kV Transformer Research Articles

Cycle time reduction using intermittent DC internal heating in vapour phase drying of cellulose-based insulation used in transformers

ABSTRACT For the commissioning of a new transformer, a delay in delivery caused owing to the long-drying process at the manufacturer is not acceptable in order to avoid erratic power supplies and extensive down times. To increase productivity, ensure on-time delivery, avoid unplanned power outages, reduce the cost, increase the efficiency of energy utilisation and maintain the quality parameters of the transformer insulation thereby increasing its service life, cycle time of insulation drying at the manufacturer needs to be reduced. As of today, the latest technology for insulation drying of transformers at the manufacturer’s factory is the vapour phase drying (VPD) method. The cycle time in VPD may span for 4–5 days for a power transformer. This establishes the need to reduce the cycle time in VPD of transformer insulation. In this work, experimentation was carried out on 11 kV transformers for developing a system to reduce the cycle time in VPD.

Impact of Adding Fast Switching Fault Current Limiter (FSFCL) to the Neutral Point of 220 kV Transformer

Impact of Adding Fast Switching Fault Current Limiter (FSFCL) to the Neutral Point of 220 kV Transformer

Axial vibration characteristics analysis of transformer windings based on magnetic‐structural coupling correction model

AbstractDue to the strong coupling effect between the internal magnetic field and the structural field of the transformer, the magnetic‐structural coupling should be considered in axial vibration process of the winding short‐circuit impact. A 110 kV transformer is taken as the research object. Firstly, the vibration modal characteristics of the transformer are calculated using the classical axial vibration model, and the spatial distribution of the leakage magnetic flux density of the iron core window is obtained based on the image method, which is used as the basis for calculating the excitation electromagnetic force. With the consideration of the non‐linear mechanical characteristic of the pad, the dynamic stiffness equation is analysed and established and the magnetic‐structural coupling correction model is constructed. Finally, the winding vibration amplitudes obtained respectively by the classical model, the magnetic‐structural coupling model, and the magnetic‐structural coupling correction model considering the dynamic stiffness are compared. The results show that, compared with the classical model, the vibration amplitude increment with the magnetic‐structural coupling correction model is less. The dynamic stiffness will hinder the vibration intensification. The magnetic‐structural coupling correction model can provide a more accurate calculation scheme for the winding vibration characteristic analysis.

Machine learning chain models for multi-response prediction of electrical equipment in substation subjected to earthquakes

Engineering structures often exhibit multiple potential vulnerable positions during strong earthquakes, such as porcelain insulators and connection flanges of electrical equipment in substations. This paper proposes two types of machine learning (ML) chain models, where multiple individual models are linked end to end, to predict multiple peak seismic responses of substation equipment at the same time using intensity measures (IMs). One is a simple chain where the next input is the previous output, while in another one, the next input is combined by IMs and the previous output. The training mechanisms of ML chain models are presented by means of bio-inspired multi-objective optimization techniques for the hyperparameters of multiple individual ML models. A case study on a 1100 kV transformer bushing is then conducted. Artificial neural network-gradient boosting regression and artificial neural network-kernel ridge regression chain models are respectively established for predicting the peak stresses at two most vulnerable positions. Both the evaluation indicators and shaking table tests show enough prediction accuracy of the two ML chain models. Such chain models are qualified for identifying the initial damage to equipment, which can be employed for assisting post-earthquake rapid judgement and relief.

Load Flow Analysis and Loss Reduction Activities: A Case Study on Kawasoti 132/33/11 kv Substation

This paper deals with the study of energy flow patterns in INPS connected 132KV/ 33KV/11KV Kawasoti Sub-Station. From the monthly data as of April and May 2020, the base load for 30 MVA 132/33 KV transformer is about 12 MW and peak load is around 15 MW. Load forecast of 132/33/11 KV Kawasoti Sub-Station shows that the cumulative load growth percentage is around 70 % and around 8.75% per year. The peak load in 2020 was around 23.53 MW and it would approximately reach 40 MW at the end of fiscal year 2028. Load flow analysis as of 2020 shows total distribution loss was found to be 1.7833 MW when the demand is 23.658 MW at 0.7141 lagging and reactive power loss of 8.907 MVAR is found. Estimated total distribution loss for the year 2028 would be 3.851 MW when the demand is 40.238 MW at 0.76 lagging and reactive power loss of 20.572 MVAR. After the placement of a capacitor bank of 7000 KVar and 5000 Kvar on MV and LV Bus-Bar respectively, the total distribution loss was found to be 0.8695 MW with pay-back period of 1.427 Years for year 2020. After the placement of a capacitor bank of 10000 KVar and 7000 Kvar on MV and LV Bus-Bar respectively, the total distribution loss would be 2.2563 MW with pay-back period of 1.158 Years for forecasted condition. The simulated model, result and analysis are presented in this paper.

