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As a result of the deregulations in the power system networks, diverse beneficial operations have been competing to optimize their operational costs and improve the consistency of their electrical infrastructure. Having certain and comprehensive state assessment of the electrical equipment helps the assortment of the suitable maintenance plan. Hence, the insulation condition monitoring and diagnostic techniques for the reliable and economic transformers are necessary to accomplish a comprehensive and proficient transformer condition assessment.

The main intent of this paper is to develop a new prediction model for the aging assessment of power transformer insulation oil. The data pertaining to power transformer insulation oil have been already collected using 20 working power transformers of 16-20 MVA operated at various substations in Punjab, India. It includes various parameters associated with the transformer such as breakdown voltage, moisture, resistivity, tan δ, interfacial tension and flashpoint. These data are given as input for predicting the age of the insulation oil. The proposed aging assessment model deploys a hybrid classifier model by merging the neural network (NN) and deep belief network (DBN). As the main contribution of this paper, the training algorithm of both NN and DBN is replaced by the modified lion algorithm (LA) named as a randomly modified lion algorithm (RM-LA) to reduce the error difference between the predicted and actual outcomes. Finally, the comparative analysis of different prediction models with respect to error measures proves the efficiency of the proposed model.

For the Transformer 2, root mean square error (RMSE) of the developed RM-LA-NN + DBN was 83.2, 92.5, 40.4, 57.4, 93.9 and 72 per cent improved than NN + DBN, PSO, FF, CSA, PS-CSA and LA-NN + DBN, respectively. Moreover, the RMSE of the suggested RM-LA-NN + DBN was 97.4 per cent superior to DBN + NN, 96.9 per cent superior to PSO, 81.4 per cent superior to FF, 93.2 per cent superior to CSA, 49.6 per cent superior to PS-CSA and 36.6 per cent superior to LA-based NN + DBN, respectively, for the Transformer 13.

This paper presents a new model for the aging assessment of transformer insulation oil using RM-LA-based DBN + NN. This is the first work uses RM-LA-based optimization for aging assessment in power transformation insulation oil.

The purpose of this paper is to develop a numerical simulation method based on the transient upstream finite element method (FEM) and Schottky emission theory to reveal the distribution characteristics of space charge in oil-paper insulation.

The main insulation medium of the converter transformer in high voltage direct current transmission is oil-paper insulation. However, the influence of space charge is difficult to be fully considered in the insulation design and simulation of converter transformers. To reveal the influence characteristics of the space charge, this paper proposes a numerical simulation method based on Schottky emission theory and the transient upstream FEM. This method considers the influence of factors, such as carrier mobility, carrier recombination coefficient, trap capture coefficient and diffusion coefficient on the basis of multi-physics field coupling calculation of the electric field and fluid field.

A numerical simulation method considering multiple charge states is proposed for the space charge problem in oil-paper insulation. Meanwhile, a space charge measurement platform based on the electrostatic capacitance probe method for oil-paper insulation structure is built, and the effectiveness and accuracy of the numerical simulation method is verified.

A variety of models are calculated and analyzed by the numerical simulation method in this paper, and the distribution characteristics of the space charge and total electric field in oil-paper insulation medium with single-layer, polarity reversal of plate voltage and double-layer are obtained. The research results of this paper have the guiding significance for the engineering application of oil-paper insulation and the optimal design of converter transformer insulation.

The purpose of this paper is to present a methodology based on an optimizer linked with electric finite element method (FEM) for automating the optimized design of power transformer insulation system structures.

The proposed methodology combines two stages to obtain the optimized design of transformer insulation system structures. First, an analytical calculation is carried out with the optimizer to search a candidate solution. Then, the candidate solution is numerically checked in detail to validate its consistency. Otherwise, these two steps are iteratively repeated until the optimizer finds a candidate solution according to the objective function.

The solutions found applying the proposed methodology reduce the inter-electrode distances compared to those insulation designs referenced in the literature for the same value of safety margin.

The proposed methodology explores a wide range of insulation system structures in an automated way which is not possible to do with the classical trial-and-error approach based on personal expertise.

The purpose of this paper is to study various reliability measures like reliability, mean time to failure (MTTF) and sensitivity of transformer including different parameters of insulating oil/paper as health index.

The reliability characteristics of transformer incorporating different parameters of insulating oil as well as paper have been evaluated using Markov process incorporating Gumbel–Hougaard copula, Laplace transforms and supplementary variable technique. The parameters taken into consideration are breakdown voltage (BDV) and moisture content (MC) of both insulating oil and paper, and other parameters considered are interfacial tension (IFT), dissipation factor (DF), degree of polymerization (DOP) and furanic content (FC) for insulating oil and paper, respectively. By probability consideration and continuity influence, difference-differential equations have been obtained for the considered model.

Transition state probabilities, reliability, MTTF and sensitivity of the transformer corresponding to different parameters of insulating oil and paper have been evaluated with the help of aforementioned technique. Variations of reliability with respect to time along with the variations of MTTF and sensitivity have also been examined. Remarkable points during the study have also been pointed out.

Reliability characteristics of the transformer have been evaluated including two parameters: insulating oil and paper with the help of supplementary variable technique, considering two different types of repairs incorporating Gumbel–Hougaard family of copula unlike done earlier. Reliability, MTTF and sensitivity of transformer have been analyzed considering the parameters: BDV, MC, IFT and FC of insulating oil, and BDV, MC, DOP, DF of insulating paper.

