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The traditional real-time load warning method for distribution transformers has problems such as low recall rate, low warning accuracy, and long warning time, which may lead to potential equipment failures or overload situations not being detected and dealt with in a timely manner, increasing the safety risk of transformer operation and potentially causing safety issues such as equipment damage, fire, or power outage. Therefore, a real-time early warning method of distribution transformer load considering meteorological factor data is designed. The meteorological factor data are collected by the light sensor, humidity sensor, temperature sensor and rainfall sensor, and the load data collection architecture is built by the load monitor, central master station and maintenance station to realize the load data collection of the distribution transformer. The K-nearest neighbor (KNN) method is used to process the missing values of the data, and the LOF algorithm is used to determine the local outliers and eliminate the outliers in the data set to achieve data cleaning. Considering the load loss, hot spot temperature and meteorological factors of the distribution transformer, an early warning model is built, and the cleaned data are input into the model to realize Real-time early warning of the distribution transformer load. The experimental results show that the recall rate of this method varies from 95% to 97%, the accuracy rate of early warning is always above 94%, and the maximum value of early warning time is 0.63s. Having good early warning ability. [ABSTRACT FROM AUTHOR]

In an electrical power distribution system, harmonic distortion is the most prominent power quality problem that causes long-term adverse effects such as failure of distribution transformers. Considering that most transformer problems are caused by heat losses due to the presence of harmonics, it was decided to use a numerical method with the highest accuracy, finite element method (FEM) to analyze the hot spot temperature (HST) of the thermal distribution transformer model. Through the use of COMSOL Multiphysics software, three phases of unbalanced harmonic loads are considered, which contribute to three different total harmonic distortion current (THDI) levels and five different insulation temperature classes. Using the IEEE C57.110-2018 guidance, the simulation outputs are then verified with HST results from the HST mathematical model. The findings indicated that with the increased loadings, the unbalanced harmonic currents have impacted the HST increment and distinguished the HST values between the phases. [ABSTRACT FROM AUTHOR]

In order to precisely ascertain the temperature at the hot spot within the intermediate joint of a three-core cable, this study focused on a 10 kV three-core cable joint as its primary subject. A three-dimensional finite element model of the cable joint was constructed, enabling the calculation of both the steady-state hot spot temperature field distribution and the transient temperature rise curve of the joint. Employing a one-dimensional transient thermal path model for the cable body, a radial inversion model for the cable core temperature was established. Through simulating the transient temperature field of the cable joint under varying currents, a fitting relationship was determined for the axial temperature points of the cable core. Subsequently, an inversion perception model was devised to calculate the hot spot temperature of the cable joint based on temperature measurements at specific points on the outer surface of the cable. Under both continuous and periodic loads, the inversion results revealed a consistent trend in the temperature at the joint crimping point with the finite element calculation outcomes, demonstrating a maximum error of within 3 degrees Celsius. This verification underscores the precision of the temperature combination inversion method when applied to three-core cable joints. [ABSTRACT FROM AUTHOR]

In this paper, models to predict hot spot temperature and to estimate cooling air's working parameters of racks in data centers were established using machine learning algorithms based on simulation data. First, simulation models of typical racks were established in computational fluid dynamics (CFD). The model was validated with field test results and results in literature, error of which was less than 3%. Then, the CFD model was used to simulate thermal environments of a typical rack considering different factors, such as servers' power, which is from 3.3 kW to 20.1 kW, cooling air's inlet velocity, which is from 1.0 m/s to 3.0 m/s, and cooling air's inlet temperature, which is from 16 °C to 26 °C The highest temperature in the rack, also called hot spot temperature, was selected for each case. Next, a prediction model of hot spot temperature was built using machine learning algorithms, with servers' power, cooling air's inlet velocity and cooling air's inlet temperature as inputs, and the hot spot temperatures as outputs. Finally, based on the prediction model, an operating parameters estimation model was established to recommend cooling air's inlet temperatures and velocities, which can not only keep the hot spot temperature at the safety value, but are also energy saving. [ABSTRACT FROM AUTHOR]