Inflection Point Effect of Interturn Insulation for Transformer under Preload Stress

The current research mainly focuses on the influence of different voltage forms on partial discharge for the interturn insulation of a transformer, and the discharge characteristics and its mechanism of interturn insulation under the action of preload are unclear. Therefore, a partial discharge test platform under the synergistic action of preloading force and electrical stress is constructed based on the actual operation conditions of the interturn insulation of a 750 kV transformer. Then, the partial discharge characteristics and its mechanism is explored by using (OM, SEM, FTIR, XRD, EDS, FEA). It is found that the statistical parameters and damage degree of interturn insulation decrease first and then increase with the increase in preload. Moreover, there is an inflection point at 1000 N. The reason is that the preload causes the deformation of the holes and air gaps between the layers of insulating paper and in the insulating paper. As a result, the contact area and volume of partial discharge are changed, which further changes the characteristics of partial discharge for interturn insulation. This study can provide a reference for the maintenance and structural optimization of 750 kV transformers.

Vibration and noise mechanism of a 110 kV transformer under DC bias based on finite element method

Global energy and environmental issues are becoming increasingly problematic, and the vibration and noise problem of 110 kV transformers, which are the most widely distributed, have attracted widespread attention from both inside and outside the industry. DC bias is one of the main contributing factors to vibration noise during the normal operation of transformers. To clarify the vibration and noise mechanism of a 110 kV transformer under a DC bias, a multi-field coupling model of a 110 kV transformer was established using the finite element method. The electromagnetic, vibration, and noise characteristics during the DC bias process were compared and quantified through field circuit coupling in parallel with the power frequency of AC, harmonic, and DC power sources. It was found that a DC bias can cause significant distortions in the magnetic flux density, force, and displacement distributions of the core and winding. The contributions of the DC bias effect to the core and winding are different at Kdc = 0.85. At this point, the core approached saturation, and the increase in the core force and displacement slowed. However, the saturation of the core increased the leakage flux, and the stress and displacement of the winding increased faster. The sound field distribution characteristics of the 110 kV transformer under a DC bias are related to the force characteristics. When the DC bias coefficient was 1.25, the noise sound pressure level reached 73.6 dB.

Iron Loss and Temperature Rise Analysis of a Transformer Core Considering Vector Magnetic Hysteresis Characteristics under Direct Current Bias.

Direct current (DC) bias induced by the DC transmission and geomagnetically induced current is a critical factor in the abnormal operation of electrical equipment and is widely used in the field of power transmission and distribution system state evaluation. As the main affected component, the vector magnetization state of a transformer core under DC bias has rarely been studied, resulting in inaccurate transformer operation state estimations. In this paper, a dynamic vector hysteresis model that considers the impact of rotating and DC-biased fields is introduced into the numerical analysis to simulate the distribution of magnetic properties, iron loss and temperature of the transformer core model and a physical 110 kV single-phase autotransformer core. The maximum values of B, H and iron loss exist at the corners and T-joint of the core under rotating and DC-biased fields. The corresponding maximum value of the temperature increase is found in the main core limb area. The temperature rise of the 110 kV transformer core under various DC-biased conditions is measured and compared with the FEM (Finite Element Method) results of the proposed model and the model solely based on the magnetization curve B||H. The calculation error of the temperature rise obtained by the improved model is approximately 3.76-15.73% and is much less than the model solely based on magnetization curve B||H (approximately 50.71-66.92%).

