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The research work showed where lab equipment is getting outdated and future equipment will be required for research work in IEC 61850–9-2 process bus.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

Differential relaying is one of the most widely used techniques for protecting power transformers. The purpose of this paper is to discuss and cover a developed methodology for analyzing the signals obtained from the differential protection of power transformers.

The differential signal obtained from the protective relays of power transformers is analyzed in this paper, in order to establish a relation between time‐dependent symmetrical components and space vectors. As a result of the formulation of such a relation, specific patterns are obtained and classified for the plot of the space vector during fault and inrush conditions.

What was found in the course of the work? This will refer to analysis, discussion, or results. It has been found that the discrimination between inrush and fault conditions is possible by observing a characteristic asymmetry in the plots of the space vector. A method for dealing with the said asymmetries based on the absolute value of the space vector as obtained from the differential signal is proposed and discussed. The theoretical approaches given in the paper are further validated through finite element simulations and laboratory tests, which include linear and non‐linear loads, in order to account for more severe exploitation conditions.

A complete protective algorithm can be developed from the analysis of the methodology proposed, which avoids the spectral analysis, since the methodology is based in pattern analysis rather that in the latter technique.

The methodology provides faster identification of the fault during inrush condition, since the spectral analysis is prevented.

It may be stated that the major contribution of the paper is the methodology proposed for identifying internal faults in power transformers using pattern characterization of the plot of the space vector.

THE A‐C ELECTRIC POWER GENERATION SYSTEM components for the VFW‐614 aircraft are supplied by the Aerospace Electrical Division of Westinghouse Electric Corporation located in Lima, Ohio. The a‐c electric power system consists of 2 main engine/constant speed drive driven channels and 1 auxiliary power unit (gas turbine) driven channel. Each channel consists of a generator, a generator control unit (GCU), a differential protection current transformer assembly and a control CT assembly that are supplied by Westinghouse AED. All system components are shown in fig 1.

ADVANCED GENERATOR TECHNOLOGICAL CONCEPTS by the Westinghouse Aerospace electrical division in joint development with Sundstrand Aviation offer dramatic improvements in electrical power system weight and reliability.

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.

The purpose of this paper is to describe a technique for modeling transformer internal faults using transmission line modeling (TLM) method. In this technique, a model for simulating a two winding single phase transformer is modified to be suitable for simulating an internal fault in both windings.

TLM technique is mainly used for modeling transformer internal faults. This was first developed in early 1970s for modeling two‐dimensional field problems. Since, then, it has been extended to cover three dimensional problems and circuit simulations. This technique helps to solve integro‐differential equations of the analyzed circuit. TLM simulations of a single phase transformer are compared to a custom built transformer in laboratory environment.

It has been concluded from the real time studies that if an internal fault occurs on the primary or secondary winding, the primary current will increase a bit and secondary current does not change much. However, a very big circulating current flows in the shorted turns. This phenomenon requires a detailed modeling aspect in TLM simulations. Therefore, a detailed inductance calculation including leakages is included in the simulations. This is a very important point in testing and evaluating protective relays. Since, the remnant flux in the transformer core is unknown at the beginning of the TLM simulation, all TLM initial conditions are accepted as zero.

The modeling technique presented in this paper is based on a low frequency (up to a few kHz) model of the custom‐built transformer. A detailed capacitance model must be added to obtain a high‐frequency model of the transformer. A detailed arc model, aging problem of the windings will be applied to model with TLM + finite element method.

Using TLM technique for dynamical modeling of transformer internal faults is the main contribution. This is an extended version of an earlier referenced paper of the authors and includes inductance calculation, leakages calculation, and BH curve simulation while the referenced paper only includes piecewise linear inductance values. This modeling approach may help power engineers and power system experts understand the behavior of the transformer under internal faults.

Considers the concerns of engineers designing overcurrent protection and measuring systems. Looks at the use of software to determine the instrument security fader with higher accuracy than with traditional calculation methods. An application of a space‐and‐time analysis makes it possible to calculate the peak value of the secondary voltage.

This research paper aims to investigate the change detection filter technique with a decision tree-based event (fault type) classifier for recognizing and categorizing power system disturbances on the high-voltage DC (HVDC) transmission link.

A change detection filter is used to the average and differential current components, which detects the point of fault initiation and records a change detection point (CDP). The half-cycle differential and average currents on both sides of the CDP are sent through the signal processing unit, which produces the respective target. The extracted target indices are sent through a decision tree-based fault classifier mechanism for fault classification.

In comparison with conventional differential current protection systems, the developed framework is faster in fault detection and classification and provides great accuracy. The new technology allows for prompt identification of the fault category, allowing electrical grids to be restored as quickly as possible to minimize economic losses. This novel technology enhances efficiency in terms of reducing computing complexity.

Setting a threshold value for identification is one of the limitations. To bring the designed system into stability condition before creating faults on it is another limitation. Reducing the computational burden is one of the limitations.

Creating a practical system in laboratory is difficult as it is a HVDC transmission line. Apart from that, installing rectifier and converter section for HVDC transmission line is difficult in a laboratory setting.

The suggested scheme’s importance and accuracy have been rigorously validated for the standard HVDC transmission system, subjected to various types of DC fault, and the results show the proposed algorithm would be a feasible alternative to real-time applications.

Many power system protection problems necessitate the measurement and track of the underlying current/voltage phasors. Adaptive LMS spectrum analyzers provide an ideal solution to such problems. This paper introduces a class of adaptive trigonometric spectrum analyzers. The underlying current/voltage is fed as a desired signal to an LMS adaptive algorithm. The reference input is a periodic regression derived from the basis set of the specified trigonometric discrete transform. The proposed algorithm is simple, computationally efficient, and exhibits a guaranteed stability and uniform convergence. A comparative study recommends the discrete Hartley transform. Simulations are provided to prove that the proposed spectrum analyzer is efficient in modeling faulty power system currents/voltages such as these arising from an over‐excitation of a power transformer.

Simple algoritims are developed to track the harmonic structure of the voltages or currents in a power system. The algorithms are based on fitting the measured signal adaptively to an appropriate model in a least mean squares (LMS) sense. The update is accomplished employing the well known adaptive LMS and signed LMS algorithms. The input sequence at each iteration consists of samples of harmonic sinusoids with a fundamental equal to the power frequency. It is shown that such input satisfies the persistence of excitation condition. It is also shown that the algorithms are computationally simple, practically tractable, and exhibit guaranteed stability. The performance of the algorithms and their efficiency in digital relaying in power system protection problems are demonstrated.