Transformer performance and efficiency can be enhanced by effectively address the properties of its insulation system. The power transformer insulation system weakens as a result of operational thermal stresses brought on by dynamic loading and shifting environmental patterns. Winding hot spot temperature is a crucial metric that must be maintained below the prescribed limit while power transformers are operating so as to maintained power system reliability. This is due to the fact that, among other variables, the time-dependent aging effect of insulation depends on transitions in hot spot temperatures. Due to the non‐linear nature of the conventional mathematical models used to determine these temperatures, and complexity of thermal phenomena, investigations still need to be exercised to fully understand the variables that associate with hot spot temperature computation with minimum error. This paper explores the possibilities of enhancing top oil and hot spot temperature estimation accuracy through the use of an adaptive neuro-fuzzy inference (ANFIS) technique. The paper presents an adaptive neuro fuzzy model to approximate the hot spot temperature of a mineral oil-filled power transformer based on loading, and established top oil temperature. Initially, a sub-ANFIS top oil temperature estimation model based on loading and ambient temperature as inputs is established. Using a hybrid optimization technique, the ANFIS membership functions were fine-tuned throughout the training process to reduce the difference between the actual and anticipated outcomes. The correctness and reliability of the created adaptive neural fuzzy model have been verified using real-world field data from a 60/90MVA, 132 kV power transformers under dynamic operating regimes. The ANFIS model results were validated against field measured values and literature-based electrical-thermal analogous models, establishing a precise input-output correlation. The developed ANFIS model achieves the highest coefficient of determination for both TOT and HST (0.98 and 0.96) and the lowest mean square error (7.8 and 10.3) among the compared thermal models. Correct determination of HST can help asset managers in thermal analysis trending of the in-service transformers, helping them to make proper loading recommendations for safeguarding the asset.

With the rising penetration of photovoltaic (PV) plants on low voltage distribution systems, the generation of current harmonics as well as its impact on transformer operation is a current concern. The present research work develops a mathematical relationship of solar intensity (I(t)) with PV-inverter-generated total harmonic distortion of current (THDi,inv.), and then uses IEEE recommendations to present the impact of THDi,inv. on the life of a three-phase distribution transformer (TPDT). The validation of the presented model is done by real-time data monitoring from a 100-kWp solar roof-top photovoltaic (SRTPV) system, integrated with an 11-kV grid supply through a 63-kVA TPDT in the composite environment of north India. According to the results, decreasing I(t) values from 857 W/m² to 35 W/m² raise THDi,inv. from 3.57% to 63.43%. It is also observed that the production of poor THDi,inv. is high in the winter season (daily average = 27.44%) in comparison to their values in the summer season (daily average = 15.21%). For I(t) values less than 315 W/m², the generation of large THDi,inv. (above 15%) takes place and it increases the loss of life of TPDT by a factor of 6.0. [ABSTRACT FROM AUTHOR]

In order to study the characteristics of small helium-xenon cooled nuclear reactor that only relies on natural circulation to remove residual heat after shutdown, this paper carries out geometric and physical modeling of helium-xenon cooled nuclear reactor, and uses CFD to simulate the process of natural circulation residual heat removal. Variation laws of the hot spot temperature on the surface of fuel cladding and the mass flow of helium-xenon mixed gas under different working conditions are calculated, and the transient characteristics of temperature, flow and other related parameters in the system loop are analyzed. The calculation results show that during the natural circulation residual heat removal process, the overall change trend of the hot spot temperature on the surface of the fuel cladding, the average temperature of the primary coolant and reactor outlet temperature first rises to the highest value and then decreases, and the mass flow of helium-xenon mixed gas shows an exponential decay trend; Increasing the initial mass flow of helium-xenon mixed gas and reducing the residual heat of the reactor core can reduce the maximum hot spot temperature on the surface of the fuel cladding. The relevant research results provide a useful reference for the optimal design of natural circulation residual heat removal of helium-xenon cooled nuclear reactor.

The design of medium- to high-frequency power electronics transformer aims not only to minimize the power loss in the windings and the core, but its heat removal features should also allow optimal use of both core and copper. The heat removal feature (e.g., thermal conduction) of a transformer is complex because there exist multiple loss centers. The bulk of total power loss is concentrated around a small segment of the core assembly where windings are overlaid. The primary winding is most constrained thermally. For superior use of core and copper, the temperature rise in different segments of the transformer should be well below their respective safe operating limits. In practice, cores of same soft-magnetic materials are traditionally used. To achieve superior temperature profile and for better long-term performance, this article proposes to use the mixed-core configuration. The new core(s) would replace the parent ones from the segment where windings are laid. The characteristic features of new cores would share increased burden of heat removal from the transformer. To obtain the qualitative insight of magnetic and thermal performance, the proposed mixed-core transformer would be thoroughly validated practically in two different high-power applications. In the first case, the core is always energized to its rated value, and in the second one, windings are always energized at respective rated current capacity.