The adaptability research and evaluation of digital distance protection based on Python and PSCAD

With the development of power systems, digital distance protection, as an innovative and cutting-edge technology, plays a crucial role in ensuring the stable operation of the power grid. Due to its high precision, rapidity, and reliability, digital distance protection has become a key component of power system safety. Distance protection is widely used in distribution networks at or below 35 kV. Therefore, studying its adaptability and effectiveness as a remote backup protection can provide an effective foundation for improving grid security.With the utilization of Python and PSCAD, the adaptability of digital distance protection is meticulously examined in the context of low voltage side faults in 110 kV/35 kV transformers, specifically as a remote backup protection measure. The core objective of this investigation is to assess the efficacy of this protection strategy in upholding the safety and reliability of power systems. To achieve this, 3 approaches is employed: theoretical analysis, simulation modeling, and experimental validation. This process allows for a comprehensive evaluation of the performance characteristics and application efficacy of digital distance protection. The insights garnered from this meticulous study offer profound understanding into the strengths and potential limitations of this protection paradigm, serving as a solid foundation for the refinement of existing protection strategies and the enhancement of the overall resilience of power systems. In essence, this article aims to evaluate the effectiveness of digital distance protection as a remote backup protection strategy for faults on the low-voltage side of 110 kV/35 kV transformers. The core objective is to assess the efficacy of this protection strategy in maintaining the safety and reliability of the power system.

Formation the coefficient of growth for the power scale of transformers taking into account the operational indicators of substations

The article describes the sequence of formation of the growth coefficient of the transformers power scale, taking into account the operational indicators of substations. For this purpose, an expression for finding the optimal power of 110 kV transformers has been developed on the basis of a technical-economic model of costs for the transformation of electrical energy. The developed expression is used to find the optimal power of transformers of 110 kV in conventional units, taking into account the load of substations, which is the basis for the formation of the growth coefficient of the transformers power. The search for optimal power was performed on the basis of deviations of the indicators of the maximum load of transformers and the time of maximum losses. The time indicators of maximum losses and maximum load are calculated according to the hourly load data of transformers, taking into account the presence of generation nodes on the secondary voltage buses. The formation of the growth coefficient of the scale of transformers is performed by finding the mathematical expectation of the optimal power and its shift based on the boundaries of the distribution of two adjacent powers of transformers. The substantiation of the formed coefficient of growth of the transformers power was performed according to the criterion of minimum technological losses of electrical energy, by comparing the daily loses schedules in transformers. According to the research results, it follows that the application of the obtained coefficient allows to reduce the level of technological losses. The study was carried out on the example of operating substations with two-winding transformers of 110 kV using the scheme of the established mode of operation of the electric network.

Research on new method of transformer winding deformation detection

As one of the most important electrical equipment in power system, the stable operation of transformer is the key factor to ensure the safety of power grid system. Winding deformation is the most common fault of transformer, which will seriously affect the reliable operation of the whole power system. Therefore, the detection of transformer winding deformation is of great significance to prevent transformer accidents. In order to further improve the reliability of transformer winding deformation detection, this paper proposes a transformer winding deformation detection method based on oscillation wave method. Firstly, the equivalent circuit model of transformer winding is established, and the transformer winding fault is simulated by changing the inductance and capacitance parameters in the model, and the law between the change of oscillation wave curve and the change of related performance indexes and equivalent parameters is obtained. Finally, the field test verification is carried out on a 10 kV transformer in the laboratory. The results show that the oscillation wave method can diagnose the transformer winding deformation and can be used for the actual transformer winding deformation detection.

Analysis and Treatment of a Partial Discharge Fault in a 220kV Transformer

Abstract Partial discharge test of transformer is one of the most important detection items in the factory test of transformer, which is related to whether the transformer can operate safely and stably. This article will analyze a case of partial discharge exceeding the standard in a 220kV transformer. Based on the joint detection technology of ultrasonic partial discharge and ultra high frequency partial discharge, the defect location will be found. And the structure of the transformer will be researched to identify the cause of the defect. The diagnosis and treatment will be successfully completed. Finally, the conclusion will be verified through finite element analysis. This provides reliable guidance for partial discharge detection and rectification measures in transformers’ production and operation.

Analysis on Discharge Fault of Busbar in 220kV Gas Insulated Switchgear

Abstract In this paper, the disintegration of the 220kV gas insulated switchgear (GIS) basin-type insulator which discharge is occurred during the restoring power supply process of a 220kV transformer substation is introduced. The relay protection action is analyzed and the results of predelivery test are traced. Meanwhile, the electric field of the basin-type insulator is simulated and analyzed. Finally, the cause of discharge fault of basin-type insulator is determined.

