Empirical Thermal Investigation of Oil-Immersed Distribution Transformer under Various Loading Conditions

The distribution transformer is the mainstay of the power system.Its internal temperature study is desirable for its safe operation in the power system.The purpose of the present study is to determine direct comprehensive thermal distribution in the distribution transformers for different loading conditions.To achieve this goal,the temperature distribution in the oil,core,and windings are studied at each loading.An experimental study is performed with a 10/0.38 kV,10 kVA oil–immersed transformer equipped with forty–two PT100 sensors(PTs)for temperature measurement installed inside during its manufacturing process.All possible locations for the hottest spot temperature(HST)are considered that made by finite element analysis(FEA)simulation and losses calculations.A resistive load is made to achieve 80%to 120%loading of the test transformer for this experiment.Working temperature is measured in each part of the transformer at all provided loading conditions.It is observed that temperature varies with loading throughout the transformer,and a detailed map of temperature is obtained in the whole test transformer.From these results,the HST stays in the critical section of the primary winding at all loading conditions.This work is helpful to understand the complete internal temperature layout and the location of the HST in distribution transformers.

Digital Transformation Trend of the Pharmaceutical Distribution Industry in the Context of New Infrastructure in China

Objective To study the pharmaceutical distribution industry against the background of new infrastructure construction since it is vital to the health and life of the public,and to offer some suggestions to further improve the industry quality and achieve industry upgrading.Methods The national strategies for new infrastructure as well as the underlying logic for enterprise digital transformation were analyzed to provide the outlook on the digital transformation trend of the pharmaceutical distribution industry.Results and Conclusion In the future,the pharmaceutical distribution industry shall transform the pattern,channel,management and control,and experience in the entire business chain in a digital way by focusing on connection efficiency,data efficiency and decision-making efficiency.

Brain Functional Network Generation Using Distribution-Regularized Adversarial Graph Autoencoder with Transformer for Dementia Diagnosis

The topological connectivity information derived from the brain functional network can bring new insights for diagnosing and analyzing dementia disorders.The brain functional network is suitable to bridge the correlation between abnormal connectivities and dementia disorders.However,it is challenging to access considerable amounts of brain functional network data,which hinders the widespread application of data-driven models in dementia diagnosis.In this study,a novel distribution-regularized adversarial graph auto-Encoder(DAGAE)with transformer is proposed to generate new fake brain functional networks to augment the brain functional network dataset,improving the dementia diagnosis accuracy of data-driven models.Specifically,the label distribution is estimated to regularize the latent space learned by the graph encoder,which canmake the learning process stable and the learned representation robust.Also,the transformer generator is devised to map the node representations into node-to-node connections by exploring the long-term dependence of highly-correlated distant brain regions.The typical topological properties and discriminative features can be preserved entirely.Furthermore,the generated brain functional networks improve the prediction performance using different classifiers,which can be applied to analyze other cognitive diseases.Attempts on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset demonstrate that the proposed model can generate good brain functional networks.The classification results show adding generated data can achieve the best accuracy value of 85.33%,sensitivity value of 84.00%,specificity value of 86.67%.The proposed model also achieves superior performance compared with other related augmentedmodels.Overall,the proposedmodel effectively improves cognitive disease diagnosis by generating diverse brain functional networks.

基于Transformer的数据中心机房三维温度场快速重构和预测方法

机房内部气流组织的合理性关系到数据中心制冷系统的能耗、IT设备的性能和热环境的安全。传统气流组织模拟性能一般在小时级,使用场景受限,难以满足实时运营对机房温度场预测的时效性需求。提出一种基于Transformer的机房三维温度场快速重构和预测方法,通过融合深度学习模型与传统CFD,将气流组织预测时间降低至分秒级,全局平均预测精度误差控制在5%以内,从而使CFD仿真有效地从设计阶段应用到运维阶段,支撑数据中心的智慧运营业务。

