05-07-2012, 01:22 PM
TRANSFORMER THERMAL BEHAVIOR AND AGING IN DISTRIBUTION DELIVERY SYSTEMS
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INTRODUCTION
In the “local delivery” concept of
distribution used throughout North
America, medium-voltage feeders reach
within a few hundred meters of the individual
customer loads. Distribution
transformers are widely dispersed with
each transformer serving relatively few
customers; typically one to twelve residential
customers, or often a single commercial
customer, per transformer. Thus,
the transformer loads are not very diversified
and can vary widely in magnitude
over a relatively short period of time.
TRANSFORMER THERMAL BEHAVIOR
The relationship between acceleration
of aging and temperature, as specified
in [1], is plotted in Figure 1.
When the hottest spot on the transformer
winding is at 110°C, the aging
acceleration factor (FAA) is 1.0, meaning
that the transformer ages at a rate yielding
a useful insulation life of 180,000
hours of continuous exposure to this temperature.
Every 7°C increase in temperature
yields a doubling of the rate at which
the insulation deteriorates.
Conversely, a decrease in temperature
decreases the aging rate.
Commercial and Institutional Loads
Hourly integrated demand
measurements were made on a
total of twelve loads in six categories
and four locations with
reasonably diverse climates in
the southeastern U.S. (Atlanta,
Rome, and Savannah, Georgia,
and Panama City, Florida).
CONCLUSIONS
The research described in this paper has shown that distribution
transformers can be applied to loads substantially
exceeding the transformers’ nameplate rating.
While the optimized rating of distribution transformers
serving commercial loads tends to be constrained by accumulated
insulation aging, residential transformers are more likely
to be constrained by peak temperature considerations during
very-high short-term loads. Best management of commercial
and residential transformer assets, however, cannot be achieved
using fixed maximum transformer overload factors. Optimal
sizing must also consider the characteristics of the application
including the shape of the load profile, recurrence of peak periods,
and correlation between peak load and ambient temperature.