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LONG AND MEDIUM-TERMFORECASTING OF
O&M COSTS AND CAPITAL REPLACEMENT
IN AN ELECTRICAL UTILITY
CASE STUDY USING PRINCIPLE OF
EVIDENCE BASED ASSET MANAGEMENT
Ali Zuashkiani : Director of Educational Programs
Centre for Maintenance Optimization and Reliability Engineering
University of Toronto
THE CHALLENGE -IMPROVE ABILITY TO
FORECAST O & M IN THE MID TO LONG-TERM
PERIOD (3 TO 10 YEARS)
The Key Business Drivers for Improving:
Regulators developing Incentive Based Rate Methodologies which could set rates for
prolonged period, about 5-years (Long-term forecasts demanded by regulators and Intervener
community to provide context for decisions)
Utilities must ensure rates adequate to recover expected future costs and leverage opportunity
for improving utility earning potential if can find efficiencies within the rate period
Improve planning of utility based operational work and staffing needs in the mid to long-term
period
Key Issues:
Recent trend toward increasing Planned and Corrective O&M
Demographics indicate increasing number of end-of-life assets and improved correlations to
O&M needed
Recent trend toward increasing number of mid-life overhauls
Recent failures necessitate undertaking a one-time specific asset remedial program
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TYPES OF OVERHAULS
OverhaulType Name
Leak Reduction
Radiator Refurbishment/Paint
Transformer Dehydration
Operating Spare Equip.
Refurbishment
ULTC Refurbishment
Normal Overhaul
Major Transformer Overhaul
Midlife Refurbishment
12.
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The utility,had very limited data-(data existed only for the last
8 years)
Since there were 19 different classes of transformers, it was
not possible to estimate EOL distributions of transformers
with accuracy based on hard data only
There was no record of assets which had received overhauls.
This was crucial for building the prediction model.
CHALLENGES
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Age
0 20 4060
End of Life time
Age
0 20 40 60
End of Life time
Age
0 20 40 60
End of Life time
Distribution of end of life of
transformers based on
experts’ knowledge
Distribution of end of life of
transformers based on
available data
Distribution of end of life of
transformers based on
both experts opinion and
available data
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COMBINING TACIT KNOWLEDGE WITH HARD
DATA