基于CNN-Swin Transformer的分布式超宽带雷达人体动作识别

针对传统雷达人体动作识别方法中特征提取能力不足和上下文建模困难的问题,提出了一种结合卷积神经网络(Convolutional Neural Network, CNN)和Swin Transformer的网络模型,用于有效识别分布式脉冲超宽带雷达数据中的人体动作。通过多分支的CNN对多个雷达的多个谱图、雷达数据的幅度和相位等特征进行提取和融合,利用Swin Transformer模块的多层自注意力机制对生成的特征映射进行上下文建模,提取具有高级语义信息的特征。采用代尔夫特理工大学(Technische Universiteit Delft)公开的数据集进行5折交叉验证,结果表明所提方法能够有效识别9类连续人体动作,识别准确率达到98.2%。

基于Transformer的电力故障分类系统探究

配电系统易受外部环境影响,在时空尺度上对潜在故障风险进行分类,对于制订配电系统维护与检修计划,以提高整个配电系统的可靠性至关重要。针对配电系统数据的时空分布不平衡问题,提出了一种基于Transformer模型和注意力机制的配电系统故障风险动态分类模型,旨在对故障结果、故障原因和故障位置进行预测,并结合多种特征属性进行综合分析。实验结果表明,该模型在不同故障的分类任务中表现优异,特别是在捕捉自然因素引起的故障方面展现出显著优势。这项研究不仅进一步证实了自注意力机制和位置编码在提高模型性能方面的核心作用,还充分体现了它们在配电系统数据分析领域中的实用价值。

Exploring a New Lifetime Distribution for Modelling the Waiting Time of Bank Customers

The fitting of lifetime distribution in real-life data has been studied in various fields of research. With the theory of evolution still applicable, more complex data from real-world scenarios will continue to emerge. Despite this, many researchers have made commendable efforts to develop new lifetime distributions that can fit this complex data. In this paper, we utilized the KM-transformation technique to increase the flexibility of the power Lindley distribution, resulting in the Kavya-Manoharan Power Lindley (KMPL) distribution. We study the mathematical treatments of the KMPL distribution in detail and adapt the widely used method of maximum likelihood to estimate the unknown parameters of the KMPL distribution. We carry out a Monte Carlo simulation study to investigate the performance of the Maximum Likelihood Estimates (MLEs) of the parameters of the KMPL distribution. To demonstrate the effectiveness of the KMPL distribution for data fitting, we use a real dataset comprising the waiting time of 100 bank customers. We compare the KMPL distribution with other models that are extensions of the power Lindley distribution. Based on some statistical model selection criteria, the summary results of the analysis were in favor of the KMPL distribution. We further investigate the density fit and probability-probability (p-p) plots to validate the superiority of the KMPL distribution over the competing distributions for fitting the waiting time dataset.

Reduction of Vibration Noise for Amorphous Metal Alloy Core Distribution Transformer

To understand the vibration noise behaviors of amorphous metal alloy core distribution transformer(AMACDT), a 10 k VA prototype was tested under no-load and short-circuit conditions, respectively. The vibration characteristics were described when rated voltage was applied to the secondary side, and the primary side was connected with different load resistances. The largest amplitude positions on the upper bracket and tank surfaces were recorded by vibration sensors arranged on the surface. A data-acquisition platform was set up for signal measurement. The vibration amplitude related to frequency was discussed, and experimental results indicated that the position with the largest amplitude accrued in the middle of the upper bracket and tank surface, at phases a and c, respectively. The experimental results suggest that magnetostrictive and electrodynamic forces play a major role in exciting the vibration noise. At the same time, some rib-reinforcements were welded on the upper bracket and tank surfaces to lessen the vibration energy, which reduced the noise.

