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Predictive Maintenance

The stability and reliability of power delivery have always been a major concern of electrical utilities and were given higher priorities than the power losses issues. According to the World Bank report [1] dated April 2014, the average annual calculated electric power transmission and distribution losses in the world is about 8%. This annual figure represents the difference between sources of supply and points of distribution to consumers. The losses percentage span from 3% to rates as high as 55%. The divergent performances of different power grids can be explained and attributed to controllable factors and to uncontrollable factors. Some key factors are known; others are not and are constantly being investigated. Knowledge of what factors increase and decrease the power losses makes it possible to optimize the grid with respect to the power losses.

Corona is one of the known causes for power loss. Corona losses occur when there is an electric current flowing to the ground through the air. Extreme weather conditions such as rime, fog, heavy rain and wet snow can cause a significant increase of corona losses, but these are seasonal temporary conditions. On the other hand corona losses incurred as a result of known local environmental factors that enhance corona, such as humidity, contamination and exposure to salty mist in coastal areas, as well as improper installations, erroneous design, unfit components etc., can be controlled and minimized.

The stability and reliability of power delivery have always been a major concern of electrical utilities and were given higher priorities than the power losses issues. According to the World Bank report [1] dated April 2014, the average annual calculated electric power transmission and distribution losses in the world is about 8%. This annual figure represents the difference between sources of supply and points of distribution to consumers. The losses percentage span from 3% to rates as high as 55%. The divergent performances of different power grids can be explained and attributed to controllable factors and to uncontrollable factors. Some key factors are known; others are not and are constantly being investigated. Knowledge of what factors increase and decrease the power losses makes it possible to optimize the grid with respect to the power losses.

Corona is one of the known causes for power loss. Corona losses occur when there is an electric current flowing to the ground through the air. Extreme weather conditions such as rime, fog, heavy rain and wet snow can cause a significant increase of corona losses, but these are seasonal temporary conditions. On the other hand corona losses incurred as a result of known local environmental factors that enhance corona, such as humidity, contamination and exposure to salty mist in coastal areas, as well as improper installations, erroneous design, unfit components etc., can be controlled and minimized.

The reliability of today’s generation of composite insulators (NCI), manufactured in accordance with the latest technology, can only be reached, if the correct corona protection of the composite insulator is set. For a comprehensive evaluation of NCI a combination of UV method and other tools is needed. The UV method is particularly efficient in detecting conductive/semi-conductive defects that have developed on insulators (8)

According to the USA Department of Energy, California lost about 19.7 x 109kWh of electrical energy through transmission/distribution in 2008 (6). This amount of energy loss was equal to 6.8% of total amount of electricity used in the state throughout that year. At the 2008 average retail price of $0.1248/kWh, this amounts to a loss of about $2.4B worth of electricity in California, and a $24B loss nationally. It is commonly accepted among electrical utilities that resistive loss ranges between 1.9% and 2.8% over 1000km. These losses are fixed and depend on wiring configuration. Corona losses, on the other hand, range between 0.083% – 3.66% depending on power line properties & environmental factors (7). Although energy losses due to corona sum up to considerable figures, the main losses involved with corona are those resulted from its atrocious effect on the electrical elements and in particular on insulation material.

As an active ageing factor corona accelerates electrical and mechanical deterioration processes and is considered to be a major ageing factor. Corona activity creates corrosive substances, like nitrogen oxides and ozone that compromise the electrical properties of insulators. Nitric acid derivatives corrode metal end fitting and erode concrete fillings of porcelain insulators affecting the mechanical strength of these components. Corona leads to loss of hydrophobicity, and is therefore lethal to NCI. The outcome emitted ultraviolet radiation dries insulation and changes its chemical properties. The level of corona discharge may change from time to time according to humidity (increasing at higher humidity) and air temperature. However, corona problems are not problems that sort themselves out on their own. They always worsen with time. The first step to care about corona is to locate it by using a UV imager corona camera.

Electrical losses due to corona discharge and to corona related failures can be reduced to minimum through preventive and predictive maintenance scheme that makes use of combined imaging technologies, such as IR, Visible and UV.

Preventive maintenance is typically planned, based upon time and not on the actual condition of the components. Regularly prescheduled activities such as: inspection, adjustments, cleaning, lubrication, parts replacement, and repair of components are usually predefined by the manufacturers, who may have a protective self-interest at stake and a lesser regard for costs to the plant. Being arbitrary, these time-based activities can result in unnecessary even damaging maintenance. Preventive maintenance induces failures and is considered to be costly as for example is the case of overhauling a properly functioning motor generator set based on a manufacturer recommended timetable.

Predictive maintenance is based upon the actual condition of components and uses nonintrusive non-destructive testing techniques. Predictive maintenance is based upon analyzed performance data that is has been collected during visual inspections. With predictive maintenance there is no need for arbitrarily scheduled maintenance and the risk of unplanned failure is very much reduced. A major role in this kind of maintenance plays trending analysis, because it is used for planning and to establish schedules. There are various electrical monitoring techniques that are applicable to certain types of equipment or failure modes, and therefore it is most effective to combine technologies.

