Operating Conditions Of Power Transformers Research Articles

Application of improved support vector machine model in fault diagnosis and prediction of power transformers

AbstractPower transformers undertake the task of transforming voltage and transmitting electrical energy. Its operating status is directly connected with the stability and safety of the whole power system, and it is very important to judge the operating conditions of power transformers and diagnose fault types. The use of dissolved gas analysis technology in oil can provide preliminary fault diagnosis for transformers. However, with the increasing demand for fault diagnosis accuracy in modern electrical equipment, relying only on dissolved gas analysis technology in oil cannot satisfy the demands. To lift the transformer fault diagnosis accuracy, this study introduces the K‐means algorithm into the model and constructs a high‐precision and fast convergence diagnosis method and a power transformer fault location recognition model. In the example analysis, kernel functions were selected for training five typical gases to obtain the optimal parameters, and their prediction curves and errors were analyzed. Its diagnostic accuracy is 98.4%, and the error in all five gases is within 1 (uL/L). The average error of the improved support vector machine intelligent algorithm is lower than that of the previous model and other prediction methods. By testing the same sample data, the correctness of this method was verified. The significance of improving support vector machines lies in further improving the performance and applicability of the original support vector machine algorithm, providing a basis for future transformer maintenance and contributing to social development and continuous improvement of economic benefits.

Analysis of Operating Modes of Oil-Immersed Power Transformers with a Voltage of 10 (6) / 0.4 kV

The rate of thermal aging of the power transformers windings insulation depends on the effects of the electric field, mechanical stresses, temperature and processes that cause changes in these factors. A calculation algorithm is considered that allows determining the temperature of the most heated point of the windings of an oil power transformer at known values of the load current and ambient temperature. Calculation of the most heated winding point temperature and the rate of thermal aging of insulation for an oil power transformer at different ambient temperatures during the year, different values and different spectral composition of the electric load current showed that in some cases it is possible to violate the permissible operating conditions of power transformers. According to the calculation results, the dependences of the thermal aging rate of insulation on the ambient temperature are constructed, with different load parameters and different load coefficients of power transformers. For the considered modes, in the warm season, the value of the thermal aging rate of insulation significantly exceeds the nominal value. Based on mathematical models of oil power transformers with natural and forced oil circulation, expressions are obtained for determining the coefficient of reduction of the oil power transformers permissible load when the ambient temperature exceeds the normal value of 20 °C. On the basis of these expressions, for practical use, the dependences of the coefficient of reduction of the permissible load on the ambient temperature are constructed. The influence of ambient temperature must be taken into account when choosing the power of oil power transformers, for which it is assumed to operate in full redundancy mode or high load factor values (³ 0.8) in normal mode. To ensure the normative service life of the insulation of the windings, it is necessary to determine the design power of oil power transformers using the coefficient of reduction of the permissible load under the influence of higher harmonics of the current and the coefficient of reduction of the permissible load under the influence of ambient temperature.

Measuring Complex for Determining the Operating Conditions of Power Transformers

Приведен краткий обзор использования цифровых технологий для оценки технического состояния и ресурса силовых трансформаторов. Показано, что обследование действующих трансформаторных подстанций должно производиться с использованием средств, позволяющих определить фактический режим работы силовых трансформаторов. Предложено использовать мгновенные значения токов и гармонический анализ для определения фактического режима работы силовых трансформаторов и оценки выработки ресурса изоляции обмоток.Приведены состав и описание принципа работы и визуализация результатов, получаемых посредством измерительного комплекса, назначением которого является определение фактического режима работы силовых трансформаторов. Измерительные комплекс позволяет выполнять обследование действующих трансформаторных подстанций с мощностью силовых трансформаторов до 4000 кВА напряжением 10(6)/0,4(0,69) кВ.Определение фактического режима работы силовых трансформаторов и параметров, характеризующих ресурс работы силовых трансформаторов, производится с учетом воздействия несинусоидальных токов нагрузки и температуры окружающей среды. Используются математические модели сухих силовых трансформаторов с воздушно-барьерной изоляцией с естественным и принудительным охлаждением и масляных силовых трансформаторов с естественной и принудительной циркуляцией масла. Модели учитывают влияние высших гармонических составляющих тока нагрузки и фактическое значение температуры окружающей среды. Результаты определения фактического режима работы силовых трансформаторов визуализированы посредством трехфазных годографов тока, что обеспечивает наглядность отображения полученной информации.

Simple Geomagnetic Induced Current Detection and Monitoring in Power Transformers

This paper presents a detection system of geomagnetic induced currents based on the measurement of the magnetic field outside the magnetic core; it is possible to evaluate the core operating conditions of power transformers under the effect of geomagnetic induced currents. The nonlinear behavior of the core due to asymmetric saturation produces a distortion in the external magnetic field which can be evaluated by the measurement of the magnitude of even harmonics; we describe the experimental setup and the instrumentation required for real-time detection of asymmetric saturation caused by quasi-DC magnetic fields. The experimental results obtained by simulating the presence of geomagnetic induced currents are presented.

Improved transformer protection using probabilistic neural network and power differential method

This article presents a novel technique to distinguish between magnetizing inrush current and internal fault current of power transformer. An algorithm has been developed around the theme of the conventional differential protection method in which parallel combination of Probabilistic Neural Network (PNN) and Power Differential Protection (PDP) methods have been used. Both PNN and PDP method are independent of harmonic contents of differential current. The proposed algorithm is capable of detecting fault and its type in the eventuality of fault in the transformer. Moreover, the combination of PDP method with the PNN makes it capable to detect light internal faults for all ratings of transformers which improve the overall performance of digital differential protection scheme. For evaluation of presented algorithm, relaying signals of various operating conditions of power transformer, including internal faults, external faults, over-excitation and inrush conditions were obtained through modeling of transformer in PSCAD/EMTDC. The performance of proposed amalgamated technique (i.e. combined PNN and PDP method) is compared with the PNN, Feed Forward Back Propagation (FFBP) neural network and the conventional harmonic restraint methods. The results amply demonstrate the capability of the proposed algorithm in terms of accuracy and speed. The algorithm has been implemented in MATLAB. Keywords: Digital differential protection, Protective relaying, Probabilistic neural network, Active power relays, Power differential method.

Digital relays improve protection of large transformers

High demands are imposed on power transformer protective relays. Requirements include dependability (no missing operations), security (no false trippings), and speed of operation (short fault clearing time). The operating conditions of power transformers do not make the relaying task easy. Protection of large power transformers is one of the most challenging problems in the power system relaying area. Advanced digital signal processing techniques and artificial intelligence (Al) approaches to power system protection provide the means to enhance the classical protection principles and facilitate faster, more secure, and dependable protection for power transformers. Also, it is anticipated that, in the near future, more measurements will be available to transformer relays, owing to both substation integration and novel sensors installed on power transformers. All of this will change the practice for power transformer protection. This article briefly reviews the state of the art, but is primarily devoted to discussion of new approaches and future directions in digital relaying for power transformers.