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Computers need clean, reliable, electrical power. The various faults of electrical power, such as spikes, sags, outages, noise, frequency variations, and static electricity, are defined and described. Preventive measures that computer users can employ to reduce the potential of electrical problems are discussed, as are the processes for detecting, diagnosing, and curing electrical problems when they do occur. Sidebars consider: transformers; power distribution units (PDUs); surge currents/ linear and non‐linear loads; and sizing the power conditioning system. The next issue will conclude this series with an article on uninterruptible power supplies and a bibliography.

The purpose of this paper is to investigate the applicability of a direct current (DC) hysteresis measurement on power transformer terminals for the subsequent hysteresis model parametrization in transformer grey box topology models.

Two transformer topology models with two different hysteresis models are used together with a DC hysteresis measurement via the power transformer terminals to parameterize the hysteresis models by means of an optimization. The calculated current waveform with the derived model in the transformer no-load condition is compared to the measured no-load current waveforms to validate the model.

The proposed DC hysteresis measurement via the power transformer terminals is suitable to parametrize two hysteresis models implemented in transformer topology models to calculate the no-load current waveforms.

Different approaches for the measurement and utilization of transformer terminal measurements for the hysteresis model parametrization are discussed in literature. The transformer topology models, derived with the presented approach, are able to reproduce the transformer no-load current waveform with acceptable accuracy.

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.

This paper aims to focus on the implementation of the International Electrotechnical Commission (IEC) 61850–9-2 standard based process bus with merging units (MUs) and sampled values (SV) to improve the protection and control systems. The digital process interface is important to be included on the process bus level.

The IEC 61850–9-2 process bus standard is not extensively used in regard to SV when the IEC 61850 standard is implemented by power utilities. Many protection and control intelligent electronic devices (IEDs) are connected to a substation communication network, routers and switches using fibre-optic linked Ethernet. However, inductive current transformers (CTs) and voltage transformers (VTs) secondary circuits are still hardwired to the IEDs. The paper highlight issues with the copper wires for currents signals and how these issues can be eliminated by using the MUs and the SV protocol. The voltage regulator control IED of each transformer is required to regulate the voltage level of the secondary side bus bar it is connected to. All the regulating IEDs of parallel-connected transformers are required to communicate with each other to share information. They collectively control the bus bar voltage depending on the switching configuration of the parallel transformers.

It is shown that process bus information such as the high voltage switchgear status information of primary plant in the yard, can be used to improve the substation protection and control systems. The power transformer protection and voltage regulator control are focused on.

The deliverables of the research work can be applied in: The Centre for Substation Automation and Energy Management systems of the Department of Electrical Engineering, power utilities and other establishments using power systems and digital substations in the electrical supply industry. The research work on the thesis led to the development of a laboratory test-bench where students can learn and understand the basics of the IEC 61850–9-2 SVs principles. The test-bench components such as the IEDs, real-time digital simulator, standalone MUs and Ethernet equipment can be used for future research applications. The test-bench can be used to demonstrate during course work for students at the University, the basics of digital substations using a process bus network with IEDs, MUs and Ethernet equipment.

The research work showed where lab equipment is getting outdated and future equipment will be required for research work in IEC 61850–9-2 process bus.

Power utilities can benefit from implementing the IEC 61850 part 9–2 of the standard and by using MUs and other process interface information in substations. A cost reduction in high voltage equipment, substation installation and commissioning costs and better performance of protection and control system can be achieved.

Statistics show that selecting the best investment program based on both cost and effectiveness can avoid financial losses. However, investment evaluation of a power transformer is full of uncertainty as it is hard to obtain accurate and useful cost-effectiveness results. Therefore, the purpose of the paper is to establish an investment evaluation model.

The cost-effectiveness evaluation model in this study used grey correlation analysis for the power transformer selection based on life cycle cost (LCC). Indices of cost and effectiveness factors were chosen to form a three-level index system including quantitative and qualitative factors. Evidential reasoning was applied to quantify the qualitative indexes. Grey correlation analysis was applied to select the best investment program.

The results from this study show that the proposed approach is effective and offers a new approach to evaluating transformer investment.

