A Study on the Motion Behavior of Metallic Contaminant Particles in Transformer Insulation Oil under Multiphysical Fields.

When using transformer insulation oil as a liquid dielectric, the oil is easily polluted by the solid particles generated in the operation of the transformer, and these metallic impurity particles have a significant impact on the insulation performance inside the power transformer. The force of the metal particles suspended in the flow insulation oil is multidimensional, which will lead to a change in the movement characteristics of the metal particles. Based on this, this study explored the motion rules of suspended metallic impurity particles in mobile insulating oil in different electric field environments and the influencing factors. A multiphysical field model of the solid-liquid two-phase flow of single-particle metallic impurity particles in mobile insulating oil was constructed using the dynamic analysis method, and the particles' motion characteristics in the oil in different electric field environments were simulated. The motion characteristics of metallic impurity particles under conditions of different particle sizes, oil flow velocities, and insulation oil qualities and influencing factors were analyzed to provide theoretical support for the detection of impurity particles in transformer insulation oil and enable accurate estimations of the location of equipment faults. Our results show that there are obvious differences in the trajectory of metallic impurity particles under different electric field distributions. The particles will move towards the region of high field intensity under an electric field, and the metallic impurity particles will not collide with the electrode under an AC field. When the electric field intensity and particle size increase, the trajectory of the metallic impurity particles between electrodes becomes denser, and the number of collisions between particles and electrodes and the motion speed both increase. Under the condition of a higher oil flow velocity, the number of collisions between metal particles and electrodes is reduced, which reduces the possibility of particle agglomeration. When the temperature of the insulation oil changes and the quality deteriorates, its dynamic viscosity changes. With a decrease in the dynamic viscosity of the insulation oil, the movement of the metallic impurity particles between the electrodes becomes denser, the collision times between the particles and electrodes increase, and the maximum motion speed of the particles increases.

Structure-Activity Relationship Models to Predict Properties of the Dielectric Fluids for Transformer Insulation System.

Mineral oils and synthetic and natural esters are the predominant insulating liquids in electrical equipment. Structure-activity relationship models to predict the key properties of pure insulating liquids, including pulse breakdown strengths, AC breakdown voltages, dielectric constants, flash points, and kinematic viscosities, have been proposed for the first time. Dependence of the specific properties on the molecular structures has been illustrated quantitatively in terms of surface area, statistical total variance, and average deviation of positive and negative electrostatic potentials, as augmented by molecular weight, volume, and ovality. Moreover, the individual contribution of the functional groups to viscosity has been revealed by an additive approach. The predicted properties are in good agreement with the experimental data. The present theoretical work provides new insights on the development of novel dielectric fluids.

Effective Electrical Properties and Fault Diagnosis of Insulating Oil Using the 2D Cell Method and NSGA-II Genetic Algorithm.

In this paper, an experimental analysis of the quality of electrical insulating oils is performed using a combination of dielectric loss and capacitance measurement tests. The transformer oil corresponds to a fresh oil sample. The paper follows the ASTM D 924-15 standard (standard test method for dissipation factor and relative permittivity of electrical insulating liquids). Effective electrical parameters, including the tan δ of the oil, were obtained in this non-destructive test. Subsequently, a numerical method is proposed to accurately determine the effective electrical resistivity, σ, and effective electrical permittivity, ε, of an insulating mineral oil from the data obtained in the experimental analysis. These two parameters are not obtained in the ASTM standard. We used the cell method and the multi-objective non-dominated sorting in genetic algorithm II (NSGA-II) for this purpose. In this paper, a new numerical tool to accurately obtain the effective electrical parameters of transformer insulating oils is therefore provided for fault detection and diagnosis. The results show improved accuracy compared to the existing analytical equations. In addition, as the experimental data are collected in a high-voltage domain, wireless sensors are used to measure, transmit, and monitor the electrical and thermal quantities.

Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors.

