Effects of multiple shapes for steady flow with transformer oil+Fe_(3)O_(4)+TiO_(2) between two stretchable rotating disks

In this study,we examine the effects of various shapes of nanoparticles in a steady flow of hybrid nanofluids between two stretchable rotating disks.The steady flow of hybrid nanofluids with transformer oil as the base fluid and Fe_(3)O_(4)+TiO_(2)as the hybrid nanofluid is considered.Several shapes of Fe_(3)O_(4)+TiO_(2)hybrid nanofluids,including sphere,brick,blade,cylinder,and platelet,are studied.Every shape exists in the same volume of a nanoparticle.The leading equations(partial differential equations(PDEs))are transformed to the nonlinear ordinary differential equations(ODEs)with the help of similarity transformations.The system of equations takes the form of ODEs depending on the boundary conditions,whose solutions are computed numerically by the bvp4c MATLAB solver.The outputs are compared with the previous findings,and an intriguing pattern is discovered,such that the tangential velocity is increased for the rotation parameter,while it is decreased by the stretching values because of the lower disk.For the reaction rate parameter,the concentration boundary layer becomes shorter,and the activation energy component increases the rate at which mass transfers come to the higher disk but have the opposite effect on the bottom disk.The ranges of various parameters taken into account are Pr=6.2,Re=2,M=1.0,φ_(1)=φ_(2)=0.03,K=0.5,S=-0.1,Br=0.3,Sc=2.0,α_(1)=0.2,γ=0.1,E_(n)=2.0,and q=1.0,and the rotation factor K is within the range of 0 to 1.

A Deep Learning Ensemble Method for Forecasting Daily Crude Oil Price Based on Snapshot Ensemble of Transformer Model

The oil industries are an important part of a country’s economy.The crude oil’s price is influenced by a wide range of variables.Therefore,how accurately can countries predict its behavior and what predictors to employ are two main questions.In this view,we propose utilizing deep learning and ensemble learning techniques to boost crude oil’s price forecasting performance.The suggested method is based on a deep learning snapshot ensemble method of the Transformer model.To examine the superiority of the proposed model,this paper compares the proposed deep learning ensemble model against different machine learning and statistical models for daily Organization of the Petroleum Exporting Countries(OPEC)oil price forecasting.Experimental results demonstrated the outperformance of the proposed method over statistical and machine learning methods.More precisely,the proposed snapshot ensemble of Transformer method achieved relative improvement in the forecasting performance compared to autoregressive integrated moving average ARIMA(1,1,1),ARIMA(0,1,1),autoregressive moving average(ARMA)(0,1),vector autoregression(VAR),random walk(RW),support vector machine(SVM),and random forests(RF)models by 99.94%,99.62%,99.87%,99.65%,7.55%,98.38%,and 99.35%,respectively,according to mean square error metric.

Decomposition of Transformer Oil Under Ultrasonic Irradiation During Degassing Process

In the degassing process of transformer oil with ultrasonic waves, decomposition of the oil was observed. Light hydrocarbons, including methane, ethane, ethylene, acetylene, propane etc, were found to be released continuously from the oil into headspace within a closed vial placed in an ultrasonic field. The gases came from decomposition of hydrocarbon molecules under cavitation effect.

A rapid method for determination of acid value in transformer oil by PPy modified electrode

A polypyrrole-modified glassy carbon electrode （PPy/GC electrode） was prepared and its electrocatalytic behavior towards naphthoquinone in the presence of acid was characterized by linear sweep voltammetry （LSV）. A well-defined new reduction peak appeared at a more positive potential than the original reduction peak. The new reduction peak current was linearly related to the acid value （AV） of oil. Based on it, a rapid electrochemical method for determining AV of transformer oil was developed using PPy/GC electrode. A working curve was obtained in the AV range of 0.01 to 0.40 mg（KOH）.g^-1, with a sensitivity of 39.42 μA0.5/（mg（KOH）.g-l） and the detection limit of 0.0014 mg（KOH）.g^-1 （signal-to-noise ratio is 3, standard deviation is 2.247%）. Moreover, the proposed method has been successfully applied to AV determination of several transformer oil samples with advantages of rapidness, high sensitivity and accuracy compared to the conventional method.