Methodology for the optimal replacement of power transformers based on their health index

Transformer life is critical to ensuring the reliability and stability of the power system. However, making decisions about the optimal time to replace a transformer is challenging due to the complexity of the interactions between equipment aging and applied maintenance. This study employs a risk analysis method based on the health status of the equipment and the consequences of its failure to develop a mathematical optimization methodology aimed at identifying the optimal timing for transformer replacement or monitoring activities, thus facilitating effective preventive maintenance strategies. The methodology was developed in AMPL with the objective of minimizing the risk index of the transformer fleet, taking as a constraint a given annual budget. It was applied to a study case covering a period of six years for a fleet of 39 110 kV transformers using real data. The results presented show that the developed methodology provides valuable information to the power system operator who is thus able to manage the transformer fleet and ensure a safe and financially efficient operation of the grid, providing a list of the 10 most risky units and suggesting a replacement and improvement scheme for them.

Investigating temperature rise dynamics at hot-spots within dry-Type transformer windings: A comparative analysis across varied loading rates and an extrapolative computational model

The dynamic temperature data of a transformer can be utilized to accurately assess its load capability and operational longevity. This paper presents a study on the temperature rise characteristics of hot-spots in dry-type transformer windings and develops a extrapolative computational model based on various load rates, utilizing the results of transformer temperature rise tests. Firstly, the dynamic temperature rise characteristics of B-phase low-voltage (LV) winding and high-voltage (HV) winding hot-spot, along with its correlation calculation model with varying load rates, were determined based on the results of temperature rise tests. Subsequently, an extrapolative computational model for the temperature rise of the winding hot-spot, utilizing a three-section continuous load application approach, was proposed employing the lumped parameter method. The validity of this model was confirmed through verification. Lastly, a temperature rise test was conducted on another dry-type transformer to validate the universality of the model. Finally, a different dry-type transformer is chosen, and a temperature rise test is conducted to confirm the general applicability of the model. The results indicate that the calculation model for the hot-spot temperature rise of the winding under three consecutive loads is associated with the dynamic temperature rise pattern of the hot-spot of the winding between the temperature rise test with a small load rate and the temperature rise test with a large load rate. The maximum deviation between the hot-spot temperature rise test of the winding of SCB14-800/10-NX2 transformer and the results of the steady-state temperature rise value calculation is only 1.3 K, with a maximum error of the time constant value of the temperature rise being only 0.05 h. Similarly, the maximum deviation of the steady-state temperature rise value obtained from the hot-spot temperature rise test and the extrapolative computation of SCB-1250kVA/10 kV transformer winding is only 2.03 K, with a maximum error of the temperature rise time constant value being only 0.09 h. The extrapolative computational model proposed in this study conducts the temperature rise test under a small load rate instead of a large load rate, addressing the industry challenge of the challenging implementation of transformer on-site temperature rise tests and high power loss. This approach enhances inspection efficiency.

Analysis and application of suppression measures for protection misoperation caused by excitation inrush current of 15.75kV transformer

Abstract This article briefly described the mechanism of transformer magnetizing inrush current, and introduced the principle of differential protection magnetizing inrush current suppression of Siemens 7UT682 protection device. Through the analysis and research of a differential protection malfunction trip event when a no-load closing power of a overhauled transformer, the method of optimizing the relevant parameter configuration of the protection device to avoid the excitation inrush current was proposed and achieved good application results.

An analysis of circuit breaker capacity according to IEC 60909 and IEC 60059 standards at the PT Borneo Alumina Indonesia electrical system