An accurate estimation model of winding hot spot temperature is the key to assess the thermal state and insulation life of oil-immersed transformers. Based on the hot spot temperature and load current monitored by the substation,the genetic programming algorithm is applied to train the basic structure of the hot spot temperature estimation model. Then,the parameter identification of the hot spot temperature estimation model is performed by the normalized least square mean (NLMS) algorithm. Finally,an explicit prediction model of the hot spot temperature is established for oil-immersed transformers. The explicit winding hot spot temperature estimation model can effectively reflect the relationship between the load factor and the winding hot spot temperature. Moreover,the goodness of fit of the model under the test set is 0.998 8,and the maximum absolute error is only 1.36 ℃,which verify the correctness and effectiveness of the model. Furthermore,the strong generalization performance of the proposed model is proved by estimating the winding hot spot temperature for oil-immersed transformers with the same capacity and model in the same area.

The variation in daily environmental conditions has a notable effect on the thermal performance of the electrical machines, especially power transformers. The objective of this paper is to see the effect of solar radiation and wind flow external to the outdoor operating power transformers. The research work in this field involves the development of computational thermal models based on conventional International Electro-technical Commission (IEC) loading guide using appropriate software tools in order to determine the hot spot temperature. These thermal models are then modified by incorporating the effect of solar radiation and wind flow. The proposed method is validated using the operational data gathered from a 500MVA power transformer located at 400kV Grid Substation, Kankani, Jodhpur (Rajasthan, India). The comparative study between the conventional and modified thermal models helps in the reliable operation of power transformer and optimizes the use of forced cooling arrangements. [ABSTRACT FROM AUTHOR]

The winding and core of amorphous alloy transformer generally adopt rectangular structure. The unbalanced temperature rise caused by operating loss is more likely to lead to winding insulation deterioration and affect the reliability of power supply. For the special winding structure of amorphous alloy transformer, the temperature rise of amorphous alloy transformer winding was analyzed and calculated, and the hot spot temperature was predicted, which had theoretical guiding significance for the design optimization and operation control of rectangular winding structure transformer. Based on the three-dimensional magnetic-thermal-flow multi-physics coupling simulation and temperature rise test, a three-phase oil-immersed amorphous alloy distribution transformer with SBH15-M-200/10 was taken as the research object. The operation characteristics under rated load were analyzed, and the hot spot temperature of each winding was simulated. The correctness of the simulation results was verified by short-circuit temperature rise test. The results show that the relative error between the hot spot temperature of amorphous alloy transformer winding calculated by three-dimensional magnetic-thermal-flow multi-physical field coupling and the temperature rise test results is not more than 5%. The hot spot temperature of amorphous alloy transformer winding studied appears in the middle and upper part of phase B low voltage winding, and the hot spot temperature reaches 64.77 ℃. [ABSTRACT FROM AUTHOR]

The hot spot temperature (maximum temperature) is one of the main concerns for thermal devices due to its severe impacts on thermal reliability in actual operation. To alleviate the negative impact of hot spot temperature, a combined system of the vibrating blade (VB) and the vortex generator (VG) is proposed. The heat dissipation mechanism is revealed from the viewpoint of longitudinal and transverse vortices. The corresponding experiments are conducted to verify the reliability of the numerical results. The results show that the near-wall vortices enhance the localized turbulent kinetic energy and airflow velocity, which is the key factor for heat dissipation improvement. The vibrating blade can form high-intensity longitudinal vortices, and these vortices move forward under the action of the incoming flow. The vortex generator of 30° further induces these vortices to form more secondary longitudinal vortices, significantly reducing the hot spot temperature downstream of the heated surface. Therefore, the channel with VB + VG(30°) can significantly reduce the hot spot temperature by 14.2 °C and improve comprehensive heat transfer by 33.9%, compared to the smooth channel. It is also found that the combined system performs better in low-velocity channel flow, reducing hot spot temperatures by up to 32.4 °C. • A combined system of a vibrating blade and the vortex generator is developed. • The combined system effectively reduces hot spot temperatures. • The channel with VB + VG(30°) reduces the T max by 14.2 °C than the smooth channel. • The heat dissipation mechanism is revealed from the viewpoint of vortex evolution. • The combined system performs better heat dissipation at lower d and v in. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The design of medium- to high-frequency power electronics transformer aims not only to minimize the power loss in the windings and the core, but its heat removal features should also allow optimal use of both core and copper. The heat removal feature (e.g., thermal conduction) of a transformer is complex because there exist multiple loss centers. The bulk of total power loss is concentrated around a small segment of the core assembly where windings are overlaid. The primary winding is most constrained thermally. For superior use of core and copper, the temperature rise in different segments of the transformer should be well below their respective safe operating limits. In practice, cores of same soft-magnetic materials are traditionally used. To achieve superior temperature profile and for better long-term performance, this article proposes to use the mixed-core configuration. The new core(s) would replace the parent ones from the segment where windings are laid. The characteristic features of new cores would share increased burden of heat removal from the transformer. To obtain the qualitative insight of magnetic and thermal performance, the proposed mixed-core transformer would be thoroughly validated practically in two different high-power applications. In the first case, the core is always energized to its rated value, and in the second one, windings are always energized at respective rated current capacity. [ABSTRACT FROM AUTHOR]

