3.1.1. Waveform generation .................................................................................... 78 3.1.2. Amplification .................................................................................................. 79 3.1.3. Image capture................................................................................................ 80 3.1.4. Electroluminescence capture......................................................................... 80 3.1.5. Hardware assembly ....................................................................................... 81

3.2. Partial discharge instrumentation ......................................................................... 84 3.2.1. Design............................................................................................................ 85 3.2.2. Simulation ...................................................................................................... 86 3.2.3. Software development ................................................................................... 89

3.3. Limitations ............................................................................................................ 95 3.3.1. Sampling rate and sample size...................................................................... 95 3.3.2. Disturbances.................................................................................................. 96 3.3.3. Improvements for disturbance mitigation....................................................... 97

3.4. Disturbance reduction .......................................................................................... 98 3.4.1. Implementation of balanced circuit detection................................................. 98 3.4.2. Disturbance analysis.................................................................................... 100

3.5. System integration.............................................................................................. 102 3.6. Sample preparation ............................................................................................ 103 3.7. Assessment of partial discharge sources........................................................... 105 3.8. Experimental plan............................................................................................... 108

3.8.1. Influence of power quality on electrical tree growth and breakdown times.. 109 3.8.2. Influence of power quality on electrical treeing partial discharge patterns .. 110

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4. Experimental results and analysis......................................................................... 112 4.1. Influence of needle lubricant coating.................................................................. 112

4.1.1. Partial discharge patterns............................................................................ 113 4.1.2. Electrical tree growth ................................................................................... 115 4.1.3. Initiation and breakdown times .................................................................... 119 4.1.4. Gaseous activity .......................................................................................... 120 4.1.5. Summary ..................................................................................................... 124

4.2. Sequence of electrical tree growth..................................................................... 125 4.3. Influence of power quality on electrical tree growth and breakdown time.......... 128

4.3.1. Electrical tree growth ................................................................................... 128 4.3.2. Deductions................................................................................................... 137 4.3.3. Breakdown time........................................................................................... 137 4.3.4. Deductions................................................................................................... 146

4.4. Influence of power quality on partial discharge patterns .................................... 148 4.4.1. Partial discharge modelling ......................................................................... 151 4.4.2. The statistical evaluation of the partial discharge patterns.......................... 161 4.4.3. Visual correlation with partial discharge pattern and statistical indices ....... 167 4.4.4. Deductions................................................................................................... 174

5. Summaries and outcomes...................................................................................... 176 5.1. Asset management ............................................................................................ 176 5.2. Test facility ......................................................................................................... 177 5.3. Lubricant coating................................................................................................ 178 5.4. Direction of electrical tree growth....................................................................... 179 5.5. Power quality and electrical tree growth ............................................................ 179 5.6. Power quality and breakdown times .................................................................. 180 5.7. Power quality and partial discharge patterns ..................................................... 181

6. Major contributions ................................................................................................. 183 6.1. Achievements..................................................................................................... 183 6.2. Conclusions........................................................................................................ 183 6.3. Further work ....................................................................................................... 184

References ..................................................................................................................... 185 Appendix A – Weibull plots of breakdown times ....................................................... 194 Appendix B – Partial discharge data and tree images............................................... 196 Appendix C – List of publications................................................................................ 239

≈ 40,000 words

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List of tables Table 1-1: Electrical fields required for different electrical trees in polyethylene [46]. .....................24 Table 1-2: Categories and typical characteristics of disturbances in the power network [50]..........26 Table 1-3: Voltage distortion limits [49]. ...........................................................................................29 Table 1-4: Typical harmonic current relative to fundamental from common sources.......................30 Table 1-5: Percentage of residual insulation life during peak periods [59].......................................34 Table 1-6: Percentage of residual insulation life during the entire day [59]. ....................................34 Table 1-7: Quantitative analysis illustrating increased partial discharge activity as a

consequence of ageing with 50 Hz compared to 50 Hz + 10 % 11th harmonic [72].......36 Table 1-8: Summary of the impact of electrical stress factors on electrical ageing mechanisms. ...38 Table 3-1: Properties of the seven test waveforms. .........................................................................76 Table 3-2: AWG vertical sensitivity. ..................................................................................................79 Table 3-3: AWG horizontal resolution...............................................................................................79 Table 3-4: Power amplifier parameters. ...........................................................................................79 Table 3-5: Summary of problems, solutions & tradeoffs. .................................................................84 Table 3-6: Summary of problems, solutions & tradeoffs. .................................................................89 Table 4-1: Sample details to investigate lubricant effects. .............................................................113 Table 4-2: Interpretation of the width/length ratio. ..........................................................................116 Table 4-3: Densities of compounds. ...............................................................................................123 Table 4-4: Conclusions on the influence of the needle lubricant coating. ......................................124 Table 4-5: Breakdown results of 42 test samples...........................................................................138 Table 4-6: Graphically determined α and β values from the breakdown time data........................142 Table 4-7: Comparison of the 5th and 7th harmonic influence on breakdown time β values...........145 Table 4-8: Influence of 7th harmonic magnitude on breakdown time β values. ..............................146 Table 4-9: Variation in Weibull α and β values for breakdown times to corresponding Ks and

THD indices for each composite waveform. .................................................................147 Table 4-10: Description of samples tested. ....................................................................................148 Table 4-11: Upper quartile values for wave 7 is the lowest, while waves 12 and 11, exceed

wave 1 whose THD is significantly higher. ...................................................................167 Table 5-1: Variation in breakdown time α and β values to corresponding KS and THD (same as

Table 5-9)......................................................................................................................180

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List of figures Figure 1-1: Factors which influence insulation ageing......................................................................17 Figure 1-2: Dry ageing of polymeric insulation [8]. ...........................................................................18 Figure 1-3: Wet ageing of polymeric insulation [8]............................................................................22 Figure 1-4: Schematic representation of typical electrical tree growth [3]. .......................................23 Figure 1-5: Possible routes to electrical tree initiation [47]. ..............................................................25 Figure 1-6: Harmonic orders of 50 Hz fundamental (top) polluting the fundamental, influencing

the shape of the resultant (below)...................................................................................27 Figure 1-7: Links between power quality disturbances and electrical stress factors [65]. ................32 Figure 1-8: Influence of harmonic content on phased resolved partial discharge plots. A) Pure

test voltage B) 17 % - 3rd harmonic C) 11 % - 5th harmonic [73].....................................35 Figure 1-9: Partial discharge phase-resolved plots after 720 hours of 50 Hz ageing (left) and 50

Hz + 10 % 11th harmonic ageing (right) [72]. ..................................................................36 Figure 1-10: Simulation model (left) and experimental partial discharge activity (right)

incorporating 11 % of the 11th harmonic, showing good correlation to phase location of discharge activity [73]..................................................................................................37

Figure 1-11: Typical overvoltage propagated from MV to LV network via a transformer [90]. .........41 Figure 1-12: Induced overvoltage on the line from indirect lightning i.e. strike to ground in the

vicinity of the line [95]......................................................................................................42 Figure 1-13: Typical overvoltages at varied locations from direct lightning strike to the line [90].....42 Figure 1-14: Asset manager’s management processes - the big picture [100]. The resource,

cost and work control loops are feedback loops which influence the control loop to improve management of the physical assets..................................................................45