Power transformers are considered important and expensive items in electrical power networks. In this regard, the early discovery of potential faults in transformers considering datasets collected from diverse sensors can guarantee the continuous operation of electrical systems. Indeed, the discontinuity of these transformers is expensive and can lead to excessive economic losses for the power utilities. Dissolved gas analysis (DGA), as well as partial discharge (PD) tests considering different intelligent sensors for the measurement process, are used as diagnostic techniques for detecting the oil insulation level. This paper includes two parts; the first part is about the integration among the diagnosis results of recognized dissolved gas analysis techniques, in this part, the proposed techniques are classified into four techniques. The integration between the different DGA techniques not only improves the oil fault condition monitoring but also overcomes the individual weakness, and this positive feature is proved by using 532 samples from the Egyptian Electricity Transmission Company (EETC). The second part overview the experimental setup for (66/11.86 kV-40 MVA) power transformer which exists in the Egyptian Electricity Transmission Company (EETC), the first section in this part analyzes the dissolved gases concentricity for many samples, and the second section illustrates the measurement of PD particularly in this case study. The results demonstrate that precise interpretation of oil transformers can be provided to system operators, thanks to the combination of the most appropriate techniques.

Color Index of Transformer Oil: A Low-Cost Measurement Approach Using Ultraviolet-Blue Laser.

The color of transformer oil can be one of the first indicators determining the quality of the transformer oil and the condition of the power transformer. The current method of determining the color index (CI) of transformer oil utilizes a color comparator based on the American Society for Testing and Materials (ASTM) D1500 standard, which requires a human observer, leading to human error and a limited number of samples tested per day. This paper reports on the utilization of ultra violet-blue laser at 405- and 450-nm wavelengths to measure the CI of transformer oil. In total, 20 transformer oil samples with CI ranging from 0.5 to 7.5 were measured at optical pathlengths of 10 and 1 mm. A linear regression model was developed to determine the color index of the transformer oil. The equation was validated and verified by measuring the output power of a new batch of transformer oil samples. Data obtained from the measurements were able to quantify the CI accurately with root-mean-square errors (RMSEs) of 0.2229 for 405 nm and 0.4129 for 450 nm. This approach shows the commercialization potential of a low-cost portable device that can be used on-site for the monitoring of power transformers.

Dual LSPR and CT synergy: 3D urchin-like Au@W18O49 enables highly sensitive in-situ SERS detection of dissolved furfural in insulating oils.

Assessing the levels of furfural in insulating oils is a crucial technical method for evaluating the degree of aging and mechanical deterioration of oil-paper insulation. The surface-enhanced Raman spectroscopy (SERS) technique provides an effective method for enhancing the sensitivity of in-situ detection of furfural. In this study, a homogeneous three-dimensional (3D) urchin-like Au@W18O49 heterostructure was synthesized as a SERS substrate using a straightforward hydrothermal method. The origin of the superior Raman enhancement properties of the 3D urchin-like heterostructures formed by the noble metal Au and the plasmonic semiconductor W18O49, which is rich in oxygen vacancies, is analyzed experimentally in conjunction with density-functional theory (DFT) calculations. The Raman enhancement is further amplified by the remarkable dual localized surface plasmon resonance (LSPR) effect, which generates a strong local electric field and creates numerous "hot spots," in addition to the interfacial charge transport (CT). The synergistic effect of these factors results in the 3D urchin-like Au@W18O49 heterostructure exhibiting exceptionally high SERS activity. Testing the rhodamine 6G (R6G) probe resulted in a Raman enhancement factor of 3.41 × 10-8, and the substrate demonstrated excellent homogeneity and stability. Furthermore, the substrate was effectively utilized to achieve highly sensitive in-situ surface-enhanced Raman scattering (SERS) detection of dissolved furfural in complex plant insulating oils. The development of the 3D urchin-like Au@W18O49 heterostructure and the exploration of its enhancement mechanism provide theoretical insights for the advancement of high-performance SERS substrates.

Neural networks and particle swarm for transformer oil diagnosis by dissolved gas analysis.