Copper Release Kinetics and Ageing of Insulation Paper in Oil-Immersed Transformers

The paper provides a general overview of chemical processes leading to the degradation of oil-paper insulation in oil-immersed electrical current transformers. Previous knowledge available in literature is complemented by new results placing a specific emphasis on the physicochemical factors which affect the copper release in the insulation oil and the oil oxidation kinetics. It is demonstrated that various ageing processes interact with each other, with one or another process dominating under specific conditions. Comprehensive but disjoint studies focusing on separate sub-processes may produce rather misleading results, and occasionally, lie behind rather irrelevant quality demands imposed on the insulating liquids.

Organic matter transformation ratio, hydrocarbon expulsion efficiency and shale oil enrichment type in Chang 7_(3) shale of Upper Triassic Yanchang Formation in Ordos Basin, NW China

The major enrichment type of shale oil in the Chang 7_(3) shale of Upper Triassic Yanchang Formation in the Ordos Basin is unknown.This paper analyzes the organic matter transformation ratio,hydrocarbon expulsion efficiency and roof/floor sealing conditions of the Chang 7_(3) shale,and evaluates the major enrichment type of shale oil in this interval.The average organic matter transformation ratio of the Chang 7_(3) shale is about 45%;in other words,more than 50%of the organic matters have not transformed to hydrocarbons,and the lower the maturity,the greater the proportion of untransformed organic matters.The cumulative hydrocarbon expulsion efficiency of the transformed hydrocarbon is 27.5% on average,and the total proportion of untransformed organic matters plus retained hydrocarbons is greater than 70%.The relative hydrocarbon expulsion efficiency of the Chang 7_(3) shale is 60%on average,that is,about 40% of hydrocarbons retain in the shale.The Chang 7_(3) shale corresponds to Chang 7_(1+2) and Chang 8 sandstones as the roof and floor,respectively,and is further overlaid by Chang 6 shale,where extensive low porosity and low permeability–tight oil reservoirs have formed in the parts with relatively good porosity and permeability.Moreover,the Chang 7_(3) shale is tested to be in a negative pressure system(the pressure coefficient of 0.80–0.85).Therefore,the roof/floor sealing conditions of the Chang 7_(3) shale are poor.The retained hydrocarbons appear mostly in absorbed status,with low mobility.It is concluded that the medium–high mature shale oil is not the major enrichment type of shale oil in the Chang 7_(3) shale,but there may be enrichment opportunity for shale oil with good mobility in the areas where the sealing conditions are good without faults and fractures and oil reservoirs are formed off Chang 7_(1+2),Chang 6 and Chang 8.Furthermore,low–medium mature shale oil is believed to have great potential and is the major enrichment type of shale oil in the Chang 7_(3) shale.It is recommended to prepare relevant in-situ conversion technologies by pilot test and figure out the resource availability and distribution.

Development of a New Bio-Based Insulating Fluid from <i>Jatropha curcas</i>Oil for Power Transformers

The present work aims to develop a new vegetable insulating fluid for power transformers based on Jatropha curcas oil. Besides its technical benefits, Jatropha curcas oil has a socio-economic role by promoting income to rural families, contributing to the countryside development and avoiding rural exodus. Thus, the entire transformer oil production (extraction, processing, characterization and accelerated aging) was covered and a new process was developed. For oil extraction, the most suitable process was the solvent extraction (5 mL of hexane per gram of crushed non-peeled seeds during 30 minutes) with an oil yield of 32%. In raw oil processing stage, the degumming, with 0.4 g of phosphoric acid per 100 g of oil, at 70°C, was used to remove phosphatides. Then, free fatty acids were 96% neutralized with a sodium hydroxide solution (0.5% w/w) at room temperature. For the oil clarification, the combination of 5% w/woil of activated carbon and 1% w/woil of MgO resulted in a bright, odorless and clear oil with an acid number of 0.04 mgKOH·g﹣1. The oil drying in a vacuum rotary evaporator, at 70°C, for 2 hours reduced the water content to 177 ppm. The processed oil was characterized following ASTM D6871 methods. This oil presented higher dielectric breakdown voltage (55 kV) than commercial transformer fluids (BIOTEMP?, EnvirotempFR3?, and Bivolt?), which increases transformer safety, capacity and lifetime. In addition, the processed oil has a lower viscosity than BIOTEMP? fluid, which can enhance the heat dissipation efficiency in the transformer. Moreover, the processed oil flash and fire points of 310°C and >340°C, respectively, confirm the great security of vegetable insulating fluids. The analyzed properties of the processed oil fulfill all the ASTM D6871, ABNT NBR 15422 and IEC 62770 specifications. Therefore, Jatropha curcas oil is a potential substitute formineral insulating fluids.

