Reliable thermal modelling approaches are crucial to transformer thermal design and operation. The highest temperature in the winding, usually referred to as the hot-spot temperature, is of the greatest interest because the insulation paper at the hot-spot undergoes the severest thermal ageing, and determines the life expectancy of the transformer insulation. Therefore, the primary objective of transformer thermal design is to control the hot-spot temperature rise over the ambient temperature within certain limit. For liquid-immersed power transformers, the hot-spot temperature rise over the ambient temperature is controlled by the winding geometry, power loss distribution, liquid flow rate and liquid properties. In order to obtain universally applicable thermal modelling results, dimensional analysis is adopted in this PhD thesis to guide computational fluid dynamics (CFD) simulations for disc-type transformer windings in steady state and their experimental verification. The modelling work is split into two parts on oil forced and directed (OD) cooling modes and oil natural (ON) cooling modes. COMSOL software is used for the CFD simulation work For OD cooling modes, volumetric oil flow proportion in each horizontal cooling duct (Pfi) and pressure drop coefficient over the winding (Cpd) are found mainly controlled by the Reynolds number at the winding pass inlet (Re) and the ratio of horizontal duct height to vertical duct width. The correlations for Pfi and Cpd with the dimensionless controlling parameters are derived from CFD parametric sweeps and verified by experimental tests. The effects of different liquid types on the flow distribution and pressure drop are investigated using the correlations derived. Reverse flows at the bottom part of winding passes are shown by both CFD simulations and experimental measurements. The hot-spot factor, H, is interpreted as a dimensionless temperature at the hot-spot and the effects of operational conditions e.g. ambient temperature and loading level on H are analysed. For ON cooling modes, the flow is driven by buoyancy forces and hot-streak dynamics play a vital role in determining fluid flow and temperature distributions. The dimensionless liquid flow and temperature distributions and H are all found to be controlled by Re, Pr and Gr/Re2. An optimal design and operational regime in terms of obtaining the minimum H, is identified from CFD parametric sweeps, where the effects of buoyancy forces are balanced by the effects of inertial forces. Reverse flows are found at the top part of winding passes, opposite to the OD results. The total liquid flow rates of different liquids for the same winding geometry with the same power loss distribution in an ON cooling mode are determined and with these determined total liquid flow rates, the effects of different liquids on fluid flow and temperature distributions are investigated by CFD simulations. The CFD modelling work on disc-type transformer windings in steady state present in this PhD thesis is based on the dimensional analyses on the fluid flow and heat transfer in the windings. Therefore, the results obtained are universally applicable and of the simplest form as well. In addition, the dimensional analyses have provided insight into how the flow and temperature distribution patterns are controlled by the dimensionless controlling parameters, regardless of the transformer operational conditions and the coolant liquid types used.

Power and Generator Transformers are important and expensive elements of a power system. Inadvertent failure of Power Transformers would cause long interruption in power supply with consequent loss of reliability and revenue to the supply utilities. The mineral oil impregnated paper, OIP, is an insulation of choice in large power transformers in view of its excellent dielectric and other properties, besides being relatively inexpensive. During the normal working regime of the transformer, the insulation thereof is subjected to various stresses, the more important among them are, electrical, thermal, mechanical and chemical. Each of these stresses, appearing singly, or in combination, would lead to a time variant deterioration in the properties of insulation, called Ageing. This normal and inevitable process of degradation in the several essential properties of the insulation is irreversible, is a non-Markov physico-chemical reaction kinetic process. The speed or the rapidity of insulation deterioration is a very strong function of the magnitude of the stresses and the duration over which they acted. This is further compounded, if the stresses are in synergy. During the processes of ageing, some, or all the vital properties undergo subtle changes, more often, not in step with the duration of time over which the damage has been accumulated. Often, these changes are non monotonic, thus presenting a random or a chaotic picture and understanding the processes leading to eventual failure becomes difficult. But, there is some order in this chaos, in that, the time average of the changes over short intervals of time, seems to indicate some degree of predictability. The status of insulation at any given point in time is assessed by measuring such of those properties as are sensitive to the amount of ageing and comparing it with earlier measurements. This procedure, called the Diagnostic or nondestructive Testing, has been in vogue for some time now. Of the many parameters used as sensitive indices of the dynamics of insulation degradation, temporal changes in temperatures at different locations in the body of the transformer, more precisely, the winding hot spots (HST) and top oil temperature (TOT) are believed to give a fairly accurate indication of the rate of degradation. Further, an accurate estimation of the temperatures would enable to determine the loading limit (loadability) of power transformer. To estimate the temperature rise reasonably accurately, one has to resort to classical mathematical techniques involving formulation and solution of boundary value problem of heat conduction under carefully prescribed boundary conditions. Several complications are encountered in the development of the governing equations for the emergent heat transfer problems. The more important among them are, the inhomogeneous composition of the insulation structure and of the conductor, divergent flow patterns of the oil phase and inordinately varying thermal properties of conductor and insulation. Validation and reconfirmation of the findings of the thermal models can be made using state of the art methods, such as, Artificial Intelligence (AI) techniques, Artificial Neural Network (ANN) and Genetic Algorithm (GA). Over the years, different criteria have been prescribed for the prediction of terminal or end of life (EOL) of equipment from the standpoint of its insulation. But, thus far, no straightforward and unequivocal criterion is forth coming. Calculation of elapsed life in line with the existing methodology, given by IEEE, IEC, introduces unacceptable degrees of uncertainty. It is needless to say that, any conformal procedure proposed in the accurate prediction of EOL, has to be based on a technically feasible and economically viable consideration. A systematic study for understanding the dynamical nature of ageing in transformers in actual service is precluded for reasons very well known. Laboratory experiments on prototypes or pro-rated units fabricated based on similarity studies, are performed under controlled conditions and at accelerated stress levels to reduce experimental time. The results thereof can then be judiciously extrapolated to normal operating conditions and for full size equipment. The terms of reference of the present work are as follows; 1. Computation of TOT and HST Theoretical model based on Boundary Value Problem of Heat Conduction Application of AI Techniques 2. Experimental Investigation for estimating the Elapsed Life of transformers Based on the experimental investigation a semi-empirical expression has been developed to estimate the loss of life of power and station transformer by analyzing gas content and furfural dissolved in oil without performing off-line and destructive tests.