The lifetime of power transformers is closely related to the insulating oil performance. This latter can degrade according to overheating, electric arcs, low or high energy discharges, etc. Such degradation can lead to transformer failures or breakdowns. Early detection of these problems is one of the most important steps to avoid such failures. More efficient diagnostic systems, such as artificial intelligence techniques, are recommended to overcome the limitations of the classical methods. This work deals with diagnosing the power transformer insulating oil by analysis of dissolved gases using new techniques. For this, we have proposed intelligent techniques based on Multilayer artificial neural networks (ANN). Thus, a multi-layer ANN-based model for fault detection is presented. To improve its classification rate, this one was optimized by a meta-heuristic technique as the particle swarm optimization (PSO) technique. Optimized ANNs have never been used in transformer insulating oil diagnostics so far. The robustness and effectiveness of the proposed model is demonstrated, and high accuracy is obtained.

Influence of Mineral Oil-Based Nanofluids on the Temperature Distribution and Generated Heat Energy Inside Minimum Oil Circuit Breaker in Making Process.

The enhancement of the thermal properties of insulating oils has positively reflected on the performance of the electrical equipment that contains these oils. Nanomaterial science plays an influential role in enhancing the different properties of liquids, especially insulating oils. Although a minimum oil circuit breaker (MOCB) is one of the oldest circuit breakers in the electrical network, improving the insulating oil properties develops its performance to overcome some of its troubles. In this paper, 66 kV MOCB is modeled by COMSOL Multiphysics software. The internal temperature and the internally generated heat energy inside the MOCB during the making process of its contacts are simulated at different positions of the movable contact. This simulation is introduced for different modified insulating oils (mineral oil and synthetic ester oil) with different types of nanoparticles at different concentrations (0.0, 0.0025, 0.005, and 0.01 wt%). From the obtained results, it is noticed that the thermal stress on the MOCB can be reduced by the use of high thermal conductivity insulating oils. Nano/insulating oils decrease internal temperature and generate heat energy inside the MOCB by about 17.5%. The corresponding physical mechanisms are clarified considering the thermophoresis effect.

Investigation on Adsorption of Polar Molecules in Vegetable Insulating Oil by Functional Fossil Graphene.

As a new engineering dielectric, vegetable insulating oil is widely used in electrical equipment. Small polar molecules such as alcohol and acid will be produced during the oil-immersed electrical equipment operation, which seriously affects the safety of equipment. The polar molecule can be removed by using functional fossil graphene materials. However, the structural design and group modification of graphene materials lack a theoretical basis. Therefore, in this paper, molecular dynamics (MD) and quantum mechanics theory (Dmol3) were utilized to study the adsorption kinetics and mechanism of graphene (GE), porous graphene (PGE), porous hydroxy graphene (HPGE), and porous graphene modified by hydroxyl and carboxyl groups (COOH-HPGE) on polar small molecules in vegetable oil. The results show that graphene-based materials can effectively adsorb polar small molecules in vegetable oil, and that the modification of graphene materials with carboxyl and hydroxyl groups improves their adsorption ability for polar small molecules, which is attributed to the conversion of physical adsorption to chemical adsorption by the modification of oxygen-containing groups. This study provides a theoretical basis for the design and preparation of graphene materials with high adsorption properties.

Investigation of CeO2 nanoparticles on the performance enhancement of InsulatingOils.