Improvement of Used Transformer Oils with Activated Bentonite

This research presents the evaluation of activated Bentonite material for treatment of used transformer oil. Different properties such as;electrical, physical, chemical and thermal of used transformer oil were meas-ured before and after purification and treatment. Two power transformers were used in this research (6.4: 4.6 MVA, 3 phases, 50 Hz). One of them was filled with purified oil and the other was filled with activated Bentonite treated oil after purification, and then the two power transformers were tested for one year under practical conditions of the operating field. Initial tests have indicated that the use of Activated BENTONITE in the treatment process for the aged transformer oil improved breakdown voltage, water content, total acidi-ty and flash point. Thus activated Bentonite gives an ideal treatment of aged transformer oil with its environmental and economic advantages. Moreover, activated Bentonite is available at many places in Egypt with low costs.

Insulation System of Power Transformers Behavior Comparison of Mineral Oils and Natural Ester Dielectric Fluids

Paper deals with a comparison of selected properties of several vegetable oil representatives along their accelerated thermal ageing at the temperature of 90 ℃. These properties are compared to two widely used and commercially available mineral transformer oils. A combined insulating system （an oil-paper system） was created with the usage of mentioned oils for measurement purposes. Dissipation factor, capacity and volume resistance are characteristics measured along a thermal ageing of the oil-paper systems. Infrared spectroscopy was used as an additional method. After 1,000 hours of ageing, the dissipation factor of all systems based on vegetable oils did not exceed the value of 0.015. The volume resistance of systems containing mineral oils was approx, twice as high as the volume resistance of those with vegetable oils. The capacity on the other hand was slightly lower in the case of mineral oils application. An experiment also showed that the paper combined with the vegetable oil dries more quickly than in combination with the mineral oil. Infrared spectroscopy has not shown any expressive changes in the chemical structure of aU tested oils yet （up to 1,000 hours of ageing）.

Reviews on Transformer Oil-based Nanofluids

目前纳米改性变压器油由于其高散热性和独特的电气性能,正受到越来越广泛的关注。以近年来纳米改性变压器油的相关研究成果为基础,分析了纳米改性变压器油在导热、击穿、老化、抗水分影响以及改性油-纸相互作用等方面的特点,并介绍了目前常用的3种用于解释绝缘油介质中纳米颗粒改性机理的理论模型,最后提出了纳米改性变压器油领域后续研究需要关注的问题,即纳米颗粒材料体系的选择、高稳定性改性变压器油的制备工艺以及纳米颗粒对变压器油的改性机理。

Identification of Lubricating Oil Additives Using XGBoost and Ant Colony Optimization Algorithms

To address the problem of identifying multiple types of additives in lubricating oil,a method based on midinfrared spectral band selection using the eXtreme Gradient Boosting(XGBoost)algorithm combined with the ant colony optimization(ACO)algorithm is proposed.The XGBoost algorithm was used to train and test three additives,T534(alkyl diphenylamine),T308(isooctyl acid thiophospholipid octadecylamine),and T306(trimethylphenol phosphate),separately,in order to screen for the optimal combination of spectral bands for each additive.The ACO algorithm was used to optimize the parameters of the XGBoost algorithm to improve the identification accuracy.During this process,the support vector machine(SVM)and hybrid bat algorithms(HBA)were included as a comparison,generating four models:ACO-XGBoost,ACO-SVM,HBA-XGboost,and HBA-SVM.The results showed that all four models could identify the three additives efficiently,with the ACO-XGBoost model achieving 100%recognition of all three additives.In addition,the generalizability of the ACO-XGBoost model was further demonstrated by predicting a lubricating oil containing the three additives prepared in our laboratory and a collected sample of commercial oil currently in use。

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.

