Algorithm for Thermal Modelling and Calculation for Loss of Life and Remnant Life of Power Transformer

Shraddha Acharya, Prof. Pawan C. Tapre

Abstract


Power transformers are very vital and costliest
apparatus in electrical power network. A long lead time for
delivery and huge cost warrants for optimize usages of Power
transformer. Transformer loading, a function of current through
its winding, leads to ohmic losses in transformer wining and
enclosure. ohmic losses responsible for producing heat inside the
transformer. Heat, temperature has an adverse effect on life of
transformer insulation. Oil impregnated paper (OIP) insulation is
the sole choice as insulating medium in power transformer. Life
of the transformer which is life of OIP is a time temperature
function.
Substation engineers are often interested in keeping track of
consumed life and remnant life of transformer. Overloading of
the transformer beyond name plate rating involves risk and leads
to accelerated rating. Before taking on any call on overloading,
substation engineer needs to evaluate the impact on transformer
reliability and impact on life. At any moment allowable overload
(with additional loss of life) will depend on prevailing load
and ambient conditions. Understanding thermodynamic towards
temperature rise, mapping of temperature at various zone like
top oil, winding and winding hot-spot becomes essential. Based
on these; Loading (current) - Time temperature characteristics
can be forecasted.
In this review paper, calculations of average winding, hot-spot
temperature, acceleration factor for ageing, cumulative ageing
will be covered and will produce time-load characteristics for
long-time and short-time overloading. The calculation models
shall cover all type of cooling modes in power transformers. As
an outcome of the presented algorithm, a computer program shall
be developed to compute top-oil and hottest-spot temperatures as
a function of time and load, the allowable limit for overload that
can be impressed on a transformer to meet specified limitations
with loss of life. Based on calculations models, computer program
can forecast loading (current) - time temperature characteristics
(winding hot-spot temperature, ageing acceleration factor and
percentage loss of life).


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