At PT Borneo Alumina Indonesia (PT BAI), the D01 Power Distribution System uses circuit breakers (CB) with a current rating capacity of 1250A for both incoming and outgoing 10kV busbars. Replacing outgoing CBs with the same capacity during maintenance leads to unnecessary waste. This study was conducted to examine the appropriate CB capacity as a substitute for the old CBs in the outgoing 10 kV busbars for loads of 10 kV induction motors and transformers so that recommendations can be made to improve efficiency during maintenance on the D01 Power Distribution System. The Electronic Transient Analyzer Program (ETAP) 19.0.1 software was used to perform short circuit simulations based on IEC 60909 and load flow simulations, which were then adjusted to IEC 60059 and CB products from Siemens. The results show that we can replace the current Siemens CB, which has a rated breaking current specification of 31.5kA, with 25kA during the maintenance period. We can also replace the rated peak value of 80kA with 63kA, and the rated current of 1250A with 630A. Replacement of CB specifications does not change/modify the switchgear panel because the replacement CB matches the brand, dimensions, and size of the currently installed CB. These findings would also help increase efficiency during maintenance on the D01 Power Distribution System. The discussion includes limitations and recommendations for future research.

Enhancing rational approximation of wideband resonant MIMO systems with frequency-domain data

Vector Fitting (VF) is a successful methodology for both time and frequency domain estimation of dynamic systems. These algorithms have gained popularity as a system identification tool due to their ability to provide a practical procedure for accurately approximating the measured frequency response behavior of complex and highly resonant dynamic systems using rational models. Instrumental Variable (IV) techniques can also be added to the VF algorithm to enhance the optimality of the solutions in the presence of measurement noise. In this context, this paper presents a multiple-input multiple-output (MIMO) generalization of instrumental variable (IV-)VF. The proposed algorithm can be applied to accurately estimating models formed by either continuous- or discrete-time rational basis functions (RBFs). We show that such a generalization preserves the main implementation features observed in Standard VF, but with improved optimality property for its solutions. Additionally, in order to alleviate convergence problems that may arise from the fixed high-frequency normalization, we also present in this paper how to incorporate in the proposed IV-VF method the relaxed formulation found in standard VF for both the continuous and discrete-time cases. The resulting MIMO IV-VF algorithm can be easily understood by VF users, and its applicability is discussed by using an estimation case study with two power system pieces of equipment (an 88 kV Transformer and a 550 kV Instrument Transformer) for which actual frequency domain measurements were collected in the field. It is shown that the proposed algorithm significantly improves the modeling accuracy when compared to standard VF algorithms.

Identification method for inter-turn faults in transformers based on digital twin concept

A transformer inter-turn fault identification method is proposed based on the digital twin concept to tackle the challenges of high operational complexity and low accuracy associated with traditional transformer fault identification methods. Initially, the Bald Eagle Search algorithm is employed to optimize the critical parameters of the Extreme Learning Machine (ELM), determining the optimal input layer weight and hidden layer threshold of the Extreme Learning Machine. Subsequently, leveraging the digital twin concept, a digital replica of the physical transformer is established, enabling multi-physical field coupling simulation encompassing electrical, thermal, and acoustic domains to elucidate the variation patterns of various physical parameters across different operational scenarios and fault scenarios. Furthermore, key physical characteristic parameters such as sound pressure and winding hot spot temperature are carefully selected to drive a fault identification model tailored to inter-turn faults within the framework of the digital twin concept. Through a detailed investigation using 630 kV A/10 kV transformers as a case study, the results exhibit an impressive fault identification accuracy of 95.24% for the proposed method. Comparative analysis reveals notable enhancements in fault identification accuracy of 12.22%, 7.85%, and 3.73% for ELM, Support Vector Machine and Tuna Swarm Optimization—ELM models, respectively. These findings underscore the effectiveness and practicality of the transformer inter-turn fault identification method based on the digital twin concept, offering valuable insights for the real-time monitoring and diagnosis of inter-turn faults in transformers.

Fault diagnosis and analysis of a 110 kV transformer

This paper aims to provide valuable insights and assistance for ensuring the safe operation of a 110 kV main transformer by conducting an in-depth analysis of tap changer breather oil leakage defects. By employing transformer testing, disassembly analysis, and other methods, this study successfully identifies and prevents the possibility of transformer failure. The analysis reveals that the deformation of the transformer winding is caused by insufficient short-circuit resistance, which leads to the deformation of the medium-voltage windings under the continuous action of electrodynamic forces during near-area short-circuit currents. Near-area short-circuits are a significant contributing factor to transformer failures. Therefore, it is recommended to enhance operation and maintenance management for older main transformers and optimize protection settings to reduce the risk of near-area short-circuit failures, thus ensuring the safe and stable operation of the main transformer.