Figure 1-15: Asset management balance of costs, risks and performance [101].............................46 Figure 1-16: Pyramid of railway infrastructure condition monitoring highlighting the three major

contributors: maintenance policies, technologies and infrastructure [109]. ....................50 Figure 1-17: Classification of maintenance strategies [115]. ............................................................53 Figure 1-18: Scope of PAS 55 [101]. ................................................................................................57 Figure 1-19: Considerations for asset managers in a dynamically changing environment. .............59 Figure 2-1: Interaction of stress factors influencing the mechanisms of failure in context to the

asset manager’s decisions forming the asset management layer of the framework. .....62 Figure 2-2: Insulation failure flowchart. .............................................................................................63 Figure 2-3: Electrical stress factors...................................................................................................65 Figure 2-4: Ageing mechanisms are dynamic and may change in time as the material and local

stresses change [131]. ....................................................................................................67 Figure 2-5: Flow of information to the asset manager. .....................................................................69 Figure 2-6: Multifactor framework of insulation life. ..........................................................................71 Figure 2-7: Future development of the framework with defined asset management strategies

tailored to the company’s business plan. ........................................................................74 Figure 3-1: Wave 1 THD=40 % Ks=1.56. ..........................................................................................77 Figure 3-2: Wave 7 THD=0 % Ks=1.00. ............................................................................................77 Figure 3-3: Wave 8 THD=5 % Ks=1.03. ............................................................................................77 Figure 3-4: Wave 9 THD 5 % Ks=1.06. .............................................................................................77 Figure 3-5: Wave 11 THD=17.8 % Ks=1.60. .....................................................................................77 Figure 3-6: Wave 12 THD=7.85 % Ks=1.60. .....................................................................................77 Figure 3-7: Wave 13 THD=5 % Ks=1.27. ..........................................................................................78 Figure 3-8: Slew rate variation with capacitive load for the amplifier at its 20 mA limit. ...................80

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Figure 3-9: Overview of test equipment and their interfaces............................................................81 Figure 3-10: Test facility fully assembled. ........................................................................................82 Figure 3-11: Amplifier: 30 kV 20 mA.................................................................................................82 Figure 3-12: High voltage testing area (top) with close up view of the camera and sample

under test (below) ...........................................................................................................82 Figure 3-13: Schematic of high voltage test facility. .........................................................................83 Figure 3-14: Overview of partial discharge measuring system. .......................................................84 Figure 3-15: Straight detection circuit. ..............................................................................................85 Figure 3-16: Measurement instrument - amplifier filter circuit. .........................................................86 Figure 3-17: Simulation circuit in MicroCap......................................................................................86 Figure 3-18: AC response.................................................................................................................87 Figure 3-19: Transient response.......................................................................................................87 Figure 3-20: Input 50 pC calibrating pulse........................................................................................88 Figure 3-21: Output 100 pC/V discharge pulse. ...............................................................................88 Figure 3-22: Flowchart of the modules essential to the partial discharge measuring system..........89 Figure 3-23: Flowchart of modules 2 and 3 of the partial discharge instrumentation.......................90 Figure 3-24: All input data point captured.........................................................................................91 Figure 3-25: Input data points above noise threshold within 20 μs window.....................................92 Figure 3-26: Partial discharge detected at sampling rate of 10 MSps..............................................93 Figure 3-27: Flowchart of process to produce PRPD plot. ...............................................................94 Figure 3-28: Comparison of commercially available LDS 6 (left) and the in-house test facility

(right) showing good correlation of partial discharge activity from an electrical tree......95 Figure 3-29: Sampling rate of 5 MSps..............................................................................................96 Figure 3-30: Noise (magnified time scale on right plot) from energised high voltage amplifier at

output = 0 V, 100 pC/V. ..................................................................................................97 Figure 3-31: Balanced detection circuit. ...........................................................................................98 Figure 3-32: Implemented balance circuit integrated with the amplifier filter stages........................99 Figure 3-33: Noise from high voltage amplifier energised at output = 0 V, 100 pC/V from

straight circuit detection (left) and balanced circuit detection (right). .............................99 Figure 3-34: Power spectrum of FFT of sampled noise data. ........................................................100 Figure 3-35: Offset of input data points nullified at 100 pC/V (left) and 50 pC/V (right). ................101 Figure 3-36: Flowchart of hardware and software integration. .......................................................102 Figure 3-37: Sample screen shots of integrated software..............................................................103 Figure 3-38: Schematic of epoxy resin sample. .............................................................................104 Figure 3-39: Produced epoxy resin samples. .................................................................................104 Figure 3-40: Sample production rig. ...............................................................................................105 Figure 3-41: Physical setup of the sample in preparation for testing. ............................................105 Figure 3-42: Partial discharge patterns in ethylene-acrylic acid copolymer point-plane geometry

samples (gap = 10 mm, tip radius = 3 µm), from artificial channel diameter = 40 µm, length = 2 mm (plot A) and length = 1 mm (plot B) both at 4 kV, while length = 2 mm at 4.5 kV (plot C) [155, 160]..........................................................................................106

Figure 3-43: Partial discharge patterns in ethylene-acrylic acid copolymer samples at 12 kV for point-plane geometry (gap = 12 mm, tip radius = 3 µm), from electrical tree growth, after 1 min (plot A), 35 min (plot B), 2 h (plot C), 6 h (plot D), 6 h 45 min (plot E) and 6 h 55 min (plot F) [157]................................................................................................106

Figure 3-44: Influence of aquadag and lubricant coating on discharge activity. ............................107 Figure 3-45: General plan for each sample under test. ..................................................................109

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Figure 3-46: Flowchart of the experimental process to investigate the influence of power quality on partial discharge due to electrical treeing. ...............................................................110

Figure 4-1: Hypodermic needles soaked for 12 days (upper) resulted in greater lubricant retention conveyed by the glossy needle surface compared to needles soaked for 3 days (lower)...................................................................................................................112

Figure 4-2: Partial discharge activity from electrical trees of length ≤ 30 μm at 50 Hz sinusoidal reference with lubricant coating on needles (top) and without lubricant coating on needles (below).............................................................................................................114

Figure 4-3: Illustration of typical tree growth A) with lubricant and B) without lubricant. ................116 Figure 4-4: Tree growth images for T444-07-Y with lubricant coating (left) and T213-07-N

without lubricant coating (right). ....................................................................................116 Figure 4-5: Reduced electrical tree length and width measurements with lubricant coating

compared to measurements without lubricant coating. ................................................117 Figure 4-6: 3D plots showing reduced width/length ratios for samples with lubricant coating

relative to samples without lubricant coating. ...............................................................118 Figure 4-7: Scatter of initiation and breakdown times with and without lubricant coating. .............120 Figure 4-8: Illustration of gaseous activity.......................................................................................121 Figure 4-9: Gas percentage vs cycles in the electrical tree channels of polyethylene. 10 s

pause between the full cycles 50 Hz, 30 kV (gap = r mm, electrode tip radius = 5 µm) [164]. ......................................................................................................................122

Figure 4-10: Simple example with dimensions of tree channel. .....................................................123 Figure 4-11: Sequence of electrical tree growth for sample T345-09-N.........................................126 Figure 4-12: Plot of electrical tree length vs time of all samples. Inset the cluster of 2 mm tree

length (♦) and scatter of breakdown (♥) points. T325-09-N exhibits significant growth relative to all samples........................................................................................131

Figure 4-13: Normalized plot of electrical tree length vs time of all samples. Insulation gap of length = 2 mm used as reference. Lengths ≥ 2 mm registered due to branches growing upward beyond the needle tip e.g.T325-09-N.................................................132

Figure 4-14: Plot of width/length ratio vs time of all samples. Inset the cluster of 2 mm tree length (♦) and scatter of breakdown (♥) points. ............................................................133