Integrating nanotechnology in dielectric fluid significantly inhibits losses and boosts overall dielectric fluid performance. There has been research done on the effects of introducing various nanoparticles, such as titania, alumina, silica nanodiamonds, etc. In this paper, a novel nanoparticle, Ceria (CeO2), has been used, and its properties were examined using the FTIR (Fourier Transform Infrared) spectrum, the XRD (X-ray Diffraction) spectrum, the SEM (Scanning Electron Microscopy), and the TEM (Transmission Electron Microscopy). This paper illustrates an efficient dielectric fluid prepared by the successful dispersion of Cerium Oxide (CeO2) nanoparticles in various concentrations into four commercial oils, namely mineral oil, rapeseed oil, synthetic ester oil, and soybean oil, to enhance and improve their dielectric characteristics. The performance investigation emphasises breakdown strength enhancement and other dielectric properties of the colloidal solution comprising different nanoparticle (NP) concentrations. Various commercial oils are used as a base in nano-oil to diversify their applicability as dielectric fluids by measuring the correlation in dielectric parameters and statistically assessing their applicability with normal and Weibull distributions. The obtained experimental data sets were analyzed using the Statistics and Machine Learning Toolbox in MATLAB. The aging measurement has been done only on mineral oil, and results were matched using a predictive model of statistics and the Machine Learning Toolbox in MATLAB. Well-dispersed CeO2 NPs in the insulating oils lead to a significant increase in AC breakdown strength. The effect of ageing on the dielectric properties of nano oils yields better results than conventionally aged oil. It has been observed that the breakdown voltage is enhanced by up to 30% for mineral oil at an optimal concentration of 0.01 g/L, 9% for synthetic ester oil at 0.03 g/L, 18% for rapeseed oil at 0.02 g/L, and 19% for soybean oil at 0.03 g/L nanoparticle concentration. Following the dispersion of CeO2 nanoparticles, the dielectric constant of all insulating oils has also significantly improved. The overall experimental results are promising and show the potential of the CeO2 NPs-based nano oil as an efficient and highly performing dielectric oil for different power applications.

Aromatic hydrocarbons extracted by headspace and microextraction methods in water-soluble fractions from crude oil, fuels and lubricants.

Two extraction protocols were developed for the determination of mono- and poly-aromatic hydrocarbons in water-soluble fractions from gasoline, diesel, crude, mineral insulating, and lubricant oils. Development of the procedures was based on clean miniaturized strategies, such as headspace extraction and vortex-assisted dispersive liquid micro-extraction, together with quantification by gas chromatography-mass spectrometry. The mono-aromatic hydrocarbons were extracted using the headspace extraction method. The linear range obtained was 10-500 µg L-1, with r2 > 0.99. Based on the parameters of the analytical curves, detection and quantification limits of 2.56-3.20 and 7.76-9.71 µg L-1 were estimated. In addition, the method showed adequate recoveries of 69.4-83.5%, with a satisfactory precision of 4.7-17.1% (n = 5). Micro-extraction was applied for the poly-aromatics and the most favorable variables were sample volume (5.00 mL) in sodium chloride medium (1%, w/v), trichloromethane as extractor solvent (75 µL), acetone as disperser (925 µL) and vortexing for 1 min. Under these conditions, analytical curves of 0.15-4.00 µg L-1 were obtained and limits of determination and quantification were 0.03-0.15 and 0.09-0.46 µg L-1, respectively. Recovery values of 87.6-124.5% and a maximum relative standard deviation of 18.9% (n = 5) verify satisfactory accuracy and precision. This led to the achievement of enrichment factors for poly-aromatic hydrocarbons of 41-89 times. Finally, the methods were employed in samples of water-soluble fractions for the determination of analytes. The values followed the order: gasoline > diesel > crude > lubricant > mineral insulating oil. These results indicate an increase in lighter fractions, followed by poly-aromatics in more refined products.

Isotherm, Thermodynamic and Kinetic Studies of Elemental Sulfur Removal from Mineral Insulating Oils Using Highly Selective Adsorbent.