In this paper, the CFD model is established for the low voltage winding region of an oil-immersed transformer according to the design parameters, and the detailed temperature distribution within the region is obtained by numerical simulation. On this basis, the response surface methodology is adopted to optimize the structure parameters with the purpose of minimizing the hot spot temperature. After a sequence of designed experiments, the second-order polynomial response surface and the support vector machine response surface are established, respectively. The analysis of their errors shows that the support vector machine response surface can be better used to fit the approximation. Finally, the particle swarm optimization algorithm is employed to get the optimal structure parameters of the winding based on the support vector machine response surface. The results show that the optimization method can significantly reduce the hot spot temperature of the winding, which provides a guiding direction for the optimal design of the winding structure of transformers. [ABSTRACT FROM AUTHOR]

The heat conduction optimization problem is a widely investigated abstraction of various heat dissipation problems in industry and electronics cooling. This paper studies the optimization strategy that produces optimized heat conduction path made of high thermal conductivity materials, with the objective of lowering the hot spot temperature or improving temperature uniformity. The automatic differentiation (AD) technique is a general-purpose method to calculate the partial derivatives of any continuous function composed by elementary functions with respect to multiple independent variables. It is introduced to calculate the gradient of the objective function with respect to the thermal conductivity field, so that the optimization procedure can be guided directly towards the minimization of the desired objective function. This paper investigated the configurations of both continuous-value thermal conductivity and discrete-value thermal conductivity. Results indicate that the present optimization strategy is able to handle various types of boundary conditions and objective functions. The present method is compared with the iterative method based on variational principle (Var), showing that the AD method performs better than the Var method in most situations. • A strategy to generate efficient heat conduction path is proposed. • No manually designed operating rule is required during optimization. • Hot spot temperature is reduced and temperature uniformity is increased. • The present method can be used for various boundary conditions. • The present method performs better than previous method in most cases. [ABSTRACT FROM AUTHOR]

Hot spot temperature (HST) is an important parameter reflecting the working state of the traction transformer, and the load characteristics have a great influence on the HST. The current researches rarely consider the load characteristics of transformers in-depth, and most of the research on the temperature field focuses on steady load. Therefore, a prediction model of HST for the traction transformer considering the load characteristics is established by the finite element simulation in this paper. Considering the impact and nonlinearity of traction load, the influence of the load characteristics on the HST is studied. Analysis of the load curve revealed that the steady and step load combination could well simulate the traction load. Based on the analysis of traction transformer load characteristics, the temperature field coupling calculation of traction transformer is carried out according to the VI normative duty class. On this basis, the influence of load rate and time on HST is studied. The present findings show that the method can predict the HST of traction transformer under different working conditions and provide a reference for load dispatching of traction transformer. The simulation data are in good agreement with the test results, and the average relative error is 3.4%. The results verify the effectiveness of the proposed method.

The oil-immersed transformer is a crucial piece of equipment in the power system. Operating at the specified temperature is necessary to ensure the normal operation of the transformer. The insulation paper on the winding surface has a significant impact on the actual temperature of the transformers, which is often overlooked by researchers. The one-dimensional steady-state heat conduction model of the transformer is established by analyzing the heat diffusion process of winding to transformer oil. Atomic force microscope was used to observe the microsurface structure of insulation paper and copper. According to the experiment, the heat transfer resistance in the series process of heat transfer at 7 0 ∘ C is 0.0138 m2 K/W. Space thermal circuit model of transformer is established by thermoelectricity analogy method, and the simulation circuit is optimized according to the boundary conditions set up in the actual environment. The results show that the error of the hot spot temperature is closer to the measured temperature and decreases by 2.5% when considering the thermal resistance of insulation paper. [ABSTRACT FROM AUTHOR]

This article presents a methodology to simultaneously estimate the heat flux and the hot spot temperature in real time by solving an Inverse Heat Conduction Problem (IHCP). Thus, this study is useful to support the development of practical tool wear monitoring systems and to improve the comprehension of temperature distribution on the tool in machining process. In addition, the use of an IR camera avoids the need to attach thermocouples on the sample. In order to achieve this, a filter coefficient technique is used. Temperatures measured in accessible position on the face of the ceramic tool were used as input data for the problem using an IR camera with a measurement rate of 30 Hz. A monitoring software (Real Time Heat Flux Monitor) which was used in a real case scenario was developed. This software allows the user to monitor heat flux, hot spot temperature and the temperature field in real time without prior knowledge of IHCPs. The results revealed an estimated heat flux in the order of 1.41 × 107 W/m2 and the hot spot temperature reached approximately 700 °C. These results were compared with the Function Specification offline technique, which is well known in literature.