Figure 4-15: 3D plot of width/length ratio for all samples highlighting scatter of ♦ markers. ..........134 Figure 4-16: 3D plot of width/length ratio as a function of THD for all samples..............................135 Figure 4-17: 3D plot of width/length ratio as a function of Ks for all samples. ................................136 Figure 4-18: Breakdown time vs THD illustrating the mean and standard deviation......................139 Figure 4-19: As THD increased at constant peak voltage, the variation in breakdown trends did

not reveal a deterministic relationship with THD. Lines are not for best fit or trend purposes but to assist the reader identify result groups ...............................................140

Figure 4-20: Breakdown time vs Ks illustrating the mean and standard deviation..........................140 Figure 4-21: As Ks increased at constant peak voltage, the variation in breakdown revealed a

potential region at Ks=1.27 for maximum breakdown times. Lines are not for best fit or trend purposes but to assist the reader identify result groups..................................141

Figure 4-22: Weibull plots with α and β values for the total population of tested samples, subsets of Ks=1.60, THD=5 % and undistorted waveform where Ks=1.0 & THD=0 %. ..................................................................................................................................143

Figure 4-23: The probability density and cumulative distribution function plots are similar shapes except wave 8 and wave 1 which correspond to minimum and maximum β values respectively containing the highest α values. Inset at T = 4000 s wave 9 is most influential. .............................................................................................................144

Figure 4-24: Phase-resolved partial discharge plots for sample K115. ..........................................150 Figure 4-25: Time domain representation of derivatives and electrical treeing partial discharge

activity captured from wave 7 (plot 6) and wave 13 (plot 8) from K106 for one acquisition (80 ms). .......................................................................................................151

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Figure 4-26: Changes of voltage in partial discharge (PD) source at ‘pure’ and ‘harmonic’ test voltages in a solid dielectric with a) PD source (void); t=thickness of void b) Equivalent circuit diagram (a–b–c), where Ca=capacitance of solid dielectric, Cb=capacitance of solid dielectric in series with void and Cc=capacitance of void c) PD mechanisms at ‘pure’ sinusoidal test voltage d) Effect of harmonics in test voltage on void voltage Uc and PD [73]. .......................................................................153

Figure 4-27: Wave 13 discharge pattern compared to the V and dV/dt plots from four tests. .......154 Figure 4-28: Plots of the cosh and sinh hyperbolic functions illustrating potential to model

‘dead’ zones of partial discharge activity. .....................................................................155 Figure 4-29: Normalisation of the waveform to prevent operation in the asymptotic region of the

hyperbolic functions cosh and sinh with amplitude = 1 (left) and amplitude = 10 (right).............................................................................................................................156

Figure 4-30: Improved modelling of partial discharge patterns with cosh(V+dV/dt). The dotted circles highlight improved ‘dead’ zone recognition. ......................................................157

Figure 4-31: K106 partial discharge patterns due to the composite waveforms with comparison to the cosh(V+dV/dt) model. The ‘dead’ zones highlighted by the dotted circles do not fully correlate with the recorded partial discharge activity. .....................................158

Figure 4-32: Improved ‘dead’ zone recognition highlighted by the dotted ellipses for K101 for waves 9 and 8...............................................................................................................159

Figure 4-33: Typical tree growth curve with suggested operating region for further experiments investigating electrical tree partial discharge modelling. ..............................................160

Figure 4-34: Comparison of cosh(V+dV/dt) to partial discharge activity for a triangle waveform. .160 Figure 4-35: Electrical treeing partial discharge activity due to a triangle wave illustrating the

magnitude of discharge was related to not only the instantaneous voltage [159]........161 Figure 4-36: Weibull plots of negative and positive discharges for sample K115. .........................163 Figure 4-37: Linear best fit plots of charge magnitude α and β values showing no dependence

on THD and Ks. .............................................................................................................164 Figure 4-38: Box and whisker plots of determined Weibull β values for all waveforms,

combined charge polarities as well as positive and negative charge polarities. ..........165 Figure 4-39: Box and whisker plots of determined Weibull α values for all waveforms,

combined charge polarities as well as positive and negative charge polarities. ..........166 Figure 4-40: Electrical tree growth images for K115. Each plot = 2 mins, 14.4 kV peak. ..............168 Figure 4-41: Electrical tree growth images for K104. Each plot = 4 mins, 10.8 kV peak. ..............169 Figure 4-42: Test K104 Weibull analysis of negative charges for plots 1-14 showing the

variation during plots 6, 7 and 8 as a result of the sudden tree growth, accompanied by increased magnitude partial discharge activity. .......................................................169

Figure 4-43: Graph showing the sudden change between plots 6-8 for characteristic α and β values of test K104, indicating a change in the insulation state. ..................................170

Figure 4-44: Progression of partial discharge pattern with α and β values for successive tests K112 and K113 on sample T273. Plots show change in discharge patterns suggesting change of dominant ageing mechanism and change in state of insulation.......................................................................................................................171

Figure 4-45: Visual images showing electrical tree growth for tests K112 and K113. ...................171 Figure 4-46: Weibull plots of wave 1 discharge activity for K112 and K113 illustrating the

variability due to minute changes in electrical tree growth preventing consistent plots. .............................................................................................................................172

Figure 4-47: Example of spread of Weibull plots. Waves 13 and 12 have similar scatter while the other waveforms clustered together. Relative to wave 7 (fundamental) each composite waveform has a different scatter as a result of different partial discharge patterns. ........................................................................................................................173

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List of abbreviations

AWG Arbitrary Waveform Generator BD Breakdown BSI British Standards Institute CBM Condition Based Monitoring CCD Charge Coupled Device CM Corrective Maintenance CML Customer Minutes Lost EL Electroluminescence EPR Ethylene Propylene Rubber ET Electrical Tree Growth FFT Fast Fourier Transform HV High Voltage IAM Institute of Asset Management IEC International Electrotechnical Commission IEEE Institute of Electrical & Electronic Engineers IMD-UMS Integrated Mechanical Diagnostic Health & Usage System ISO International Organization for Standardization LV Low Voltage MCM Motor Condition Monitoring MFCP Maintenance Finite Capacity Planning MI Measurement Instrument MV Medium Voltage NI National Instruments ODR Operator Driven Reliability OFGEM Office of Gas and Electricity Markets OHSAS Occupational Health & Safety Advisory Services PAS Publicly Available Specification PCI Peripheral Components Interconnect PD Partial Discharge PET Polyethylene Terephthalate PP Polypropylene PRPD Phase-resolved Partial Discharge PTFE Polytetrafluoroethylene PVC Polyvinylchloride RAMSYS Rail Asset Management Systems RCM Reliability Centered Maintenance TBM Time Based Maintenance TDD Total Demand Distortion THD Total Harmonic Distortion TIV Tree Inception Voltage TTL Transistor Transistor Logic WT Water Tree Growth XLPE Cross-linked Polyethylene

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Abstract Power network operators in developed countries are faced with the challenge of effectively managing network performance with an ageing asset population. A significant proportion of equipment is already operating well beyond design life, testifying to the success of the many insulation systems employed. Increased production of renewable and distributed energy has resulted in changes of load flows on the network, while demand-side management schemes cause variation in load demands. A steady rise in the number of power electronic devices results in reduced power quality from disturbances including harmonics. Consequently, there is a gradual change in the working environment. Hence at the plant level, insulation systems will age differently influencing electrical ageing mechanisms such as partial discharges and electrical treeing.

