Magnetic Inrush Research Articles

Transformer protection, automation and monitoring systems

This paper presents the results of research on improving the protection, automation and monitoring systems of power transformers (PT) in 6-35 kV distribution networks. The authors have developed improved algorithms for differential and distance protection of a transformer based on measuring voltage and current synchrophasors, proposed additional criteria for blocking protection in the event of a magnetization inrush current (MIC), and considered the functions of the transformer monitoring and automation system based on synchrophasor technology.

Varying the energisation condition to mitigate sympathetic inrush current

Transformers are generally easy to access and can contribute significantly to entire power system. When a transformer is turned on for the first time, it produces a magnetising inrush current which acts as a starting current. Energisation of transformer has a substantial impact on inrush current and transformer that are connected in parallel. Sympathetic inrush current is a phenomenon that appears when a transformer is switched-on in network whereas the other transformers that was earlier energised. Besides, when sympathetic inrush phenomena occur, the peak and period fluctuate significantly. In this paper, the transformers will be energised in three different ways and each condition will be explored in depth. The operation time of the transformer’s energisation whether it is energised simultaneously or at different times are tested and analysed in terms of their characteristics. It is performed using power system computer aided design (PSCAD) software, starting with a develop model of the energisation and then generate the outcomes. The results of the simulation demonstrate that energising the transformer in different ways can give different effect on the sympathetic inrush current, as well as the variables that affect it and methods for reducing it.

Practical Rules to Adjust the Numerical Overcurrent Functions of Protective Relays to Avoid Maloperation due to Inrush Currents of Downstream Distribution Transformers

This article shows practical rules which were developed for the adjustment of Numerical Overcurrent Functions (NOCF) of microprocessor-based protective relays in order to avoid their maloperation due to Transformer Magnetizing Inrush Currents (TMIC). The TMIC waveforms are decaying and nonsinusoidal, and their effects are different on instantaneous, definite-time, or inverse-time NOCF; thus, specific rules are necessary for each type of NOCF. Experimental methods, specifically developed to perform tests of NOCF with TMIC, were applied to four commercial relays from different manufacturers. As each relay has different types of curves, a total of 26 inverse-time curves were included in the set of tests. In practice, the specific behavior of a relay cannot be assumed as known during the coordination of protection; therefore, the rules are based on the worst cases of results (i.e., in order to avoid the incorrect trip of any of the analyzed relays). The input data for the developed rules are the estimated cumulative RMS values of TMIC, assumed as known since there is a long tradition of their estimation. The estimated cumulative RMS values of TMIC, at different time intervals, should be divided by the numerical factors which were specifically proposed for each type of NOCF (to obtain suitable limits to avoid their inappropriate operation). In order to illustrate the application of the proposed rules, the solutions to two cases related to a simple example are shown at the end of this article.

A Statistical Approach to Discriminate the Magnetising Inrush Current and Internal Fault Current of a Transformer

Abstract: The transformer is one of the important elements of electrical power system. So, it is required to provide the good protection scheme for transformer, which enhance the reliability & economy of the system. There are many methods available for the protection of transformer out of which differential protection is the most commonly used method. It is observed that the conventional differential protection scheme mal-operates during the magnetizing inrush current. The mal-operation of differential relay will affect the continuity of supply to customer and hence the economy of our system. To avoid such type of mal-operation of the relays, proper discrimination between the magnetising inrush current and fault current is required. This paper presents Teager Energy Operator (TEO) and Statistical parameters based novel approach for the discrimination between the magnetizing inrush current and the internal fault current of a transformer. In this paper, TEO of the differential current of the transformer is calculated and compared with its threshold value to detect the abnormal condition. When TEO is more than threshold, statistical parameters like variance & standard deviation are calculated and if the calculated value is more than the threshold then it’s an internal fault condition and hence relay gives the trip signal. Else relay does not issue the trip signal. The suggested algorithm is tested using the experimental data. The results demonstrated that the suggested algorithms are capable of accurately differentiating between the transformer's internal fault current and inrush current.