This paper presents the examination of the magnetic core of a large synchronous generator, by the method of indirect heating through an improvised winding. The test results, the criteria for assessing the operating condition of the generator magnet circuit, as well as the analytical calculations for the improvised winding, which is connected through a special connection to the auxiliary transformers, are shown. Electromagnetic simulations were also performed to check the required value of the magnetic flux density in the generator core. [ABSTRACT FROM AUTHOR]

This paper presents a study on the influence of the environmental factors (respectively, ambient temperature and solar radiation) on hot spot temperatures and the consumed and remaining lifetimes of power transformers. In this regard, 15 identical 105 MVA distribution transformers are considered, loaded with the same load, and operating in 15 areas of Romania (with different climatic characteristics). Using the equations recommended by IEC 60076-7 (modified in the case of the presence of solar radiation) the values of oil temperature, hot spot temperatures and consumed and remaining lifetimes in two days from July 2020 are calculated, both in the presence and in the absence of solar radiation. It is shown that the values of the hot spot temperature and of the consumed lifetimes differ from one locality to another and that they increase with the increase of the ambient temperature and the intensities of the solar radiation. Finally, it is shown that the results obtained can be used to develop more efficient maintenance programs for distribution power transformers. [ABSTRACT FROM AUTHOR]

Since dry type transformers (DTT) has many advantages over the oily ones, this study focuses on the realibity, feasibility and cost of DTT to be used at outdoor applications. On this respect the core and winding temperatures of the 1500 VA DTT transformer model is measured by thermal camera The operational highest temperature of the transformer is obtained by this way. The DTT is simulated by ANSYS with the design parameters based On the physical model, and the simulation values and the real ones are compared to satisfy the procedure. Then in the light of simulation results, an outer cover is designed for outdoor applications which is the goal of the paper. The real hot spot temperature of the 1500 VA DTT is 129 ° C remains the same with the new cover simulation designed DTT that naturally cooled. Furthermore, the temperature of the new design DTT is reduced by about 4.6% to 123 ° C by forced cooling. So the new cover design not only provide to be used at outdoors applications, it also increases the lifetime of the device, and reduces the operation costs.

The transformer bushing hot spot temperature (HST) seriously affects its performance and design. In this paper, a novel method for calculating the hot spot temperature of bushing is proposed, in which the principle of constant joule heat is adopted to transform the fluctuating current into the steady-state current. Firstly, the fluctuating current based on time is segmented. Then, the fluctuating current in each period of time is transformed into steady-state current which is used as heat source. Next, the Finite Element Method (FEM) is used to determine a typical bushing's temperature distribution and specify its hot spot. According to the calculation results of hot spot temperature rise, the time interval is adjusted. Finally, the optimal time interval and the steady-state equivalent current are obtained by solving the hot spot temperature of the transformer bushing iteratively. In addition, the method is used to calculate the hot spot temperature of a 220kV Oil Impregnated Paper (OIP) bushing. Compared with the results of traditional transient calculation method, the validity of the proposed method is verified, and the computing time is greatly reduced.

This paper proposed a prediction method to predict a 10-kV oil-immersed transformer hot spot temperature (HST). A set of feature temperature points on the transformer iron shell is proposed based on fluid-thermal field calculation. These feature points, as well as transformer load rate, are taken as the input parameters of a machine learning model established by support vector regression (SVR), thus to describe their relationships with the HST. This model is trained by nine samples selected by L9(34) orthogonal array and applied to predict the HST of 20 test samples. The training samples are all obtained by simulation, and the test samples have consisted of simulation and transformer temperature rise test results. With effective parameter optimization of the SVR model, the predicted results agree well with the experimental and simulation data, the mean absolute percentage error (MAPE) is 1.55%, and the maximum temperature difference is less than 3 °C. The results validated the validity and the generalization performance of the prediction model.