This research encompasses the plant level, where diagnostic data is interpreted to determine asset management decisions, at the system level. A novel structured framework has been developed linking the physics and chemistry of insulation degradation as well as the management of network power quality, to plant reliability and asset management. The development of a test facility for electrical treeing investigations, using composite waveforms uniquely consisting of six harmonic components has been described. The conducted experimental studies sought to qualitatively and quantitatively identify any distinguishing features of partial discharges and electrical tree growth characteristics, as a consequence of harmonic content impacting power quality. In power network and laboratory research the power quality dynamically varies, although this is often not monitored. In this research, the total harmonic distortion (THD) and waveshape (Ks) indices were varied to a maximum of 40 % and 1.6 respectively. Electrical trees were developed in point-plane geometry using 2 μm tip radius hypodermic needles and a 2 mm gap in epoxy resin (LY/HY 5052) samples at a constant voltage of 14.4 kV peak.

The results illustrated firstly, a return growth of the electrical tree from the ground electrode towards the needle tip after the original (downward) growth of the electrical tree (from the needle tip to the ground electrode) traversed the insulation gap. Secondly, no changes were detected in electrical tree growth characteristics due to variation of harmonic content in the excitation voltage. Thirdly, composite waveforms with increased magnitude of the 7th harmonic resulted in reduced failure times and low values of the Weibull shape parameter describing the increased scatter of these times. Penultimately, the composite waveforms influenced the partial discharge pattern produced, leading to possible misinterpretation of the dominant ageing mechanism. If this change in partial discharge activity is a result of an unmonitored change in power quality, overestimation of the insulation’s ageing state will occur resulting in inappropriate asset management decisions taken. Finally, modelling partial discharge activity due to electrical treeing with

the function cosh dVVdt

⎛ ⎞+⎜ ⎟⎝ ⎠

provided a good fit for identifying locations of partial discharge

peaks on the phase-resolved partial discharge plots and also identified periods of low discharge activity.

It is concluded that at constant peak voltage, harmonic content influences electrical ageing mechanisms and further investigation of the role of the 7th harmonic is required.

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Declaration No portion of the work referred to in the thesis has been submitted in support of an

application for another degree or qualification of this or any other university or institute of

learning.

Copyright (1) Copyright in text of this thesis rests with the Author. Copies (by any process) either in

full, or of extracts, may be made only in accordance with instructions given by the author

and lodged in the John Rylands University Library of Manchester. Details may be obtained

from the Librarian. This page must form part of any such copies made. Further copies (by

any process) of copies made in accordance with such instructions may not be made

without the permission (in writing) of the Author.

(2) The ownership of any intellectual property rights which may be described in this thesis

is vested in The University of Manchester, subject to any prior agreement to the contrary,

and may not be made available for use by third parties without the written permission of

the University, which will prescribe the terms and conditions of any such agreement.

(3) Further information on the conditions under which disclosures and exploitation may

take place is available from the Head of the School of Electrical and Electronic

Engineering.

14

Acknowledgements I would like to thank and praise the Almighty for His continued guidance and support. With

Him all things are possible and thy will be done.

I can only attempt to express my deepest gratitude to my supervisor, Dr. Simon Rowland.

His guidance, support and encouragement during my PhD study have been a beacon in

the darkest hours. Thank you Simon.

A special thank you to the EPSRC Supergen consortium for their financial support.

I would also like to extend my gratitude to the other academics in the department for their

invaluable guidance and contributions in technical discussions.

A special thank you to Bobby, Anabel, Anish and Nicole who have supported me on my

quest for excellence. Most importantly, thank you for your prayers.

Many thanks to all my colleagues at The University of Manchester who have assisted me

in various ways.

Dedication

…to my parents

Chapter 1. Introduction

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1. Introduction

1.1. Supergen V - AMPerES

Supergen V is a collaborative research partnership amongst six leading UK universities,

nine industrial partners of the electrical energy sector and the Engineering and Physical

Sciences Research Council (EPSRC). The theme of Supergen V is “Asset Management

and Performance of Energy Systems - AMPerES”. The broad aims of Supergen V include:

• To deliver intelligent diagnostic tools for plant; enabling optimum usage,

maintenance and replacement.

• To provide platform technologies for integrated network planning and asset

management.

• To investigate alternative plant and reduce environmental impact of networks.

• To develop models and recommendations for improved network operation and

management in terms of economic performance and new generation

connections.

1.2. Background

Maintaining a reliable energy supply at minimal cost is a requirement of any power

system. The challenge of this task is increasing in this era of ageing plant with a global

drive to increase the integration of renewable and distributed generation. Hence gradual

evolution of the network configuration to incorporate new generation and demand trends

result in each individual item of plant experiencing a change in its working environment

and conditions. These changes include:

• New forms of generation and changes in the load characteristics.

Consequently this will change network flows, fault currents, thermal loading of

plant equipment and voltage profiles.

• Increased usage of power electronic devices which alter the natural waveform

introducing high frequency sinusoids and pulse trains.

• Modification in scheduled maintenance procedures.

Consequently, there is a gradual change in the working environment experienced by

insulation systems. As networks undergo this evolutionary process, the insulation systems

will age differently. As an example of network evolution, we might consider a part of the

network which was previously subjected to a steady low level of loading. The network

Chapter 1. Introduction

16

equipment might be old, but not considered as aged since it has not been highly thermally

stressed. Additionally, the plant may be in a location where reliability was not critical and

so maintenance may not have been a priority. However, if that location is now part of a

wind farm connection link, there is a need for high reliability to facilitate transmission unto

the network. Therefore the plant may be highly loaded at given intervals. Consequently,

we might expect more extreme and more regular thermal excursions than previously

experienced. Similarly, connection of non-linear loads lead to increased network harmonic

content and reduced power quality, not experienced previously. Harmonics can potentially

result in significant changes of the time-domain features of the power frequency waveform

i.e. from a pure sinusoidal to a non-sinusoidal (distorted) waveform. This will increase

electrical and thermal ageing of the insulation. Intrinsic contaminants, imperfections,

protrusions and voids remain in these insulation systems and will continue to play a major

role influencing ageing and failure mechanisms. Thus to improve the interpretation of

captured diagnostic data, increased understanding of dielectric ageing under such non-

power frequency conditions is required.

This rapid metamorphosis of the power system network illustrates that there are some key

issues relating to asset management which must be fully understood to efficiently manage

the network’s ageing assets. There is therefore a need to link performance of individual

items of plant to system performance addressing the diagnostic needs of the network

operators, equipment suppliers and service companies.

1.3. An interpretation of insulation ageing

Champion et al. [1] defined ageing as the reflection of the chemical and physical changes,

in electrical materials or electrical systems resulting from stresses with the passage of

time. However, ageing is much more complex and Figure 1-1 offers a more detailed

perspective. Figure 1-1 is by no means exhaustive but provides a good platform to

appreciate and improve comprehension of the multifactor nature of insulation ageing.

Chapter 1. Introduction

17

INSULATION BREAKDOWN

UltravioletHumidityIonizing

RadiationOxidation

Gases Chemicals

CHEMICAL

TimeEnvironment

Usage

PHYSICAL

accelerate with electric field

accelerate with electric field

Joule HeatingDielectric Heating

Eddy CurrentsTemp Cycling

Temp Gradient

THERMAL

Voltage AC, DCImpulsesPolarity

FrequencyCurrent

ELECTRICAL

Tensile StressCompressive

StressVibrationBendingTorsion

MECHANICAL

Figure 1-1: Factors which influence insulation ageing.

Physical ageing is affected by all the other ageing types either directly or indirectly.