Discrimination of Transformer Inrush Currents and Internal Fault Currents Using Extended Kalman Filter Algorithm (EKF)

The discrimination of inrush currents and internal fault currents in transformers is an important feature of a transformer protection scheme. The harmonic current restrained feature is used in conventional differential relay protection of transformers. A literature survey shows that the discrimination between the inrush currents and internal fault currents is still an area that is open to research. In this paper, the classification of internal fault currents and magnetic inrush currents in the transformer is performed by using an extended Kalman filter (EKF) algorithm. When a transformer is energized under normal conditions, the EKF estimates the primary side winding current and, hence, the absolute residual signal (ARS) value is zero. The ARS value will not be equal to zero for internal fault and inrush phenomena conditions; hence, the EKF algorithm will be used for discriminating the internal faults and inrush faults by keeping the threshold level to the ARS value. The simulation results are compared with the theoretical analysis under various conditions. It is also observed that the detection time of internal faults decreases with the severity of the fault. The results of various test cases using the EKF algorithm are presented. This scheme provides fast protection of the transformer for severe faults.

Mitigation of magnetising inrush current in three–phase power transformer

<span>During energization of no – load transformers, a high and peaky current flow on the primary side which has rich second harmonics. This current is magnetising inrush current and it is generated when transformer core is driven deep into saturation. This current has various disturbances on transformer attribute; reduced life-span, major voltage drop, insulation weakening, electrical and mechanical vibrations in coils, difficulties in protecting relays and all leads to poor power quality of the electric system. This paper presents the analysis and comparison of recent techniques to reduce the magnitude of inrush current during energization of power transformer. The simulation results are provided for Pre – insertion of resistors, Controlled swithing and Pre – fluxing method. The best method is suggested for mitigating inrush current by simulating in MATLAB/SIMULINK environment.</span>

Residual Magnetic Flux of On‐Load Transformer for Controlled Switching

When a transformer is being energized, a large magnetic inrush current flows depending upon the closing phase angle of the circuit breaker and the residual magnetic flux in the iron core. One of the suppressing methods of the magnetic inrush current is to control the closing phase angle of the circuit breaker. Controlled switching has been used for no‐load transformer energization until now. However, the transformer may be switched under an on‐load state. In this case, a large magnetic inrush current will flow. To suppress the inrush current by using controlled switching, the information of the residual magnetic flux in the iron core is needed. The residual magnetic flux for no‐load transformers has been investigated. However, the residual magnetic flux for on‐load transformers was not investigated. In this paper, the residual magnetic flux for an on‐load transformer was investigated by experiments and calculations. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Automated Identification of Electrical Disturbance Waveforms Within an Operational Smart Power Grid

Electric power utilities employ “smart” re-closing devices capable of capturing electrical disturbance (ED) waveforms in real-time. These waveforms are digitally sampled, transmitted back to the utility, and stored in text files that comply with the IEEE COMmon format for TRAnsient Data Exchange (COMTRADE) standard. An average of 2,100 ED events are recorded, by 850 devices, on a monthly basis within Electric Power Board's distribution network. Due to operational restraints such as: time, money, and person power, only 2% of these recorded events are currently analyzed by power utility personnel. The remaining 98% of recorded events remain a significant loss in information, which could be vital in fully understanding the operating condition within the distribution network. This work presents a hierarchical automated classification process that assigns ED events into one of three “categories”: valid data, switching events, and faults/power quality (PQ) disturbances. This process correctly assigned 92.9% of the tested 140 COMTRADE files into one of these categories. In addition to this categorization, this work presents an automated approach for the classification of magnetic inrush events. A classification rate of 90.63% is demonstrated using 32 transformer inrush COMTRADE files.

Оценка бросков тока намагничивания силового трансформатора

The mathematical model of a shell-core power transformer’s magnetization branch is substantiated. By using the model, analytical expressions for the magnetizing current instantaneous values under the conditions of geomagnetic disturbances can be obtained. Quantitative assessments of the magnetizing inrush current amplitudes and durations versus the geomagnetic disturbance intensity are obtained. The dynamics of the power transformer magnetic system saturation transient and changes in the magnetization inrush current amplitudes and durations after a sudden occurrence of geomagnetic disturbances are shown. The error of estimating the magnetizing inrush current amplitudes under geomagnetic disturbances is determined based on comparison with experimental data.