The insulation paper loss of life (LOL) of a distribution transformer (DT) is largely determined by its winding hot-spot temperature. It is mainly estimated via the transformer load, ambient temperature, and related physical parameters. Fortunately, advanced metering infrastructure (AMI) can provide load profiles of DTs, allowing a cost-effective LOL estimation solution. However, the AMI dataset contains measurement errors that significantly reduce LOL estimation accuracy. A forecasting method is needed to recover the erroneous AMI data. This is a challenging problem, as the load profiles of DTs are nonstationary and volatile. We propose an ensemble of stacked long short-term memory (ES-LSTM) networks to simultaneously capture load consumption patterns of DTs and their correlations. The ES-LSTM consists of two independent LSTM networks and a feed-forward neural network (FFNN) stacked on top of them. A two-stage training procedure is applied. In the first stage, two LSTM networks are trained to capture the daily or weekly load patterns. In the second stage, the FFNN is trained to optimally combine the last hidden outputs of the two LSTM networks. Field verification is conducted using real AMI data obtained from an urban distribution utility in China. The test results confirmed the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Transformer performance and efficiency can be enhanced by effectively address the properties of its insulation system. The power transformer insulation system weakens as a result of operational thermal stresses brought on by dynamic loading and shifting environmental patterns. Winding hot spot temperature is a crucial metric that must be maintained below the prescribed limit while power transformers are operating so as to maintained power system reliability. This is due to the fact that, among other variables, the time-dependent aging effect of insulation depends on transitions in hot spot temperatures. Due to the non-linear nature of the conventional mathematical models used to determine these temperatures, and complexity of thermal phenomena, investigations still need to be exercised to fully understand the variables that associate with hot spot temperature computation with minimum error. This paper explores the possibilities of enhancing top oil and hot spot temperature estimation accuracy through the use of an adaptive neuro-fuzzy inference (ANFIS) technique. The paper presents an adaptive neuro fuzzy model to approximate the hot spot temperature of a mineral oil-filled power transformer based on loading, and established top oil temperature. Initially, a sub-ANFIS top oil temperature estimation model based on loading and ambient temperature as inputs is established. Using a hybrid optimization technique, the ANFIS membership functions were fine-tuned throughout the training process to reduce the difference between the actual and anticipated outcomes. The correctness and reliability of the created adaptive neural fuzzy model have been verified using real-world field data from a 60/90MVA, 132 kV power transformers under dynamic operating regimes. The ANFIS model results were validated against field measured values and literature-based electrical-thermal analogous models, establishing a precise input-output correlation. The developed ANFIS model achieves the highest coefficient of determination for both TOT and HST (0.98 and 0.96) and the lowest mean square error (7.8 and 10.3) among the compared thermal models. Correct determination of HST can help asset managers in thermal analysis trending of the in-service transformers, helping them to make proper loading recommendations for safeguarding the asset., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

This article presents an innovative methodological development for the hot spot temperature estimation in mineral oil immersed power transformers by using the support vector regression (SVR). The SVR algorithm is based on the statistical learning theory and is part of the machine learning tools. It was used through a six stage implementation where an SVR model capable of estimating the variable under study is obtained. The method was applied to a real 30 MVA transformer with ONAN/ONAF cooling at 70/100% of load using a database for a 10 year period. The developed SVR model was validated by comparison to the results obtained with the Dejan Susa model using statistical performance metrics. In conclusion, the results obtained indicate that the implemented SVR model allows estimating the hot spot temperature with high accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of E-Gnosis is the property of Universidad de Guadalajara, Coordinacion General Academica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to avoid the uncontrolled removal of the power transformers, a special importance is the accurate knowledge of the estimated, consumed and remaining service life of the insulation systems of these equipment taking into account the real loads during their operation. In this paper a method of calculating the lifetimes based on the recommendations of IEEE and IEC loading guides using the values of the hot spot temperature is presented. These are calculated based on the daily load curves of the transformers, as well as the variable temperatures of the environment and the solar radiation. To highlight the effect of ambient temperature and solar radiation, a case study of three transformers operating in different geographical areas, respectively in Romania (Craiova, Suceava, Constanta) and Mauritania (Noukchatt) is presented. It is found that the values of the hot spot temperature calculated in the presence of solar radiation are approx. 3 °C higher than those calculated in its absence and, for the same daily load regime, the lifetime consumed in one year has higher values for the transformer in Nouakchott, than for those in Craiova (with 231 days) and Suceava (with 256 days). [ABSTRACT FROM AUTHOR]