Physical and chemical ageing exist without an electric field but application of an electric

field accelerates the degradation process. Additionally, both are influenced by

environmental factors but Bonten et al. [2] identified that for polymers, physical ageing

mechanisms were reversible (as long as physical rupture has not occurred) in contrast to

chemical ageing mechanisms which irreversibly modify the polymer structure. Physical

ageing affected the molecular arrangement of the polymer structure and its inter-

molecular forces [2] as a result of the inability of polymer chain bonds to return to their

equilibrium position after thermal or mechanical stress [3]. Chemical ageing is primarily

due to oxidation and molecular bond breakage through events (some outlined in Figure

1-1) liberating electrons and ions. Fundamentally, chemical ageing may either enhance

the electric field or cause a reduction in the breakdown strength [3]. Thermal ageing, often

a by-product of electrical stress leads to physical ageing changing the insulation’s

microscopic structure influencing its chemical stability [3, 4]. Mechanical ageing is

influenced by mechanical stress which may have resulted during the manufacturing and

transportation phases of the insulation system and even whilst in operation from

electrodynamics and thermal forces [5]. Mechanical ageing significantly influences

physical ageing and may accelerate electrical ageing. Compressive stress results in

breakage of bonds which generate defects in the insulation whereas tensile stress results

in crack initiation and growth allowing molecular chains to rotate, translate, unfold and

disentangle [3]. Thus mechanical stresses aid crack propagation allowing space charge

Chapter 1. Introduction

18

deposition. Consequently the crack may lengthen leading to mechanical failure and or

partial discharge activity leading to electrical tree formation and eventually breakdown.

The main degradation mechanisms of electrical ageing in solid polymeric insulation are:

• Space charge accumulation

• Partial discharge (PD)

• Water tree growth (WT)

• Electrical tree growth (ET)

Partial discharges and water trees may be predecessors for electrical trees as seen in

Figure 1-2. Partial discharge activity is one of the most prominent indicators of defects and

on-going degradation processes in electrical insulation systems, thus is it the primary

online and offline diagnostic tool employed [6, 7]. A significant degree of research has

already been conducted to identify factors affecting the degradation mechanisms listed

above in many insulation systems and environmental conditions [8]. One example in

Figure 1-2 illustrates dry ageing in polymeric insulation and highlights intrinsic and

extrinsic ageing. Intrinsic ageing is defined as irreversible changes of the fundamental

material properties in an insulation system caused by ageing factors. Conversely, extrinsic

ageing is a source of irreversible changes of insulation properties stemming from the

ageing factors acting on imperfections in the insulation system [5].

Figure 1-2: Dry ageing of polymeric insulation [8].

Chapter 1. Introduction

19

1.4. Space charge

Space charge is the net difference between positive and negative charge (electrons,

protons, ions) present in a dielectric. The presence of space charge, enhances or reduces

the local electric field [9-11], influencing partial discharge activity, electrical tree growth

and thus eventual failure of the insulation system. Polymeric insulation systems contain

micro-voids produced during the manufacturing process [12]. The differences in the

permittivity of the air and the polymer will enhance the field in the void but an initiating

electron is required to start partial discharge activity. Space charge is injected from the

surface of the electrode into the insulation [13] and the charges gain energy from the

applied field and lose it through collisions with the polymer [8]. Hence, the initiating

electron is transported through the insulation by the conduction process and is trapped as

space charge at the polymer-void interface [12]. Once the critical electric field at the

interface is exceeded, these charges are injected into the void, accelerated by the electric

field and ionize gas molecules giving rise to hot-electron avalanches. These collisions

cause damage to the lattice and accumulate on the opposite end of the void-polymer

interface depositing electrons and positive ions on the cavity walls. This repetitive process

leads to the formation of voids and growing pits in the polymer leading to electrical treeing

[12]. Significant research has confirmed that space charge injection has been observed at

field magnitudes in the range of one-fifth to one-third the magnitudes required for

breakdown in homogenous dielectrics and one-tenth the magnitude for inhomogeneous

dielectrics [14]. This confirms that the space charge can influence electrical ageing at

comparable rated voltages. In polyethylene the critical field for space charge injection is ≈

100 kV/mm [14, 15] while for tree initiation it is 500 - 700 kV/mm. In epoxy resins the

critical field space charge injection ≈ 300 kV/mm [14]. Indirect evidence for space charge

is quantified by the intensity of electroluminescence activity [8].

1.4.1. Electroluminescence

The presence of space charge has also been associated with the occurrence of

electroluminescence (EL). EL occurs prior to partial discharge inception in polymeric

insulation at high voltage and there is no measurable degradation of the polymer below

EL inception voltages [16, 17]. EL represents one of the few measurable quantities that

accompanies the electrical tree initiation process and electrical ageing [10, 18, 19].

Dissado et al. [20] described a model involving bipolar injection, trapping and

recombination of mobile and trapped charges [8, 21]. The explanation highlighted that on

one half cycle of a waveform, mobile injected charge recombines with trapped charge of

Chapter 1. Introduction

20

opposite polarity, thereby reducing their concentration and producing a pulse of EL. The

remaining space charge is trapped resulting in an accumulation of space charge of the

same polarity as the injecting electrode (homocharge) reducing the local electric field. In

the following half cycle the same processes occur again leading to EL and a polarity

reversal of the space charge [20]. No field threshold is necessary for recombination to

occur, only bipolar injection and trapped charges are required.

Ignoring space charge effects, the applied fields necessary for electroluminescence in

epoxy resins are in the range 200 - 800 kV/mm [22]. EL pulses were identified by 2 ns rise

and fall times with 10 ns pulse widths. As the voltage increased there was a noticeable

shift of activity toward shorter wavelengths [22]. EL activity was captured over the entire

visible light spectrum with the maximum activity occurring at ≈ 500 nm [22, 23]. Evidence

suggested EL emission occurred within the ultraviolet spectrum beyond 300 nm albeit self

absorption in the material occurred [23], resulting in a total bandwidth of 375 - 725 nm for

epoxy [22] and 300 - 600 nm for cross-linked polyethylene (XLPE) [24]. The energy of EL

photons can be responsible for breaking chemical bonds [20] and inducing chemical

damage of the dielectric [10]. The ultraviolet radiation can cause photo dissociation,

photochemical reactions and charge transfers which create free radicals, promote bond

scissions and it is thought creates a micro cavity in which partial discharges can occur and

lead to electrical treeing [18].

1.5. Partial discharges

A partial discharge can be defined as localized electrical discharge that only partially

bridges the insulation between conductors. It may or may not occur adjacent to a

conductor [25]. Partial discharges can be categorized as a symptom and a mechanism

associated with insulation degradation [7]. Partial discharge activity can occur at operating

voltages in electrical trees, voids, cuts, cracks and at fillers or contaminants with poor

adhesion to the polymer and delaminating sites at interfaces of the insulation [26]. Partial

discharges are, in general, a consequence of local electrical stress concentrations in the

insulation due to voids, contaminants, protrusions and defects on the surface of the

insulation. Voids may form as a consequence of electrostrictive forces due to the applied

field and by electrochemical effects such as water treeing [3]. Partial discharges can be

described by pulses with rise-times as short as 1 ns [27] and are often accompanied by

emissions of sound, light and heat as well as chemical reactions [25]. The magnitude of

partial discharges is proportional to the size of the degradation site. The frequency of

discharges is an indication of the number of degraded sites in the insulation system. Other

Chapter 1. Introduction

21

parameters such as the phase relation and applied voltage magnitude compliment such

information to provide more accurate estimates about the nature and extent of partial

discharge activity taking place in the insulation system [28].