Extensions to the Finite Element Technique for the Magneto-Thermal Analysis of Aged Oil Cooled-Insulated Power Transformers

It is well known that the hot spot temperature represents the most critical parameter identifying the power rating of a transformer. This paper investigates the effect of the degradation of core magnetic properties on temperature variation of aged oil-cooled transformers. Within this work, 2D accurate assessment of time average flux density distribution in an oil insulated-cooled 25 MVA transformer has been computed using finite-element analysis taking into account ageing and stress-induced non-uniform core permeability values. Knowing the core material specific loss and winding details, local core and winding losses are converted into heat. Based upon the ambient temperature outside the transformer tank and thermal heat transfer related factors, the detailed thermal modeling and analysis have then been carried out to determine temperature distribution everywhere. Analytical details and simulation results demonstrating effects of core magnetic properties degradation on hot spot temperatures of the transformer’s components are given in the paper.

Benefits of Dielectric Oil Regeneration Systems in Power Transmission Networks: A Case Study

The criticality of transformers and reactors in the power transmission network and the paramount importance of ensuring their reliability through maintenance of the insulating oil is known. This paper presents a comprehensive examination of the efficacy and economic viability of a dielectric oil regeneration system, as implemented by the Transmission System Maintenance Department (TSMD) of the Independent Power Transmission Operator (IPTO), Greece’s sole transmission operator. Through a detailed chemical analysis and performance evaluation, we assess the impact of the regeneration system on treated insulating oil quality over multiple cycles. The study reveals that the electrical properties of the insulating oil are fully restored after regeneration, negating the need to fully replace it, while the investment becomes cost-neutral within weeks from the commissioning of the regeneration system. This economic analysis, coupled with the system’s environmental benefits of reducing waste oil generation, positions the dielectric oil regeneration system as a compelling solution for the maintenance of power transmission assets.

Properties of Electrical Discharges Developing in Transformer Oil Under Lightning Impulse in the Setup of Insulated Electrodes

Looking at the problem of electrical discharge development in mineral oil, it is easy to see that most studies in this area focused on the setups of bare high voltage electrodes having a point-plane electrode arrangement. The setups with insulated electrodes are the mar- gin of these studies but it seems to be important to find the dependences between the paper insulation on high voltage electrode and parameters of the discharges initiated in the vicinity of this electrode. Hence, in this paper the results of researches intended to reveal the role of insulation wrapping on a HV electrode in the mechanism of electrical discharges in transformer oil under lightning impulse of both polar- ities are presented. This role is determined by analysis of the parameters characterizing the discharges (onset voltage, propagation velocity, time to initiation, rise-time of light impulses) and also by observation of their spatio-temporal development and oscillograms of the light emitted by their channels. The research was performed for two model electrode configurations: an electrode with paper insulation and a bare electrode which had the same outer dimensions as the insulated one. The most essential conclusion from performed experiment is related to times to initiation. These times, equal in the case of insulated electrodes and model bare electrode, indicate that the source of "weak points" of the paper-oil insulation system is the oil, not the surface of insulation wrapping or the metal.

Coconut Fiber Pyrolysis: Bio-Oil Characterization for Potential Application as an Alternative Energy Source and Production of Bio-Degradable Plastics

The current energy crisis could be alleviated by enhancing energy generation using the abundant biomass waste resources. Agricultural and forest wastes are the leading organic waste streams that can be transformed into useful alternative energy resources. Pyrolysis is one of the technologies for converting biomass into more valuable products, such as bio-oil, bio-char, and syngas. This work investigated the production of bio-oil through batch pyrolysis technology. A fixed bed pyrolyzer was designed and fabricated for bio-oil production. The major components of the system include a fixed bed reactor, a condenser, and a bio-oil collector. The reactor was heated using a cylindrical biomass external heater. The pyrolysis process was carried out in a reactor at a pressure of 1atm and a varying operating temperature of 150˚C, 250˚C, 350˚C to 450˚C for 120 minutes. The mass of 1kg of coconut fiber was used with particle sizes between 2.36 mm - 4.75 mm. The results show that the higher the temperature, the more volume of bio-oil produced, with the highest yield being 39.2%, at 450˚C with a heating rate of 10˚C/min. The Fourier transformation Infrared (FTIR) Spectroscopy analysis was used to analyze the bio-oil components. The obtained bio-oil has a pH of 2.4, a density of 1019.385 kg/m3, and a calorific value of 17.5 MJ/kg. The analysis also showed the presence of high-oxygenated compounds;carboxylic acids, phenols, alcohols, and branched oxygenated hydrocarbons as the main compounds present in the bio-oil. The results inferred that the liquid product could be bestowed as an alternative resource for polycarbonate material production.