The purpose of this paper is numerical calculation of total electric field in oil-paper insulation. Now, there is no effective method to consider the influence of space charges when calculating the total electric field distribution in the main insulation system of the valve-side winding of an ultra-high-voltage direct current converter transformer.

To calculate the total electric field in an oil-paper insulation system, a new simulation method in single-layer oil-paper insulation based on the transient upstream finite element method (TUFEM) is proposed, in which the time variable is considered. The TUFEM is used to calculate the total electric field in an oil-paper insulation system by considering the move law of space charges. The simulation method is verified by comparing the simulation results to the test data. The move law of space charges and distribution characteristics of the electric field under difference voltage values in single-layer oil-paper insulation were presented.

The results show that the TUFEM has an excellent accuracy compared with the test data. When carrier mobility is a constant, the time to reach the steady state is inversely correlated with the initial electric field intensity, and the distortion rate of the internal total electric field is positively correlated with the initial electric field intensity.

This paper provides an exploratory research on the simulation of space charge transport phenomenon in oil-paper and has guiding significance to the design of oil-paper insulation.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

This paper aims to evaluate the effect of optimal use of rooftop photovoltaic (PV) systems on improving the loss of life (LOL) of distribution transformers, reducing power losses as well as the unbalance rate of the 69-bus distribution network.

The problem is studied in three scenarios, considering different objective functions as multi-objective optimization in balanced and unbalanced operations. Meta-heuristic golden ratio optimization method (GROM) is used to determine the optimal size of the rooftop PV in the network.

The simulation results show that in all scenarios, the GROM by optimally installing the rooftop PV is significantly capable to reduce the transformer distribution loss of loss, unbalance rate and power loss as well as reduce the temperature of the oil and transformer winding. Also, the lowest %LOL, power loss and unbalance rate occurred in the second scenario for the balanced network and first scenario, respectively. In addition, the results showed that the unbalance of the network results in increased power losses and LOL of the distribution transformer.

The better capability of GROM is proved compared with the grey wolf optimization algorithm with better objective function and by achieving better values of LOL, unbalance rate and power loss. The results also showed that the %LOL, unbalance and power losses are weakened compared to without considering the PV cost but the achieved results are realistic and cost-effective.

The purpose of this paper is to report on the simulation of an on-load tap-changer (OLTC) in a power transformer. During design and test of the electrical insulation the influence of the environment on the OLTC is normally neglected. The authors investigate how large these influences are.

The environment of the OLTC is taken into account by modeling tap leads in detail as well as transformer windings. The electric fields are computed and resulting breakdown voltages are estimated by using the streamer criterion. The results are compared to the ones of an OLTC without transformer and leads.

For the investigated typical example the influence of the transformer and the tap leads on the internal OLTC insulation is small enough to neglect them during design optimization and test procedures.

New is the execution of a finite element simulation and breakdown evaluation of such a complex geometric structure as the complete system consisting of OLTC combined with tap leads and windings. Furthermore, standard design and test procedures used by OLTC manufacturers are justified.

Electrical characteristics of transformer oil (TO) have been studied during normal and thermal aging conditions. In this paper, breakdown voltage (BDV), partial discharge (PD), heat transfer results and the physical mechanisms considering the impact of varying the diameter of Al₂O₃ nanoparticles (NPs) have been investigated. Different quantities of the two sizes of Al₂O₃ were added to the oil using a two-step method to determine the positive effect of NPs on the electrical and thermal properties of TO. Finally, the physical mechanisms related to the obtained experimental results have been performed.

The implementation of nanoparticles in this paper was provided by US Research Nanomaterials, Inc., USA. The provided Al₂O₃ NPs have an average particle size of 20–80 nm and a specific surface area of 138 and 58 m²/g, respectively, which have a purity of over 99%. Thermal aging has been done. The IEC 60156 standard has been implemented to calculate the BDV, and a 500-mL volume test cell (Apar TO 1020) has been used. PD test is performed according to Standard IEC 60343, and a JDEVS-PDMA 300 device was used for this test.

BDV tests indicate that 20 nm Al₂O₃ is more effective at improving BDV than 80 nm Al₂O₃, with an improvement of 113% compared to 99% for the latter. The analysis of Weibull probability at BDV indicates that 20 nm Al₂O₃ performs better, with improvements of 141%, 125% and 112% at probabilities of 1, 10 and 50%, respectively. The results of the PD tests using the PDPR pattern also show that 20 nm Al₂O₃ is superior. For the heat transfer test, 0.05 g/L of both diameters were used to ensure fair conditions, and again, the advantage was with 20 nm Al₂O₃ (23% vs 18%).

The effect of Al₂O₃ NP diameter (20 and 80 nm) on various properties of virgin and aged TO has been investigated experimentally in this paper to examine the effect of proposed NP on electrical improvement of TO.

This paper aims to present a 3D numerical analysis of the load noise generation associated with large, oil immersed three‐phase power transformers.

After studying the mechanical behavior of the winding structures of transformers, the results of coupled magneto‐mechanical simulations are presented.

An appropriate modeling strategy of the vibratory winding structures of transformers is necessary to reduce complexity and computational resources.

The presented model setup describes a fully transient, 3D coupled magneto‐mechanical simulation of the vibratory winding structure of large power transformers.