The model was applied to an investing decision-making problem of the transformer in a new substation in Wuhan, China.

It is very important to select the best transformer program in the candidate investment programs because the investment program decides almost 70 percent of the LCC of the power transformer.

Interturn winding faults, one of the most important causes of power transformers failures, cannot be detected by existing detection methods until they develop into high‐level faults with more severe damage to the transformer. The purpose of this paper is to describe development of a new discrete wavelet transform (DWT) based approach for detection of winding interturn faults.

The following approach was accomplished for development of the proposed fault detection method in this study. The DWT was first applied to decompose the terminal current signals of a transformer, which in turn were obtained from simulations using a finite elements method model of the transformer, into a series of wavelet components. Based on the characteristic features associated with interturn faults extracted from the decomposed waveforms of the terminal currents, a detection scheme was developed. An experimental setup was used to validate the proposed detection method.

The results of this study demonstrate the efficacy of DWT applied on terminal currents of the transformer to identify interturn faults on the windings well before such faults lead to a catastrophic failure. It is believed that, based on the present findings, there definitely exists scope for improving interturn fault diagnosis with wavelet transform.

Performing more detailed studies to find all relevant characteristics of the wavelet transform in this application, identifying the location of the faulted turns along winding, applying the method for indicating early stages of turn insulation deterioration and evaluating other type of wavelets for this application would be some future directions of this research.

With the proposed method, it is becoming possible to detect early signs of the fault occurrence, so that the necessary corrective actions can be taken to prevent long‐lasting outages and reduce down times of the faulty power transformer. The method will be particularly useful as a complement for the classical protection devices of the power transformers.

Some recent studies have been carried out regarding the application of DWT for discrimination between an internal fault and other disturbances such as magnetizing inrush and external faults. This paper extends those studies for the detection of interturn faults using more quantitative and qualitative characteristics features.

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.

Depending on the load the flux‐density distribution inside power transformers core shows significant local variations due to stray fluxes which enter the transformer core. As saturation of the core has to be avoided the flux‐density distribution has to be determined early in the design stage of the transformer. This paper seeks to address these issues.

To determine the load dependent flux‐density distribution the operating point of the transformer is calculated considering linear and non‐linear material properties. The operating point is determined using a linearised lumped parameter model of the transformer under various load conditions. Considering non‐linear material properties the inductance matrix depends on the operating point and will be extracted by means of the FEM whenever the magnetic energy within the transformer changes notably.

This paper presents a numerical stable approach to calculate the operating point of a transformer by using the magnetic flux linkage as state variable for the coupled field problem.

The proposed approach uses a fixed time‐step to update the lumped parameters by means of the FEM. This results in long simulation times. In further research it is planned to implement an adaptive time‐step method based on the change of the magnetic energy.

A numerical stable approach to calculate the operating point of a transformer by using the magnetic flux linkage as state variable for the coupled field problem is proposed. The methodology is applied to a 2D model of a three‐phase transformer. However, it also can be applied to 3D FE models. Based on the calculated operating point, the flux‐density distribution can be determined and several post‐processing methods can be executed (e.g. determination of core losses, …).

This paper aims to improve the finite element modelling of transformers subjected to DC excitation, by including core joint details.

Geomagnetically induced currents (GICs) or leakage DC can cause part-cycle, half wave saturation of a power transformer’s core. Practical measurements and finite element matrix (FEM) simulation were carried out using three laboratory-scale, untanked single-phase four limb transformers resembling real power transformers in terms of the core steel and parallel winding assemblies. “Equivalent air gaps” at the joints, based on AC measurements, were applied to the FEM models for simultaneous AC and DC excitation.

Measurements confirm that introducing equivalent air gaps at the joints improves the FEM simulation of transformers carrying DC.

The FEM simulations based on the laboratory transformers are exemplary, showing the difference between modelling core joints as solid or including equivalent air gaps. They show that, for more representative results, laboratory transformers used for research should have mitred core joints (like power transformers).

This research shows why joint details are important in FEM models for analysing transformer core saturation in the presence of DC/GICs. Extending this, other core structures of power transformers with mitred joints should improve the understanding of the leakage flux during half-wave saturation.