Partial discharge patterns served as unique signatures to identify sources of defects and

ageing states of insulation systems, with the aid of artificial intelligent techniques [7, 29-

37]. Hence, provided adequate data parameters describing the partial discharge patterns

are available, identification of an existing defect such as a void or an electrical tree is

possible [26, 38]. Partial discharge activity in voids will either increase the conductivity of

the void walls, extinguishing discharge activity, or erode the walls forming pits eventually

leading to the inception of electrical trees [26].

1.6. Water trees

A water tree is a propagating dendritic pattern of water-filled voids which over time

increases in length [39]. Water trees consist of strings of hydrophilic micro voids (which

were originally hydrophobic before a chemical change such as oxidation occurred), of the

order of 1 µm diameter filled with water [40]. Water trees have been present in a variety of

polymer based insulation systems and have been a major mechanism of in-service cable

failures over an extended period of time. These water trees can be classified as:

• Vented trees have a stem joining them to the surface of the insulation and are

therefore in direct contact with a reservoir of aqueous electrolyte [3].

• Bow-tie trees which originate from a contaminant, boundary surface or water

filled void within the insulation where there is limited access to an aqueous

reservoir [3].

Water trees occur at much lower fields than those required for electrical trees. Fothergill et

al. [40] highlighted that the water tree inception rate was more dependant on the electric

field than the applied voltage. The conditions for water tree manifestation must be

conducive and include factors such as pH, type and concentration of the electrolyte [40].

Densley et al. [8] reviewed polymeric insulation in wet environmental conditions as

depicted in Figure 1-3. Under wet conditions, the degree of moisture influencing the

insulation system is quite significant and the voids are likely to be filled if not partially filled.

These voids suppress discharges but become initiation sites for bow-tie trees [8].

Chapter 1. Introduction

22

Figure 1-3: Wet ageing of polymeric insulation [8].

While water trees represent one form of polymeric insulation degradation, water trees can

cross the insulation without causing insulation failure but can also initiate an electrical tree

[3].

1.6.1. Transition from water trees to electrical trees

Boggs et al. proposed a mechanism for the conversion of water trees to electrical trees

under impulse conditions by the electro-thermo-mechanical phenomena [41]. Boggs et al.

postulated that the impulse voltage induced a transient current causing the water in the

tree channel to boil, creating a void which supports partial discharge activity and

eventually electrical tree initiation [41]. This study revealed that water trees did not cause

failure of in-service XLPE cables, instead electrical trees were initiated from water trees as

a result of lightning surges. This explained the frequent failure of cables after torrential

rain and lightning [41]. Densley et al. contributed by highlighting that significant oxidation

may occur in water trees at high temperatures leading to an increase in water absorption,

higher conductivity and eventual thermal runaway [8]. The main cause for this transition

seems to be temperature, and if the degree of thermal exposure is reduced the transition

time to an electrical tree will be lengthened. This argument is quite consistent with the

mechanism Boggs et al. [41] discussed resulting in the time frame for such a transition

having a large spread.

Chapter 1. Introduction

23

1.7. Electrical trees

An electrical tree is a path of damage incurred by polymeric insulation as a consequence

of electrical stress and resembles the shadow of a tree [42]. Electrical trees are easily

initiated at sites of defects and once initiated can develop over a period of time to bridge

the insulation and eventually cause failure [43]. Electrical trees can also initiate from

eroded surfaces in a void, water trees and also stress enhancements without voids [26].

Electrical trees are composed of micrometre (µm) diameter and length hollow channels

[3].

Figure 1-4 outlines three distinct stages of electrical tree growth. The inception stage is

characterized by a finite inception time, the propagation stage exhibits a decelerating

growth rate (similar to water trees) which then accelerates leading into the runaway stage

before breakdown. During the propagation stage, extension of the tree channels occur

with the main channels expanding into diameters > 10 μm, discharges ≈ 100 pC

accompanied by increased acoustic and light emissions [3].

Figure 1-4: Schematic representation of typical electrical tree growth [3].

Auckland et al. [44] explained that tree growth was controlled by the number of discharges

and the residual charges in existing tubules (fine channels). The residual charges in their

respective tubules prevented further discharges in that tubule forcing new tubules to be

formed [44]. The light intensity emitted by partial discharges is ≈ 100 times more intense

than that from EL and by monitoring the light radiation from the sample, the transition from

tree initiation to tree growth is readily identified [22]. Increased temperature decreases the

Chapter 1. Introduction

24

inception time of an electrical tree and increases the tree growth rate. In the runaway

stage the leading channels are typical channels of the inception stage i.e. very thin, < 3

µm and magnitude discharges < 5 pC [3].

1.7.1. Electrical tree types

Dissado et al. classified electrical trees into 3 types [3]:

• A branch tree which has multiple branched structures with channel diameters

of the order of tens of microns (≈ 30 μm) in the main channel (trunk) to one

micron (≈ 1 μm) in the channel tips (branches) [3].

• A bushy tree where the tubules are densely packed [3].

• A bush-branch tree which is primarily a bush tree with one or more branches

projecting [3].

Jiang et al. [45] explained that branch tree channels were semiconducting and discharges

occur near the tips of the branches, distorting the electric field and reducing the likelihood

of branch formation along the tree channel. Conversely bushy tree channels cannot be

conducting since one channel would effectively short the field required to produce

discharge in other channels [45]. Jiang et al. continued to suggest that the channels are

probably full of surface charge resulting in a wildly distorted field pattern within the bush

tree thus giving rise to the random directions of the tree channel [45]. An increase in the

applied field results in a transition from branched tree to bushy tree to bush-branched tree

as illustrated in Table 1-1 [46]. This was confirmed by Jiang et al. [45] and Guastavino et

al. [38] who provided evidence confirming that branch like tree growth resulted in faster

breakdown than bushy type tree growth.

Table 1-1: Electrical fields required for different electrical trees in polyethylene [46].

Tree Type Field Magnitude (kV/mm)

Branch < 540

Bushy 540 - 600

Bush-Branch > 600

Chapter 1. Introduction

25

1.7.2. Electrical tree initiation

The incubation period as seen in Figure 1-5 is defined as the time required for tree

initiation from the time the voltage is applied [47]. This can be defined as the time for a

tree length of 10 μm to be formed [3]. Dissado et al. [3] defined the onset of tree inception

prior to a visible tree channel when 0.04 - 0.30 pC discharges are detected. In addition to

the space charge mechanisms which initiate an electrical tree, Noto et al. [46] also

attributed dielectric heating as a source of void generation and Maxwell stress as initiating

cracking around the needle tip. The resultant dielectric field would be reduced resulting in

partial discharges. Shimizu et al. [13] outlined two possibilities for tree initiation; long term

leading to gas filled cavities or short term leading to local field enhancements. Long term

tree initiation times (>> 1 s) under low voltage results in void formation. This is the

consequence of a cumulative degradation process which generally has been observed for

AC stresses, although similar processes can operate under repetitive pulsed voltages.

Tree initiation within a short time (< 1 s) under high voltages occurs under impulse, DC

and AC voltage applications. Tree initiation occurs when the local field exceeds the

breakdown field leading to localized electron avalanches and local breakdown [13].

A P P L I E D V O L T A G E

Intrinsic Process

Extrinsic Process

Charge Injection & Extraction

Field Distortion Charge Accumulation

Intensified Electric Field

Electric Field Induced Ageing

Joule Heating Oxidation

Weak Channel Formation

Decrease in Breakdown Voltage

Electrostrictive Force

Small Gap Formation

Partial Discharge

Void Discharge

Pit Formation

Material Ageing due to Other Processes

Decrease in Breakdown Voltage

T R E E I N I T I A T I O N

Incu

batio

n Pe

riod

Figure 1-5: Possible routes to electrical tree initiation [47].