An optimized maintenance mix will have a sizeable impact on the cost of maintenance: breakdowns and repairs typically cost about $17-18 per installed horsepower (hp)/year, preventive costs about $11-13 per installed hp/year, and predictive maintenance costs about $7-9 per installed hp/year. Unplanned emergency maintenance takes 25% to infinity longer to do than planned and is normally done on overtime rates. The part costs and their shipping rates are higher. The waiting time for replacement parts to arrive, the contractor’s urgent labor fees, specialty equipment to arrive on site; wasted hours due to the staging of parts and equipment in an emergency or unplanned work situation; overtime hours involved with the emergency work; extra procurement and shipping costs for emergency parts, etc. all add up to huge costs.

 

UV imaging cameras are dedicated to pinpoint sources of corona and their value propositions have been proven as follows:

  1. Preventing outages – the cost of an outage of an overhead line is estimated to be of the order of millions dollars. Litigation costs should be also added
  2. Predicting failures – the cost of an unexpected failure of a key component can easily be $50,000 to $150,000
  3. Manage assets – the shift from time based to condition based and from routine washings to planned saves utilities extensive amount of money. An estimated yearly expenditure on substations washing was $1,000,000. This cost was substantially reduced by locating, with the DayCor® camera, the specific components that needed washing.
  4. Extending the life of mature motors/generators/transformers and other major electrical components – the outcome of predictive and preventive maintenance activities and handling faults while they are still reversible.
  5. Premium labor rates required for urgent repair
  6. Saving on spare parts costs and storage, with predictive maintenance only needed components are purchased, on time in lower rates
  7. Maintaining reliability and reputation of good service provider
  8. Ensuring quality of artisan labor after repair of rotor windings
  9. Ensuring proper use of  conductors radii
  10. Ensuring proper use of  corona rings, spacers and other components that are purchased in bulk and although individually low priced their accumulative effect is high
  11. Ensuring corona free newly designed and newly produced grid components
  12. Safety – alerting of existing compromised insulation
  13. Safety – alerting of existing sparks in enclosed dusty areas
  14. Preventing fire – mostly wooden pole fire due to arcing on the first drizzling rain following a long dry period
  15. Alerting of conductors‘ broken strands
  16. Alerting of loose pin and cup insulators
  17. Time & labor saving – with UV inspection location corona and arcing sources is instantaneous and accurate. There is no need for tedious guessing and search for corona saving is in time and manpower
  18. The early detection capability of the DayCor allows inspection of failures in the commissioning stage of new construction projects and hence allows taking corrective actions, before accepting the new project and avoids the losses due to wrong installations.
 

Corona cameras are intuitive to use and require little training to operate. Thus, untrained personnel can perform the inspection. Furthermore, available maintenance staff can easily adopt the UV inspection. Reliable and immediate data Inspection results are visually displayed in real time and recorded. The image of the corona and the emitting source provides immediate clear and unambiguous data

Summary

The stability and reliability of power delivery overlap with reducing revenue losses. It has been shown that power losses can be controlled and minimized if attention is given to reliability centered maintenance, which combines the strengths of predictive & preventive, as well as proactive and reactive maintenance practices. And above all, it is necessary to use a combination of testing technologies that act synergistically because each technology contributes its unique added value and unique information. Overlapping redundant information will have to be revaluated so that the most efficient equipment prevails. The trend towards using testing tools, such as Ofil’s corona cameras, that provide immediate clear information goes in tandem with the developing technologies and smart tools. Because, when revenue is at stakes, the best practice should prevail.


 
  1. International Energy Agency, Electric power transmission and distribution losses (% of output) (2013). URL http://wdi.worldbank.org/table/5.11 K. Sempler, S_a hoga ar forlusterna i elnaten (November 2009).
  2. URLhttp://www.nyteknik.se/popular_teknik/teknikfragan/article2656 20.ece
    S. Pandur, Lopande kostnader i forhandsregleringen – grundprinciper vid berakning (2010).
    URL 
  3. http://www.energimarknadsinspektionen.se/Documents/Forhandsreglering_el/Viktiga_dokument/Lopande_kostnader_i_forhandsregleringen_grundprinciper_vid_berakning.pdf
  4. Predictive models of current, voltage and power losses on electric transmission lines M. Bamigbola_, M. M. Aliyand K. O. Awodele z Department of Mathematics, University of Ilorin, Ilorin, Nigeria, School of Computational and Applied Mathematics, Faculty of Science, and TCSE, Faculty of Engineering and the Built Environment, University of the Witwatersrand, South Africa, Department of Electrical Engineering, University of Cape Town, Cape Town, South Africa
  5. M. Bowles,” State Electricity Profiles 2008″ US Energy Information Administration, DOE/EIA 0348(01)/2, March 2010
  6. Paul Gill, Electrical Power Equipment Maintenance And Testing, Second Edition, CRC Press2009 by Taylor & Francis Group, LLC
  7. Assessment Of Composite Insulators By Means Of Online Diagnosis , WG

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