The increasing penetration of electric vehicles and distributed generation into distribution networks are giving rise to higher, more volatile, and bi-directional energy flows through distribution transformers (DTs). To minimize future capital expenditure, improved DT design approaches are required. Therefore, a novel DT design approach based on a new paradigm of “designing for maximum utilization” is proposed. It incorporates manufacturer and customer-sourced empirical data to achieve a desired DT retirement age and utilization rate, and allows for transient operation beyond DT nameplate rating through accurately accounting for thermal inertia. The novelty of the proposed approach derives from not only a new notion of designing for maximum utilization, but also allowing for the fact that winding insulation may not be the most critical factor affecting a DT's lifetime. Using the proposed approach, DT capital expenditure and utilization constraints can be optimized at a planning stage. The algorithm is applied and validated. [ABSTRACT FROM AUTHOR]

High current conductors of transformers cause to produce losses and thermal problems in their tank cover. Finite Difference (FD) Method (FDM) magnetic analysis is used to find out an exact estimation of the magnetic field and the losses near the bushings in the transient solution, considering the non-linear magnetic permeability of the cover plate, because FDM is more flexible to deal with the nonlinear constitutive law and easy-to-be implemented especially in the case of simple geometry. Finite Element Method (FEM) thermal analysis is used to determine the plate temperature based on magnetic FD analysis, taking account non-linear heat flux boundary condition. A calibration procedure is used between the analyses to ensure the precision of assumptions. The reliability of the technique, confirmed by experimental and FEM results. [ABSTRACT FROM AUTHOR]

Effects of a reduced torque on heating and the electrical resistance of wire-screw terminal connections in an old (used) receptacle and two new receptacles with intentionally corroded connections were experimentally investigated in the laboratory. In one of the new receptacles, the corrosion process was accelerated by treating the line connection with a mixture of nitric acid and hydrochloric acid, and in the other by treating the neutral connection with sulfuric acid. It was shown that by using these acids, both the temperature rise and electrical behavior of long-serving receptacles can be simulated. The possibility to detect a poor contact in an electrical circuit by measuring both the line to earth (L-PE) resistance and the line to neutral (L-N) short circuit loop resistance during a periodic verification of low-voltage electrical installations was also analyzed. In the laboratory conditions, a test electrical circuit with a poor contact in each of the tested receptacles was formed and the influence of that contact on both of the mentioned resistances was observed during long-lasting heating processes. Based on the results of both the laboratory experiments and periodic verifications of low-voltage electrical installations in public and commercial buildings with the total of 11 243 receptacles, a new procedure for detecting poor contacts in low-voltage electrical installations, valid for the terra neutral protection system, is recommended. The procedure, intended for periodic verification, provides information about poor contacts and their location in the tested receptacle (on the phase, neutral, and/or equipment grounding conductor) by comparing both the L-PE resistance and the L-N short circuit loop resistance to the limit values obtained during the verification. [ABSTRACT FROM AUTHOR]

• The feasibility of CICC cable based on Bi-2223 tape has been studied. The performances of cables with 3-, 4-, 5- and 6-slot are analyzed to investigate the relation between the quantity of grooves and tapes on the critical current. The comparison between the copper and aluminum frame on the quench behavior of cable is also discussed. • The critical current properties of the stacked-tape cable are studied by the self-consistent model and H-formula model. The hot-spot temperature during an emergency discharge is also estimated based on one-dimensional analyses. • The critical current of cable is mainly determined by the quantity of tape in cable where the self-field effect has little impact on the critical current in 4.2 K and 15 T. • The minimum quench energy (MQE) is proportional to the tape numbers where the MQE with copper frame is higher than that with aluminum frame. The hot spot temperature is decreased with tape numbers for cable with aluminum frame, however, the effect of tape numbers on the hot spot temperature of cable with copper frame is not obvious where the quench is triggered by MQE. The cable with lower quantity of grooves shows higher stability compared with other variants containing the same number of tapes. The cable-in-conduit-conductor (CICC) based on Bi 2 Sr 2 Ca 2 Cu 3 O x (Bi-2223) tape has potential to be used in fusion magnets duo to its high current-carrying capacity under high field and low temperature. In this study, the optimized study on the stacked tape cable based on Bi-2223 tape was performed. The effect of the quantity of grooves and tapes on the critical current is studied by the finite element method, respectively. The comparison between the copper and aluminum frame on the quench behavior of cable is also discussed. The results shows that the critical current of cable is mainly determined by the quantity of tape in cable where the self-field effect has little impact on the critical current in 4.2 K and 15 T. The minimum quench energy (MQE) is proportional to the tape numbers where the MQE with copper frame is higher than that with aluminum frame. The hot spot temperature is decreased with tape numbers for cable with aluminum frame, however, the effect of tape numbers on the hot spot temperature of cable with copper frame is not obvious where the quench is triggered by MQE. Moreover, the cable with lower quantity of grooves shows higher stability compared with other variants containing the same number of tapes. [ABSTRACT FROM AUTHOR]