Elemental sulfur (S8) is a corrosive sulfur compound which was found to be extremely reactive to silver, causing intensive silver sulfide (Ag2S) deposition on on-load tap changer (OLTC) contacts in power transformers. A highly selective adsorbent (HSA), called Tesla'Ssorb, for the removal of S8 from mineral insulating oils was prepared from raw material (RM) using the novel procedure. In this study, the adsorption properties of HSA for the removal of S8 from the oil were determined. RM and HSA were characterized using various techniques, such as field-emission scanning electron microscopy (FESEM), energy-dispersive X-ray (EDX), and X-ray diffraction (XRD). The performance of HSA was determined by adsorption equilibrium, thermodynamic, and kinetic study through batch experiments, at various temperatures and initial concentrations of S8. The obtained results were analyzed by Langmuir and Freundlich adsorption isotherms and it was found that equilibrium data were fitted better with the Langmuir isotherm model. The maximum adsorption capacity was 4.84 mg of S8/g of HSA at 353 K. Thermodynamic parameters, such as enthalpy (ΔH°), Gibbs free energy (ΔG°), and entropy (ΔS°), were calculated and it was found that the sorption process was spontaneous (ΔG° < 0) and endothermic in nature (ΔH° > 0). It was found that the adsorption of S8 follows pseudo-second-order kinetic model, and the activation energy indicated the activated chemisorption process.

Study on the Anti-Aging Performance of Different Nano-Modified Natural Ester Insulating Oils Based on Molecular Dynamics.

In order to investigate the anti-aging performance of nano-modified natural ester insulating oils, in this paper, two different types of nanoparticles are selected to modify insulating oils. We studied the microscopic mechanism of nano-modified models using molecular simulation techniques. Three models were established: an oil-water model without the addition of nanoparticles and two which contained nano-Fe3O4 and nano-Al2O3 particles, where the concentration of water was 1 wt.%. The research found that the diffusion of water molecules in the nano-modified model was slow, and the water molecules generated from transformer insulation aging were adsorbed around the nanoparticles, which inhibited the diffusion of water molecules, reduced the hydrolysis of ester molecules, and effectively enhanced the anti-aging performance of natural ester insulating oil. Compared with two different types of nano-modified models, the interface compatibility between nano-Fe3O4 and natural ester insulating oil is better, the composite model is stable, the change rate of the diffusion coefficient with temperature is small, there are more hydrogen bonds generated by nano-Fe3O4 and water molecules, and the anti-aging performance of the nano-Fe3O4-modified oil model is better.

Lubrication Performances of Polyalkylene Glycols at Steel Interface under External Electric Fields.

This work studied the lubrication performances of polyalkylene glycols, which are insulating oils, at the steel interface under external electric fields. The results show that external electric fields greatly affect the lubrication performances of polyalkylene glycols, and there is an optimal voltage (-1.0 V) for the improvement in friction reduction performance. The surface analysis and experiment results indicate that the polyalkylene glycol adsorption film and the reduction in the amount of FexOy and FeOOH in the tribochemical film contribute to improved friction performance under the negative voltage condition. This work proves that the lubrication performances of insulating oils can be affected by external electric fields as well. A lubrication model was proposed, hoping to provide a basic understanding of the lubrication mechanisms of ether-bond-containing insulating oils in the electric environment.

One-Step Electrical Insulating Oil Regeneration on Electret PVDF/BaTiO3 Composite Nanofibers.

Insulating oil is a pivotal component of power transformers, but it suffers from aging byproducts during service operation. The aging byproducts from the degradation of oil insulation tend to induce insulation failure, which poses a significant threat to the security of the power grid. Therefore, the regeneration of insulating oil is required to prolong the useful life of insulating oil and hence be of economic and ecological interests. Typical in-use oil regeneration routes employ multi-step procedures. In this work, a one-step regeneration method using a PVDF/BaTiO3 composite membrane is proposed. BaTiO3 endows the composite membrane with improved hydrophobicity and an electret state. The regeneration performance of the PVDF/BaTiO3 nanofiber membrane was assessed by considering the acid value, moisture content, dielectric loss factor tan δ, and the AC breakdown voltage of the refreshed oil. The test results showed that the filtration efficiencies toward formic acid and moisture were up to 77.5% and 60.6%, respectively. Moreover, the dielectric loss factor tan δ of the refreshed oil decreased evidently at a power frequency, and the AC breakdown voltage rose from 23.7 kV to 38.9 kV. This suggests that the PVDF/BaTiO3 composite membrane may be employed efficiently, and it minimizes aging byproducts via the one-step filtration.