Multiscale multivariate fuzzy entropy‐based technique to distinguish transformer magnetising from fault currents

As vectors' similarity is defined on the basis of the hard boundary of Heaviside function in multiscale multivariate sample entropy, the two families of statistics show high sensitivity to the similarity tolerance. Multiscale multivariate fuzzy entropy (MMFE), which applied fuzzy membership function, overcomes the problem. Hence, the visualisation inrush current discrimination algorithm based on MMFE is proposed. The proposed algorithm divides the MMFE-τ plane into two parts: active and braking zones. The ratio of the current entropy area to the given braking zone area is designated as the entropy area ratio. The magnetising inrush and fault current of the transformer are identified on the basis of the numerical value comparison between the entropy area ratio and the fixed value of 1. Through the ATP/EMTP platform and dynamic testing system, the transformer currents under different operating conditions are analysed. Results demonstrate that the proposed algorithm can effectively distinguish the magnetising inrush from the fault current of the transformer and is superior to other methods.

A New Algorithm for Three-Phase Power Transformer Differential Protection Considering Effect of Ultra-Saturation Phenomenon Based on Discrete Wavelet Transform

Abstract One of transient phenomena that lead to the false trip of the power transformer differential protection during the energization of a loaded power transformer is the ultra-saturation phenomenon. This paper presents, at first, a new algorithm for three-phase power transformer differential protection considering effect of the ultra-saturation phenomenon based on Discrete Wavelet Transform (DWT). To model the ultra-saturation phenomenon, the nonlinear characteristic of the transformer core and the effect of the saturation of the current transformers are taken into account. It is assumed that the load of the transformer is a resistive and inductive load. In this algorithm, the ultra-saturation phenomenon, the external and internal faults of power transformer and the magnetic inrush current are simulated. To distinguish between these phenomena, appropriate criteria using DWT by the use of standard deviation of coefficients are presented. Also, one of the most important criteria for the digital relays is the time for making a decision. Thus, to determine the time of decision, the experimental results will be presented.

Mitigation of Electric Arc Furnace Transformer Inrush Current Using Soft-Starter-Based Controlled Energization

The energization of power transformers is a frequent operation in electric arc furnaces (EAFs). Magnetization inrush currents with 10–50 times the rated transformer current can flow during several line cycles. The magnitude of the inrush currents depends on parameters like the point on wave of voltage energization, residual flux in the core, transformer size, and utility systems characteristics. This momentary high current results in system disturbances and reduction of the transformer life cycle. In this paper a scheme to mitigate large inrush currents using controlled voltage ramp soft-starter-based circuit is presented. Simulation and experimental results prove the effectiveness of the soft-starter-based controlled energization.

A GDSC-Based Technique to Distinguish Transformer Magnetizing From Fault Currents

This paper presents a novel technique to distinguish a transformer magnetization inrush current from a fault current. The proposed scheme is based on the behavior of fundamental and second-harmonic positive- and negative-sequence components. These four components are computed by using generalized delayed signal cancelation (GDSC). After a transient analysis for the GDSC filters, related to the behavior of those four components detection, some features were proposed. These features depict the trajectory change of the most relevant components in the $\alpha \beta$ plane and their amplitudes for short-circuit discrimination, rather than waiting for filters convergence or waiting one cycle to analyze waveform symmetries. Some features instantly change after an electrical event, making possible a distinction by analyzing a short number of samples. This is the main competitive advantage of the proposed technique. In order to evaluate the proposed method performance, 2200 test cases based on an actual power system were simulated. Also, current-transformer (CT) saturation influence on the technique, computational burden, and embedded implementation were analyzed. In about 95% of the results obtained, the response time of the proposed method was around one fourth of a fundamental cycle.

Using smart grid sensors and advanced software applications as an asset management tool at Hydro Ottawa

In 2014, Hydro Ottawa began a pilot project to use power quality monitors to locate faults on distribution feeders supplied by medium voltage systems. Fault measurements captured by the meters are downloaded automatically, integrated into a relational database, and processed for reactance calculations. The reactance calculations are combined with detailed distribution circuit models and geographic information system data to build estimated fault location tables and web-based map displays. The systems are integrated on the company intranet and used in real time by numerous groups within Hydro Ottawa including power quality engineers, control room operators, field operations, and distribution planning. The algorithm used for waveform processing can distinguish between single-phase faults, multi-phase faults, sub-cycle faults, and feeder energising magnetising inrush. This study presents an overview of some of the parameters and practices for finding faults at Hydro Ottawa.