Temperature is a key factor for failure analysis of power transformers. Conventionally, transformer failure rate is calculated with hot spot temperature induced from IEEE empirical equations. This article firstly introduces a spatial and temporal related failure model based on three‐dimensional thermal simulations of transformer and the related environment. The proposed thermal model is established with computational fluid dynamics for ventilation calculation and heat generation equations for power device simulation. Cooling strategies and mutual heating effect of power equipment are considered for an accurate temperature distribution prediction. By incorporating the three‐dimensional thermal model into the service life‐dependent and temperature‐dependent model, the failure rate of each spatial point in power transformer could be calculated according to Arrhenius theory and Weibull distribution. The simulation results show that the proposed model clearly improves the accuracy of failure analysis and can be used for thermal and ventilation design of transformer room. [ABSTRACT FROM AUTHOR]

Since 2010 to present, several subsize magnet assemblies, designed as test beds for the validation of impregnated Nb3 Sn-based coil technology, have been tested at the Superconducting Magnet Test Facility (SM18) at CERN. These short model coils and racetrack model coils have been used to study two types of Rutherford cables foreseen for the coils of the Nb3Sn magnets in the framework of the HL-LHC upgrade and High Field Magnet program of CERN. During several test campaigns, the Rod Restack Process and the Powder-In-Tube conductors have been characterized in terms of performance and quench propagation velocity (QPV). Moreover, hot spot temperature (HST) increase during quenches has been estimated from the analysis of the registered voltage and current signals. In this paper, the multiphysics problem of quench propagation in Nb3Sn cables is addressed under adiabatic conditions by means of a set of analytical formulae and several finite element models with different level of complexity in ANSYS APDL, COMSOL Multiphysics, and MATLAB. These models are aimed at describing the conductor behavior in terms of HST and QPV observed during the training of racetrack coils at SM18. [ABSTRACT FROM AUTHOR]

In this work, 3D particle-resolved CFD simulations have been performed to investigate the thermal effects of natural gas production from coke oven gas. The catalyst packing structures with uniform, gradient rise and gradient descent distribution and the operating conditions of pressure, wall temperature, inlet temperature and feed velocity are optimized for reduced hot spot temperature. The simulation results show that compared with packing structures with uniform distribution and gradient descent distribution, the gradient rise distribution could effectively reduce the hot spot temperature without affecting the reactor performance in the reactor with upflow reactants feeding, of which the reactor bed temperature rise is 37 K. Under the conditions with the pressure of 20 bar, wall temperature of 500 K, inlet temperature of 593 K, inlet flow rate of 0.04 m/s, the packing structure with gradient rise distribution exhibits the minimum reactor bed temperature rise of 19 K. By optimizing the catalyst distribution and operation conditions, the hot spot temperature of CO methanation process could be dramatically reduced by 49 K at the sacrifice of slightly reduced CO conversion. [Display omitted] • The particle-resolved reactor model on COG methanation is successfully established. • Gradient rise distribution could reduce the hot spot temperature by 31K • Optimizing operation conditions would further lower hot spot temperature. [ABSTRACT FROM AUTHOR]

This paper develops a novel dynamic correction method for the reliability assessment of large oil-immersed power transformers. First, with the transformer oil-paper insulation system (TOPIS) as the target of evaluation and the winding hot spot temperature (HST) as the core point, an HST-based static ageing failure model is built according to the Weibull distribution and Arrhenius reaction law, in order to describe the transformer ageing process and calculate the winding HST for obtaining the failure rate and life expectancy of TOPIS. A grey target theory based dynamic correction model is then developed, combined with the data of Dissolved Gas Analysis (DGA) in power transformer oil, in order to dynamically modify the life expectancy calculated by the built static model, such that the corresponding relationship between the state grade and life expectancy correction coefficient of TOPIS can be built. Furthermore, the life expectancy loss recovery factor is introduced to correct the life expectancy of TOPIS again. Lastly, a practical case study of an operating transformer has been undertaken, in which the failure rate curve after introducing dynamic corrections can be obtained for the reliability assessment of this transformer. The curve shows a better ability of tracking the actual reliability level of transformer, thus verifying the validity of the proposed method and providing a new way for transformer reliability assessment. This contribution presents a novel model for the reliability assessment of TOPIS, in which the DGA data, as a source of information for the dynamic correction, is processed based on the grey target theory, thus the internal faults of power transformer can be diagnosed accurately as well as its life expectancy updated in time, ensuring that the dynamic assessment values can commendably track and reflect the actual operation state of the power transformers.