Chapter 1. Introduction

26

1.8. Power quality and electrical ageing

To a power engineer, power quality concerns powering and grounding of equipment to

ensure successful operation [48-50]. Transient, short or long term, as well as steady state

disturbances impact the network’s power quality. Table 1-2 provides a condensed table of

such disturbances extracted from the IEEE 1159 standard, Recommended Practice for

Monitoring Electric Power Quality [50].

Table 1-2: Categories and typical characteristics of disturbances in the power network [50].

Categories Spectral content Duration Voltage

Impulsive 0.5 ns – 0.1 ms rise ns – ms Transients

Oscillatory kHz – MHz ms – µs 0 – 8 pu

Interruption 0.5 cycles – 1 min < 0.1 pu

Sag 0.5 cycles – 1 min 0.1 – 0.9 pu Short duration

Swell 0.5 cycles – 1 min 0.1 – 1.8 pu

Interruption > 1 min 0.0 pu

Undervoltage > 1 min 0.8 – 0.9 pu Long duration

Overvoltage > 1 min 1.1 – 1.2 pu

Voltage imbalance steady state 0.5 – 2.0 %

DC offset steady state 0.0 – 0.1 %

Harmonics 1 – 100th H steady state 0.0 – 20 %

Interharmonics 0 – 6 kHz steady state 0.0 – 2.0 %

Notching steady state

Waveform distortion

Noise broadband steady state 0.0 – 1.0 %

Voltage fluctuation < 25 Hz intermittent 0.1 – 7.0 %

Power frequency < 10 s

Short duration sags and swells, as well as long duration overvoltages and undervoltages,

influence the rms, amplitude and rise-time voltage attributes. The rise-time denotes a rate

of change of voltage which the insulation experiences, e.g. under fault conditions. Swells

and overvoltages can represent increased electrothermal stressing depending on the

peak, rms and duration of such disturbances. An insulation component at a particular site

in the network can be electrically vulnerable due to weak system impedance and so suffer

from a poor quality of supply e.g. as a result of harmonics. Voltage waveform distortion

levels from harmonic phenomena and transient disturbances observed on the

transmission and distribution networks are an important problem. These non-power

Chapter 1. Introduction

27

frequency disturbances have resulted in new working environments for ageing insulation

systems.

1.8.1. The role of harmonics

The harmonic of a wave is an integer multiple of the fundamental frequency. The

fundamental is the 1st harmonic. In power engineering the fundamental frequency is 50 or

60 Hz depending on the network, realising harmonics of 100 or 120 Hz, 150 or 180

Hz…etc, shown in Figure 1-6.

0 2 4 6 8 10 12 14 16 18 20-1

-0.5

0

0.5

1

Time/ms

Mag

nitu

de/P

er U

nit

Harmonic orders

0 2 4 6 8 10 12 14 16 18 20-1

-0.5

0

0.5

1

Time/ms

Mag

nitu

de/P

er U

nit

Harmonic influence on resultant

FundamentalResultant10% 3rd Harmonic20% 5th Harmonic30% 7th Harmonic

Fundamental2nd Harmonic3rd Harmonic4th Harmonic

Figure 1-6: Harmonic orders of 50 Hz fundamental (top) polluting the fundamental, influencing the shape of the resultant (below).

On power networks there may be an unacknowledged harmonic contribution. This may

also be true for reported experimental laboratory work. It is therefore important to know

the thresholds at which power quality affects insulation ageing. Comprehending the effect

of the abnormalities in any resultant waveform experienced by the insulation is crucial to

defining which time-domain waveform features and characteristics are most influential to

insulation degradation. Only then can the crucial harmonic combinations be identified.

The sources of harmonics are non-linear loads, consuming non-sinusoidal currents, from

a sinusoidal voltage on the distribution networks. These non-sinusoidal currents are

Chapter 1. Introduction

28

harmonic currents yielding harmonic voltages across the network impedances. This

distortion of the power frequency waveform on the grid, commonly known as harmonic

pollution mainly results from the use of power electronic devices such as adjustable speed

drives, switching power supplies, inverters and other high speed switching devices [48].

Other sources of harmonics include static power converters, electric arc furnaces,

electrical equipment with magnetic cores (transformers and motors) and static var

compensators. Other disturbances originate from utility switching, fault clearing and

lightning. This distortion of the sinusoidal waveform, often leads to malfunctioning of

sensitive electronic devices, unexpected tripping of relays due to high harmonic currents,

overheating and accelerated electrothermal ageing of cables, motors and transformers,

reducing the functional life of electrical components [48, 51, 52].

Harmonics, described as a frequency-domain representation of time-domain occurrences

[53] may increase the peak, rms and rate of change of an electric field within a dielectric,

increasing dielectric losses whilst creating a temperature rise within the dielectric [48, 54].

High frequency harmonics may lead to increased Joule heating and mitigation is achieved

by derating transformers and cables [48, 49, 55, 56]. However, thermal stressing of the

dielectric still occurs. Thermal runaway of the insulation due to high harmonic currents

may be mitigated by engaging network protection. The transients introduced with

protection switching further pollute the network. For example SF6 and vacuum switchgear

produce hundreds of surges during switching operations with 300 ns rise-times and rates

of 200 - 3000 surges per second [57].

The 3rd order harmonics and the multiples of this frequency commonly known as the

triplen harmonics pose a serious threat to thermal overloading neutral cables [52]. Such

harmonic components contain a zero sequence and the vector addition of each harmonic

phase current results in a magnitude three times the fundamental in the neutral cable.

Major sources of such components include electronic ballasts, switch mode power

supplies and personal computers, all connected at low voltages [48]. The triplen

harmonics are usually filtered from propagating to higher voltage levels with the delta star

transformer [55]. Thus on the distribution networks the 3rd, 5th and 7th harmonic orders

dominate, whereas the 5th and 7th would be the most influential to power quality and

potentially to insulation system failure at increased voltage levels of transmission.

The harmonic components produced by pulse converters are governed by expression (1-

1), where n is the integer number (n = 1, 2, 3…) and p = the number of rectifiers in the

circuit.

Chapter 1. Introduction

29

1n p× ± (1-1)

Thus the characteristic 5th, 7th and higher order harmonics consistent with expression (1-1)

are produced by 6-pulse motor drives [55]. The 5th and 11th harmonic components have a

negative sequence since the motor is being driven in reverse and might induce

overheating or cause over-current protection devices to operate. The 5th harmonic

dominates [55, 58]. The advent of the more expensive 12-pulse motor drives eliminated

the 5th and 7th order harmonics but introduced the 11th and 13th harmonic components

[59]. The 23rd and 25th harmonic components are generated within HVDC transmission

links [58].

The most common measure of harmonic content on the utility side is an index expressed

as a percentage, known as total harmonic distortion (THD) in equation (1-2).

=

⎛ ⎞= ×⎜ ⎟

⎝ ⎠∑

2

2 1

(%) 100N

h

h

VTHDV

(1-2)

Where h represents the harmonic order while Vh and V1 are the rms voltages of the hth

harmonic order and fundamental respectively.

Table 1-3 specifies the voltage distortion limits outlined in the IEEE 519 standard,

Recommended Practices and Requirements for Harmonic Control in Electrical Power

Systems [49]. At local industrial sites, the maximum THD index for voltage distortion

recorded can double these limits, as reported in [60, 61].

