Ludwig Schiel

Correction of Current Transformer Transient Performance

If a current transformer (CT) saturates while transforming the heavy primary current, in each period, there are sections when the magnetic core is unsaturated and transformation is correct, and when it is saturated, it causes enormous errors. The key to correct the errors is to detect instants of saturation and moments when the saturation ends. This paper presents simple and efficient methods of doing that. In addition, it shows the way how to predict up to three samples after saturation with the acceptable degree of accuracy, thus artificially expanding the unsaturated section. It may substantially facilitate operation of protective devices. The ultimate solution of the problem is to estimate the values of the fundamental frequency component amplitude and the decaying DC component in each period. This paper presents the method of doing that on the ground of four consecutive samples taken during the unsaturated section. If the primary current consists of the fundamental and DC exponential components only, the accuracy of the method is excellent. Neglecting contamination of the current signal with harmonics and noise, it is possible to reconstruct the CT primary current based on the measured values of fundamental and DC components.

Universal Adaptive Differential Protection for Regulating Transformers

Since regulating transformers have proved to be efficient in controlling the power flow and regulating the voltage, they are more and more widely used in todays environment of energy production, transmission and distribution. This changing environment challenges protection engineers as well to improve the sensitivity of protection, so that low-current faults could be detected (like turn-to-turn short circuits in transformer windings) and a warning message could be given. Moreover, the idea of an adaptive protection that adjusts the operating characteristics of the relay system in response to changing system conditions has became much more promising. It improves the protection sensitivity and simplifies its conception. This paper presents an adaptive adjustment concept in relation to the position change of the on load tap changer for universal differential protection of regulating transformers; such a concept provides a sensitive and cost-efficient protection for regulating transformers. Various simulations are carried out with the Electro-Magnetic Transients Program/Alternative Transients Program. The simulation results indicate the functional efficiency of the proposed concept under different fault conditions; the protection is sensitive to low level intern faults. The paper concludes by describing the software implementation of the algorithm on a test system based on a digital signal processor.

Ultrasaturation Phenomenon in Power Transformers—Myths and Reality

In this paper, the ultrasaturation phenomenon of power transformers during their energization is studied. It is shown that under special conditions, the currents observed after transformer switching on do not contain enough restraining information (e.g., second harmonic), which may lead to protection maloperation. This paper concentrates on a thorough explanation of the problem and possible causes of ultrasaturation. Theoretical investigations are supported and illustrated with simulation studies performed both with MATLAB and electromagnetic transients program-alternative transients program. The outcomes of this research can further be used as hints for substation operation personnel as well as for the development of new protection stabilization criteria, which is not discussed further in this paper.

Sensitive protection of power transformers for internal inter-turn faults

In the paper new sensitive algorithms for detection of internal inter-turn faults in power transformers are described. Such faults are extremely difficult to detect since they induce negligible increase of the currents at the transformer terminals, although the currents flowing at the fault place are very high and dangerous for the transformer. The algorithms developed are based on the differential equation of the equivalent circuit of the transformer. In one version additional information from a CT installed inside of the triangle of delta side windings is used, which brings very promising results. Theoretical investigations are supported and illustrated with simulation studies performed with EMTP-ATP.

Transformer Differential Protection with Neural Network Based Inrush Stabilization

Application of artificial neural networks (ANN) for transformer differential protection stabilization against inrush conditions is presented. Three versions of the stabilization scheme are described. The best of them employs three ANNs fed with transformer terminal currents that has proven to be superior over the two other ANN schemes. The final solution combines the classification strengths of neural networks with commonly used second harmonic restraint, thus being a hybrid classification unit. To determine the most suitable ANN topology for the inrush classifier a genetic algorithm was used. The developed optimized neural inrush detection units have been tested with EMTP-ATP generated signals, proving better performance than traditionally used stabilization algorithms.

New algorithms to improve the sensitivity of differential protection of regulating transformers

Early detection of incipient failures is an important issue on the way to improve the reliability of energy supply and reduces the cost of maintenance activities. In this paper an advanced method of digital protection will be demonstrated. The new approach based on adaptive adjustment of percentage differential characteristic takes into account the current tapping position of regulating transformers and so provides the timely recognition of low-current faults being undetected before due to insufficient sensitivity to small current magnitude. The presented adjustment algorithm has been tested for two different transformer models set up using ATP-EMTP. Both of them are proved to be suitable for sensitivity improvement, which leads to enhanced information quality regarding the risk assessment of supply breakdown.

Differential protection of converter transformers

In this paper, development of the special converter transformer model (with 5 windings) and testing results of its differential protection is presented. The special converter transformer is mainly used for supply of rectifiers or converters, FACTS devices etc. This type of transformer can introduce non-standard fixed phase angle shifts such as 20o, 15o, 12o, 10o, etc. this is obtained by unique connections of the secondary windings (e.g. polygon, zig-zag, extended delta). The converter transformer must be protected by a relay being able to compensate for non-standard phase shifts. Otherwise the error magnitude would be very high (0.34 pu for 20o phase shift) and problem with sensitivity and stabilization of protection can take place. An appropriate simulation model of the converter transformer with five windings has been developed in MATLAB/Simulink environment. Next, the testing results of differential protection (7UT87 Siemens device) operation for various disturbances are presented. The testing was performed with use of Omicron tester and prepared simulation files in COMTRADE format.

Modeling and analysis of the single-core phase shifting transformer and its differential protection

In this paper, the analysis and simulation of a single-core asymmetrical phase shifting transformer (PST) is presented. PSTs are usually used for varying the voltage phase angle between the two systems, which provides controlling active power flow through transmission (tie) line. The essential part of this work was related to developing an appropriate simulation model of the single-core phase shifting transformer in MATLAB/ Simulink environment. In addition, this paper presents testing results of a selected PST differential protection scheme (proposed in the literature) for various disturbances. The testing outcomes provide useful information about limitations of the selected algorithm and create basis for further research.

Differential protection of single-core symmetrical phase shifting transformers

The development of the single-core symmetrical phase shifting transformer (PST) model and testing results of its selected differential protection is described in this paper. Generally, a PST is used for controlling the active power between the two systems being connected with one or more parallel transmission lines (paths). Most types of PSTs allow for changing of phase shift in a certain pre-defined range and thus the differential protection must on-line compensate for the phase angle shift introduced by a PST. Otherwise the error magnitude would be very high (even 1 pu) and problem with sensitivity and stabilization of protection can take place. An appropriate simulation model of the single-core symmetrical phase shifting transformer has been developed in MATLAB/Simulink environment. Next, the selected PST differential protection (proposed in the literature) was tested for various disturbances. The simulative testing results bring information about limitations of the selected algorithm and create basis for further research.

Analysis of potential use of the SVM technique for transformer protection

Reliable and fast discrimination between internal faults and inrush conditions is still a challenging issue. In this paper an application of Support Vector Machine (SVM) for the transformer differential protection is discussed. To achieve the satisfactory classification strength various input vectors and training parameters were considered. Finally, 16 different versions of SVM classifiers are proposed. The developed SVM based power transformer protection units have been trained and tested with EMTP-ATP generated signals. The operation performance of designed SVM classifiers is compared to standard differential protection with traditional second harmonic stabilization approach. Moreover, potential hardware implementation of the presented SVM classifiers is analyzed.