A modified lumped parameter model of distribution transformer winding

The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction.A distributed parameters model can depict the winding characteristics accurately,but it requires complex calculations.Lumped parameter model requires less calculations,but its applicable frequency range is not wide.This paper studies the amplitude-frequency characteristics of the lightning wave,compares the transformer modelling methods and finally proposes a modified lumped parameter model,based on the above comparison.The proposed model minimizes the errors provoked by the lumped parameter approximation,and the hyperbolic functions of the distributed parameter model.By this modification it becomes possible to accurately describe the winding characteristics and rapidly obtain the node voltage response.The proposed model can provide theoretical and experimental support to lightning protection of the distribution transformer.

Research on power electronic transformer applied in AC/DC hybrid distribution networks

The AC/DC hybrid distribution network is one of the trends in distribution network development, which poses great challenges to the traditional distribution transformer. In this paper, a new topology suitable for AC/DC hybrid distribution network is put forward according to the demands of power grid, with advantages of accepting DG and DC loads, while clearing DC fault by blocking the clamping double sub-module(CDSM) of input stage. Then, this paper shows the typical structure of AC/DC distribution network that is hand in hand. Based on the new topology, this paper designs the control and modulation strategies of each stage, where the outer loop controller of input stage is emphasized for its twocontrol mode. At last, the rationality of new topology and the validity of control strategies are verified by the steady and dynamic state simulation. At the same time, the simulation results highlight the role of PET in energy regulation.

A Temperature Prediction Model for Oil-immersed Transformer Based on Thermal-circuit Theory

This paper proposed an improved temperature prediction model for oil-immersed transformer.The influences of the environmental temperature and heat-sinking capability changing with temperature were considered.When calculating the heat dissipation from the transformer tank to surroundings,the average oil temperature was selected as the node value in the thermal circuit.The new thermal models will be validated with the delivery experimental data of three transformers: a 220 kV-300 MV.A unit,a 110 kV40 MV.A unit and a 220 kV-75 MV.A unit.Meanwhile,the results from the proposed model were also compared with two methods recommended in the IEC loading guide.

Adjustment of Model Parameters to Estimate Distribution Transformers Remaining Lifespan

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.

Influence of Series Choke on Damping of Switching Transients in Distribution Transformers

Distribution transformers operating in modern system grids or in industrial networks are subjected to many switching transients,which may occur due to routine operations,network reconfigurations or as reaction on protection signals.Depending on the network configuration and parameters,such events may lead to external overvoltages and result in additional stresses on the insulation system.This paper presents the influence of a series choke on damping of switching transients in distribution transformers.The impact of the choke is assessed by both amplitude and rise time reduction.The suppression of the transient rise time is shown for a test configuration involving distribution transformers connected to low loss cable lines and a medium voltage breaker.Such phenomena are especially typical for industrial networks where switching operations are very frequent.Both simulation and experiment results are given.Simulation results as well as measurement results confirmed that switching events can lead to high dU/dt and in consequence,can have adverse impacts on insulation system.Voltage escalation during switching event is strongly related with system conditions.The results obtained for presented mitigation method are promising and indicate significant dU/dt reduction as well as number of ignitions and voltage peak value.The protection of distribution transformers with a series choke is a new approach dedicated to environments prone to the occurrence of transients with high steepness.Experimental results show that the application of serial choke with suitable parameters realizes the reduction of dU/dt at the machines terminal from 24 kV/μs to 5 kV/μs,as well as the reduction of voltage peak value from 10 kV to 5 kV.The number of ignitions is also reduced.

Method for Caution Values Calculation of Dissolved Gases in Transformers Based on Statistical Distribution and Correlation Analysis