Table 1-3: Voltage distortion limits [49].

Bus voltage Individual voltage distortion (%) Total harmonic distortion (%)

≤ 69 kV 3.0 5.0

69 kV < V < 161 kV 1.5 2.5

> 161 kV 1.0 1.5

The current distortion limits define the maximum harmonic currents the end-user loads

may inject into the network. The current distortion is dependent on the bus voltage level

and the ratio of short-circuit current to maximum fundamental load current at the point of

common coupling, collectively known as the total demand distortion (TDD) [49]. In his

Master of Science (MSc) lecture notes on Quality of Supply, Professor J.V. Milanović

provided a summary of real measurements, highlighting the magnitude ratio of the

Chapter 1. Introduction

30

harmonic currents produced by common sources relative to the fundamental, expressed

as a percentage shown in Table 1-4.

Table 1-4: Typical harmonic current relative to fundamental from common sources.

Contributing Source Harmonic Order (%)

3rd 5th 7th 11th 13th 23rd 25th Pulse Width Modulation Drive 3.9 82.8 77.5 46.3 41.2 1.5 2.5

DC Drive 1.2 33.6 1.6 8.7 1.2 2.8 1.2

Switch Mode Power Supply 65.7 37.7 12.7 5.3 2.5 0.8 0.4

Variable Speed Drive 3.9 39.7 18.9 6.8 3.8 1.8 1.7

Electronic Ballast 19.9 7.4 3.2 1.8 0.8 0.1 --

Voltage distortion can be further magnified by parallel resonances of harmonic currents in

networks employing power factor compensation capacitors [55, 62]. Harmonic filters are

employed to reduce the THD to an acceptable level at the point of common coupling, in

accordance with the IEEE 519 standard [49]. Estimates of filters cost are in the range

(USD) $ 75 - $ 250 /kVA [48].

1.8.2. Modelling electrical stress with harmonic content

Montanari et al. [63, 64] formulated three parameters to model distorted, non-sinusoidal

voltage waveforms as a consequence of harmonic content. These were:

• waveshape parameter - Ks and Kf

• peak parameter - Kp

• rms parameter - Krms

The waveshape parameters are defined in equations (1-3) and (1-4).

2 2110

N

s hh

K hω αω =

= ∑ (1-3)

2 21

N

f hh

K h α=

= ∑ (1-4)

Chapter 1. Introduction

31

Where α =1

hh

VV and h is the harmonic component number. In equation (1-3) the ratio of

ωω

1

0

is unity, since ω0 is the angular frequency of the 50 Hz waveform and ω1 is the

angular frequency of the fundamental waveform, also 50 Hz. Hence Ks = Kf will be used to

represent this parameter. Equations (1-3) and (1-4) are proportional to the rms derivative

of the waveform and thus related to its steepness [64]. Hence, the value of this index is

proportional to the distortion of the waveform.

The peak parameter is defined in equation (1-5).

=1

pp

p

VK

V (1-5)

Kp is ratio of the peak voltage of the resultant waveform Vp to the peak fundamental V1p.

The rms parameter is defined in equation (1-6).

=1

rmsrms

rms

VKV

(1-6)

Krms is ratio of the rms voltage of the resultant waveform Vrms, to the rms fundamental

V1rms.

Unity values for all three parameters represent a non-distorted sinusoidal, power

frequency waveform. Figure 1-7 is an illustration of disturbances (outer circle) and their

links to the characteristic descriptions of electrical stress factors including the parameters

outlined above (inner circle) [65].

Chapter 1. Introduction

32

Figure 1-7: Links between power quality disturbances and electrical stress factors [65].

1.8.3. Impact of harmonics on electrical ageing

Life tests conducted on polyethylene terephthalate (PET) and XLPE employing the 3rd, 5th

and 7th harmonic orders separately, confirmed that the resultant composite waveform may

increase the voltage peak and thus the likelihood of partial discharge inception [66, 67].

Therefore the phase and magnitude attributes of the harmonic orders influenced the peak

parameter (Kp) causing significant scatter of failure times. Hence, the voltage peak was

cited as the principal factor for insulation life reduction, even with constant rms voltage

[54, 62, 64, 66-69] and in the absence of partial discharge activity [64]. Montanari et al.

[64] investigated the ageing effect of non-sinusoidal voltages due to harmonic content on

XLPE and polypropylene (PP) in the absence of partial discharge activity due to ‘intrinsic’

ageing. The mathematical analysis conducted in [64] suggested the prevailing

degradation mechanism under distorted voltage was similar under sinusoidal voltages in

the absence of partial discharges. Resulting life model equations confirmed the voltage

peak parameter Kp was most detrimental to insulation life for both dielectrics. Furthermore,

the voltage waveshape parameter Ks was marginally more influential than the rms

parameter Krms especially when partial discharge activity occurred [64]. However further

investigations later confirmed the outright dominance of Ks over Krms [59].

Research previously conducted focused on the influence of Kp on insulation life, ignoring

the impact of parameters Ks and Krms [54, 69]. Despite this, life estimations were

determined for cables (XLPE, ethylene propylene rubber (EPR)), motors, transformers

Chapter 1. Introduction

33

and PP capacitors under unrealistic severe harmonic conditions of a test power system

producing significant reduction of insulation life especially for cables [54]. Mazzanti et al.

[59] identified this shortcoming and included parameters Ks and Krms. Mazzanti et al. [59]

analyzed real network data from Rome’s subway which featured two 12-pulse converters

and a 20 kV XLPE feeder and employed a reduced electrothermal life model, defined in

equation (1-7). This model assumed negligible thermal ageing, since the thermal rating of

the insulation was significantly greater than the levels of thermal stress produced [59].

p s rn n nNS S p s rmsL L K K K− − −= (1-7)

LNS and LS represent the mean insulation life under the distorted (non-sinusoidal) and

undistorted (sinusoidal) conditions respectively. The exponents np, nr, ns, are model

parameters derived from insulation specific accelerated laboratory life tests for Kp, Krms

and Ks respectively [54, 69]. LS is defined as a function composed from the inverse power

model of electrical ageing and the Arrhenius model for thermal ageing [54, 70, 71]. For

completeness LS is illustrated in equation (1-8).

[ ]00 0( / )n b B

SL L E E eθ θ− − −= (1-8)

Where E is the rms electric field, E0 is a reference field, n0 is voltage endurance coefficient

defined in [68] (coefficient magnitude proportional to voltage endurance), L0 is the lifetime

at the nominal sinusoidal voltage and reference temperature, θ is conventional thermal

stress (indicative of temperature change), b is a parameter regulating stress synergism

and B is constant proportional to the activation energy of predominant thermal

degradation (magnitude of B proportional to thermal endurance).

The results obtained from this reduced electrothermal life model (under a distorted

regime) in equation (1-7), emphasized that parameters Ks and Kp impact significantly on

insulation life reduction, with Kp dominating especially during periods of significant loading

[59]. Ks = 1.6 was the worst case, while Krms never exceeded 1.08. Mazzanti et al. [59]

then argued that during peak periods where the voltage waveform is characterized by

sudden voltage rise, there is a chance of faster activation of field-assisted ageing

processes.

Table 1-5 and Table 1-6 show the overestimates of insulation life using the distorted

model in equation (1-7), incorporating all three parameters (KP, Ks, Krms) in comparison to

Kp only. These results were expressed as a percentage of residual insulation life, relative

Chapter 1. Introduction

34

to the estimates produced using the undistorted