Power transformer differential protection using current and voltage ratios

The main challenge in transformer protection is to find a fast and efficient differential relay algorithm that isolates the transformer from the system causing least damage. Algorithm should also avoid mal-operation while differentiating between the operating conditions. This paper presents an improved differential protection scheme for power transformer. The proposed scheme is based on the ratio of the absolute difference and absolute sum of the primary and secondary currents of each phase, supplemented by the ratio of the absolute difference and absolute sum of the primary and secondary terminal voltages of each phase. The proposed algorithm aims at avoiding mal-operation, possible with the conventional three-phase transformers differential protection scheme due to transient phenomena, including the magnetic inrush current, simultaneous inrush with internal fault, and faults with current transformer saturation. Investigation of the proposed differential protection scheme using both current and voltage ratios shows that it can provide fast, accurate, secure and dependable relay for power transformers.

Detection of high impedance faults using current transformers for sensing and identification based on features extracted using wavelet transform

High impedance fault (HIF) has long been a challenging problem in network protection due to its random behaviour and low magnitude. The conventional protection devices cannot be utilised since the HIF does not draw enough current to cause tripping. The feature of wavelet transform (WT) which decomposes a signal into different frequency bands and locations in time can be utilised to extract HIF features and detect its occurrence. In the study, HIF arcing currents associated with different types of contact surface are produced by experiments set up in the laboratory. Features of the fault currents are extracted and a new detection criterion is developed based on WT coefficients. Transformer magnetising inrush currents and capacitor switching transients are also produced by experiment and simulation, respectively, to represent transient disturbances commonly occurred in the distribution network. The detection criterion is used to discriminate the HIF from other normal non-fault transient events. Three different types of wavelet are tested and the Daubechies wavelet Db4 gives the best performance based on its detection and discrimination rates. The efficacy of utilising existing conventional current transformers for HIF application is also tested and verified by experiment.

EFFECT OF CORE CUTTING TOPOLOGY AND MATERIAL OF THREE PHASE TRANSFORMER ON MAGNETIZATION CURVE AND INRUSH CURRENT: EXPERIMENTAL APPROACH

This study conducts the core cutting topology effect in three phase transformer on magnetization curve and inrush current. Core cutting topology effect on magnetization curve and magnetic field is analyzed using Finite-Element Method (FEM) simulation at the points of connection between the core pieces. The magnetization curves are used to determine inrush current of each transformer. Therefore, calculated inrush current was then compared to experimental measurements of inrush currents. The existence of residual flux or remnant flux is considered in inrush current measurement, thus demagnetization method is used to obtain the real inrush current value. Simulation and experimental results show that the topology of the transformer core cutting affects the magnetization curves and inrush currents. These are proven by differences in the magnetization curve and inrush current of both topology transformer core cutting. It was also suggested that quality of core material affected the magnetization curve and inrush current.

To Reduce Magnetic Inrush Current by Point Wave Switching Method

To Reduce Magnetic Inrush Current by Point Wave Switching Method

Mitigation of magnetic inrush current during controlled energization of coupled un-loaded power transformers in presence of residual flux without load side voltage measurements

This paper presents a novel approach for minimizing magnetic inrush current to a level as low as no load current during controlled energization of coupled un-loaded power transformers in presence of residual fluxes without employing load side voltage measurements. The suggested method has been evaluated for power transformers having various winding connections, design configurations (magnetically dependent and independent type), its side of energization (Δ or Y) and different level & polarities of residual fluxes. The effect of breaker performance in terms of variation in dielectric properties and operating time of circuit breakers has also been explored. The method is applied successfully on various 765/400/33 kV power (auto) transformers with delta connected tertiary winding on an existing Indian power transmission network and results, for a couple of cases, are presented. Based on simulation results, it has been observed that the inrush current for a number of transformers has been managed below 5% of its full load current rating. This validates applicability of the proposed technique in real system applications.

Mitigation of NSC and Alleviate of Magnetic Inrush Currents in Indian Traction System

Mitigation of NSC and Alleviate of Magnetic Inrush Currents in Indian Traction System