A Highly Sensitive and Stable rGO:MoS2-Based Chemiresistive Humidity Sensor Directly Insertable to Transformer Insulating Oil Analyzed by Customized Electronic Sensor Interface.

Reduced graphene oxide and molybdenum disulfide (rGO:MoS2) are the most representative two-dimensional materials, which are promising for a humidity sensor owing to its high surface area, a large number of active sites, and excellent mechanical flexibility. Herein, we introduced a highly sensitive and stable rGO:MoS2-based humidity sensor integrated with a low-power in-plane microheater and a temperature sensor, directly insertable to transformer insulating oil, and analyzed by a newly developed customized sensor interface electronics to monitor the sensor's output variations in terms of relative humidity (RH) concentration. rGO:MoS2 sensing materials were synthesized by simple ultrasonication without using any additives or additional heating and selectively deposited on titanium/platinum (Ti/Pt) interdigitated electrodes on a SiO2 substrate using the drop-casting method. The significant sensing capability of p-n heterojunction formation between rGO and MoS2 was observed both in the air and transformer insulating oil environment. In air testing, the sensor exhibited an immense sensitivity of 0.973 kΩ/%RH and excellent linearity of ∼0.98 with a change of humidity from 30 to 73 %RH, and a constant resistance deviation with an inaccuracy rate of 0.13% over 400 h of continual measurements. In oil, the sensor showed a high sensitivity of 1.596 kΩ/%RH and stable repeatability for an RH concentration range between 34 and 63 %RH. The obtained results via the sensor interface were very similar to those measured with a digital multimeter, denoting that our developed total sensor system is a very promising candidate for real-time monitoring of the operational status of power transformers.

A Promising Nano-Insulating-Oil for Industrial Application: Electrical Properties and Modification Mechanism.

Despite being discovered more than 20 years ago, nanofluids still cannot be used in the power industry. The fundamental reason is that nano-insulating oil has poor stability, and its electrical performance decreases under negative impulse voltage. We found that C60 nanoparticles can maintain long-term stability in insulating oil without surface modification. C60 has strong electronegativity and photon absorption ability, which can comprehensively improve the electrical performance of insulating oil. This finding has great significance for the industrial application of nano-insulating oil. In this study, six concentrations of nano-C60 modified insulating oil (CMIO) were prepared, and their breakdown strength and dielectric properties were tested. The thermally stimulated current (TSC) curves of fresh oil (FO) and CMIO were experimentally determined. The test results indicate that C60 nanoparticles can simultaneously improve the positive and negative lightning impulse and power frequency breakdown voltage of insulating oil, while hardly increasing dielectric loss. At 150 mg/L, the positive and negative lightning impulse breakdown voltages of CMIO increased by 7.51% and 8.33%, respectively, compared with those of FO. The AC average breakdown voltage reached its peak (18.0% higher compared with FO) at a CMIO concentration of 200 mg/L. Based on the test results and the special properties of C60, we believe that changes in the trap parameters, the strong electron capture ability of C60, and the absorption capacity of C60 for photons enhanced the breakdown performance of insulating oil by C60 nanoparticles.

Effect of Nanoparticle Morphology on Pre-Breakdown and Breakdown Properties of Insulating Oil-Based Nanofluids.

Nanoparticles currently in use are challenged in further improving the dielectric strength of insulating oil. There is a great need for a new type of nanoparticle to promote the application of insulating oil-based nanofluids in electric industries. This paper experimentally investigates the effect of nanoparticle morphology on pre-breakdown and breakdown properties of insulating oil-based nanofluids. The positive impulse breakdown voltage of insulating oil can be significantly increased by up to 55.5% by the presence of TiO2 nanorods, up to 1.23 times that of TiO2 nanospheres. Pre-breakdown streamer propagation characteristics reveal that streamer discharge channels turn into a bush-like shape with much denser and shorter branches in the nanofluid with TiO2 nanorods. Moreover, the propagation velocity of streamers is dramatically decreased to 34.7% of that in the insulating oil. The greater improvement of nanorods on the breakdown property can be attributed to the lower distortion of the electric field. Thus, when compared with nanospheres, pre-breakdown streamer propagation of nanofluid is much more suppressed with the addition of nanorods, resulting in a greater breakdown voltage.