WAVELET TRANSFORM THRESHOLD NOISE REDUCTION METHODS IN THE OIL PIPELINE LEAKAGE MONITORING AND POSITIONING SYSTEM

This letter investigates the wavelet transform, as well as the principle and the method of the noise reduction based on wavelet transform, it chooses the threshold noise reduction, and discusses in detail the principles, features and design steps of the threshold method. Rigrsure, heursure, sqtwolog and minimization four kinds of threshold selection method are compared qualitatively, and quantitatively. The wavelet analysis toolbox of MATLAB helps to realize the computer simulation of the signal noise reduction. The graphics and calculated standard deviation of the various threshold noise reductions show that, when dealing with the actual pressure signal of the oil pipeline leakage, sqtwolog threshold selection method can effectively remove the noise. Aiming to the pressure signal of the oil pipeline leakage, the best choice is the wavelet threshold noise reduction with sqtwolog threshold. The leakage point is close to the actual position, with the relative error of less than 1%.

Intelligent Transformation and Upgrading of Oil Refining & Petrochemical Industries in China:Investigation & Application

The oil refining and petrochemical industry in China has made great achievements after decades of development, and its capacity has already ranked second in the world. However, the refining industry is suffering some challenges, such as severe overcapacity at present, and has entered a new economic normal, in which the technological progress develops rapidly, the demand for green and low-carbon development is stricter, the market competition is increasingly fiercer and the profit margins are gradually narrowing. In such a situation, informatization and its new technologies are driving the significant reforming of manufacturing patterns, marketing patterns, management and decision-making patterns. Intelligent development is the inevitable choice for the transformation and upgrading of oil refining and petrochemical industry. It is suggested that the intelligent evaluating model and method should be adopted to enterprise’s intelligentializing transformation and upgrading by laying a solid foundation of digital refinery and implemenation of digital upgrading.

Influence analysis of local heat source on internal temperature distribution of power transformer

Oil immersed power transformer is the main electrical equipment in power system.Its operation reliability has an important impact on the safe operation of power system.In the process of production,installation and operation,its insulation structure may be damaged,resulting in partial discharge and even breakdown inside the transformer.In this paper,S9-M-100/10 oil immersed distribution transformer is taken as the research object,and the distribution laws of electromagnetic field and temperature field in transformer under normal operation,inter turn short circuit and inter layer short circuit are simulated and analyzed.The simulation results show that under normal conditions,the temperatures at the oil gap between the transformer core and the high and low voltage windings and the middle position of the high-voltage winding are high.When there are inter turn and inter layer short circuit faults,the electromagnetic loss of the fault part of the transformer increases,and the temperature rises suddenly.The influence of the two faults on the internal temperature field of the transformer is different,and the influence of the inter turn short circuit fault on the temperature nearby is obvious.The analysis results can provide reference for the thermal fault interpretation and fault classification of transformer.

Intelligent Diagnostic Method for Ageing Analysis of Transformer

The fuzzy method is proposed for ageing analysis of transformer. The fuzzy controller is used for various input and one output, strictly depends on the number of membership function and there rule base and the type of the defuzzification method. The ageing of transformers is influenced by short term and long term over loads, number and intensity of short circuits, incidence of lightning, and internal faults. The recent development of various techniques for detecting the incipient fault conditions have been improved to some extent;the life expectancy of transformers by resorting to corrective actions in time. The ageing behavior is likely to be different for different types of transformers. The life span of the transformer, thus depends initially on the design and quality of manufacture and later on service conditions and maintenance standard, these factors vary considerably and affect the useful span of service life which therefore needs to be taken into account for residual life assessment. During the natural ageing of transformers, the insulation of winding deteriorates. Cellulose insulation degrades due to heating or electrical breakdown which is dissolved in oil. Hence, the chemical analysis of the Transformer oil gives evidence of changes that are taking place in the winding insulation during operation. Deterioration in transformer cellulose decreases both its electrical and mechanical strength. In this paper a novel fuzzy based algorithm has been implemented on three samples of power transformer oil.