Before diagnosed by DGA (dissolved gas analysis) methods, gas caution values, which index the level of gas formation, must be used to evaluate the possibility of incipient faults to reduce the misdiagnosis in the normal state. However, the calculation of these values is now only based on cumulative percentile method without taking into account operating conditions. To overcome this disadvantage, a new approach to calculate the transformer caution values is presented. This approach is based on statistical distribution and correlation analysis, and it takes the individual variation and fluctuation caused by internal and external factors into consideration. Then 6550 transformer DGA data collected from North China Power Grid are analyzed in this paper. The results show that the volume fraction of TH (total hydrocarbon) approximately obeys normal distribution when the 3-sigma rule is used to calculate its caution value. The volume fraction of CO has a strong positive correlation with oil temperature. For H2, the negative correlation with oil temperature is significant when the volume fraction is not very low. The caution value curves for CO and H2 are obtained by regression analyses. Thus, the gas caution values/curves obtained using the new method are not always constant, but vary with oil temperature, which is an advantage of the proposed method compared with cumulative percentile method. The variation of gas caution values/curves also reflects the influence of the external factors, for instance, va- rying with monitoring time ensures that the gas caution values are always consistent with operating status.

Low-loss B18R065 and B20R070 grain oriented electrical steels for grade 1 energy efficiency distribution transformers

To reduce distribution transformer losses and carbon dioxide emissions, in recent years, the major countries in the world have issued mandatory standards for high-energy efficiency in distribution transformers. In 2013,China has carried out a new standard GB 20052-2013. To meet the update of the standard and energy efficiency,it is important to enhance the magnetic properties of core materials. The new products B18R065 and B20R070 which are developed by Baosteel, are successfully used for grade 1 energy efficiency distribution transformers. And Baosteel becomes one of the companies which can supply both the 0.20 mm and the 0.18 mm gauge grain oriented electrical steels （GOES） in the world. The development principle, material properties, and transformer performance of B18R065 and B20R070 were introduced,which were expected to be a useful reference for materials selection by transformer manufacturers.

The Investigation of Replacing Ceramic Bushings with Silicon Bushings in the Distribution Transformers

In recent years, the deficiencies of ceramic insulators along with their high maintenance costs have resulted in the replacement of ceramic insulators with silicon type in the pollution area. This idea has been employed for more than two decades in the polluted areas. Humidity of the weather in the south of Iran and the presence of pollutants in the air have made special conditions for construction and maintenance of some equipment including transformer bushings. Usual ceramic bushings, due to their ability in absorbing pollution and the rapid reduction of creepage distance (in a limited time period), have reduced transformer disconnection severely as a result of earth fault. Additionally, they are costly to be washed regularly. Therefore, using intelligent materials in designing bushing can increase the reliability of network and consequently reduction of costs. In this regard, this paper investigates the use of silicon bushings in the distribution systems and proposes operational ideas for the optimal operation of these devices in the polluted areas. The sample bushing was evaluated based on the IEC60137 standard test.

Voltage Profile Enhancement and Power Loss Reduction with Economic Feasibility Using Small Capacity Distribution Transformers

Usually,rural areas can be electrified via three-phase distribution transformers with relatively large capacities.In such areas,low voltage lines are used for long distances,which cause power losses and voltage drop for different types of consumers.Reducing losses and improving voltage profiles in rural distribution networks are significant challenges for electricity distribution companies.However different solutions were proposed in the literature to overcome these challenges,most of them face difficulties when applied in the conventional distribution network.To address the above issues,an applicable solution is proposed in this paper by installing a number of small-capacity distribution transformers instead of every single large-capacity transformer in rural areas.The proposed approach is implemented in the branch network of Al-Hoqool village,which belongs to the Nineveh distribution network.The network has been inspected on-site,drawn,and analyzed using the electrical systems analysis program(ETAP).The analysis showed that using the single-phase pole-mounted transformers can improve the voltage in the network’s end by 29%and enhance the voltage profile for all consumers.The analysis has also demonstrated that the modification can reduce the total power losses by 78%compared to the existing network.Concerning the economic aspect,the payback period for the proposed network is assigned to be 20 months.