The Effect and Associate Mechanism of Nano SiO2 Particles on the Diffusion Behavior of Water in Insulating Oil.

Moisture has a significant effect on the internal insulation performance of transformers, and is closely related to the breakdown voltage of transformer insulating oil. In the present work, we studied the effect of nano-SiO2 particles on the diffusion of water in insulating naphthenic mineral oil using molecular dynamics simulation. Six models were established, three of which contained nano-SiO2 particles together with water concentration of 1 wt.%, 2 wt.%, or 3 wt.%. For each model variations in free volume, mean square displacement, and interaction energy were assessed. The addition of nano SiO2 particles was found to reduce the free volume fraction of the model and as well as the free motion of water molecules in the oil. These particles also increased the interaction between the oil and water molecules, indicating that insulating oil containing nano-particles has a greater binding effect on water. The diffusion coefficient of water in oil containing nano-SiO2 particles was reduced, such that water molecules were less likely to diffuse. The results also show that these particles adsorb water molecules in the oil and to reduce diffusion. Consequently, the addition nano-scale SiO2 particles could potentially improve the breakdown voltage of the insulating oil.

Palm-Based Neopentyl Glycol Diester: A Potential Green Insulating Oil.

BACKGROUND: The transesterification of high oleic palm oil methyl ester (HOPME) with neopentyl glycol (NPG) has been investigated. The present study revealed the application of low-pressure technology as a new synthesis method to produce NPG diesters. Single variable optimization and response surface methodology (RSM) were implemented to optimize the experimental conditions to achieve the maximum composition (wt%) of NPG diesters. OBJECTIVE: The main objective of this study was to optimize the production of NPG diesters and to characterize the optimized esters with typical chemical, physical and electrical properties to study its potential as insulating oil. METHODS: The transesterification reaction between HOPME and NPG was conducted in a 1L three-neck flask reactor at specified temperature, pressure, molar ratio and catalyst concentration. For the optimization, four factors have been studied and the diester product was characterized by using gas chromatography (GC) analysis. The synthesized esters were then characterized with typical properties of transformer oil such as flash point, pour point, viscosity and breakdown voltage and were compared with mineral insulating oil and commercial NPG dioleate. For formulation, different samples of NPG diesters with different concentration of pour point depressant were prepared and each sample was tested for its pour point measurement. RESULTS: The optimum conditions inferred from the analyses were: molar ratio of HOPME to NPG of 2:1.3, temperature = 182°C, pressure = 0.6 mbar and catalyst concentration of 1.2%. The synthesized NPG diesters showed very important improvement in fire safety compared to mineral oil with flash point of 300°C and 155°C, respectively. NPG diesters also exhibit a relatively good viscosity of 21 cSt. The most striking observation to emerge from the data comparison with NPG diester was the breakdown voltage, which was higher than mineral oil and definitely in conformance to the IEC 61099 limit at 67.5 kV. The formulation of synthesized NPD diesters with VISCOPLEX® pour point depressant has successfully increased the pour point of NPG diester from -14°C to -48°C. CONCLUSION: The reaction time for the transesterification of HOPME with NPG to produce NPG diester was successfully reduced to 1 hour from the 14 hours required in the earlier synthesis method. The main highlight of this study was the excess reactant which is no longer methyl ester but the alcohol (NPG). The optimum reaction conditions for the synthesis were molar ratio of 2:1.13 for NPG:HOPME, 182°C, 0.6 mbar and catalyst concentration of 1.2 wt%. The maximum NPG diester yield of 87 wt% was consistent with the predicted yield of 87.7 wt% obtained from RSM. The synthesized diester exhibited better insulating properties than the commercial products especially with regards to the breakdown voltage, flash point and moisture content.