Role of Energy Storage on Distribution Transformer Loading in Low Voltage Distribution Network

Energy storage (ES) is a form of media that store one form of energy to be utilized at another time. Importance of ES is comprehended while intermittent nature of renewable energy (RE) generation increases and integration into the grid becomes viable in terms of economics and environment. However, technical analysis should be carried out before large scale integration into the grid. Some utilities experienced in Europe and expressed concern about issues in integrating large scale renewable energy in the areas of harmonics, voltage regulation, network protection and islanding. In Australia, distribution network (DN) is not robust compared to the European grid;moreover loads are largely distributed over large geographical areas. Installation of RE such as roof top solar photovoltaic (PV) is increasing in Australia which also boosted by the governments incentives to the individual owners. It is therefore obvious that large scale PV integration into the Australian grid is imminent. The intermittent characteristic of solar PV is expected to have greater impacts on DN in Australia compared to the DN in Europe. Therefore this paper investigated the impacts of solar PV on low voltage (LV) DN where loads connected through distribution transformer (DT) and finally further investigation was conducted with the deployment of ES into the respective load centers. It was found that storage reduced the overall peak load condition on the DT, and also reduced the energy fluctuation in the DN. It was also found that storage improved the voltage regulation on the LV side of DT and stabilized node voltage.

Investigation on Noise Pollution Comprehensive Treatment of Distribution Transformer in Living Area

In the current paper,which deals with the noise pollution excited by distribution transformers in the living area,a comprehensive treatment scheme is put forward for the purpose of reducing the sound pressure level emitting into the environment.In accordance with the associated test standard,the sound pressure levels of distribution transformer and surrounding environment are not only tested but analyzed as well.The measurements were carried out with the frequency analysis of the 1/3 octave resolution,with the center frequencies at 125 Hz,250 Hz,400 Hz,and 500 Hz.As illustrated,on the basis of the measurement results,the frequency of noise at 500 Hz of distribution transformer causes the major noise pollution in the surrounding environment.This measurement result is in line with the noise frequency characteristics of distribution transformer.There are two transmission routes of noise:(i)the noise excited by distribution transformer transmits by means of the wall of distribution room,and (ii)part of noise spreads through the ground of distribution room.Accordingly,acoustic shield and vibration isolation device are applied for the reduction of the low frequency noise emitted through the above two paths.Aimed at applying the appropriate acoustic material and vibration mounting,the evaluation of the noise reduction and vibration absorption is carried out in accordance with the sound and vibration insulation theory.Following the noise treatment,the transformer and environment noise are measured again.The corresponding findings shed light on the fact that the sound level satisfied the requirement of limits of the ordinance.The proposed noise treatment scheme can be applied to the existing power distribution facilities for controlling the sound levels that reach a point where it is comparatively more unobjectionable.

Management of Charging Load of Electric Vehicles for Optimal Capacity Utilisation of Distribution Transformers

A de-centralised load management technique exploiting the flexibility in the charging of Electric Vehicles (EVs) is presented. Two charging regimes are assumed. The Controlled Charging Regime (CCR) between 16:30 hours and 06:00 hours of the next day and the Uncontrolled Charging Regime (UCR) between 06:00 hours and 16:30 hours of the same day. During the CCR, the charging of EVs is coordinated and controlled by means of a wireless two-way communication link between EV Smart Charge Controllers (EVSCCs) at EV owners’ premises and the EV Load Controller (EVLC) at the local LV distribution substation. The EVLC sorts the EVs batteries in ascending order of their states of charge (SoC) and sends command signals for charging to as many EVs as the transformer could allow at that interval based on the condition of the transformer as analysed by the Distribution Transformer Monitor (DTM). A real and typical urban LV area distribution network in Great Britain (GB) is used as the case study. The technique is applied on the LV area when its transformer is carrying the future load demand of the area on a typical winter weekday in the year 2050. To achieve the load management, load demand of the LV area network is decomposed into Non-EV load and EV load. The load on the transformer is managed by varying the EV load in an optimisation objective function which maximises the capacity utilisation of the transformer subject to operational constraints and non-disruption of daily trips of EV owners. Results show that with the proposed load management technique, LV distribution networks could accommodate high uptake of EVs without compromising the useful normal life expectancy of distribution transformers before the need for capacity reinforcement.