Biswajit Chakraborty

This paper primarily focuses on the transformer oil ageing sensitive diagnostic approach utilizing the inflection frequency derived from the differential capacitance spectrum. Continuous transformer operation results oxidation in oil, leading to the formation of low molecular weight (LMW) acids which accelerate cellulose hydrolysis and insulation degradation. Therefore, accurately monitoring of this acid-induced ageing is crucial. Considering this fact, for emulating different acid aged stages (0-30 years), formic, acetic and levulinic acids with different proportions are mixed with mineral oil and its different nanofluids (doped with 0.01 g/L of Alumina (Al₂O₃), Titania (TiO₂) and Hexagonal Boron Nitride (h-BN) separately). Then, Nuclear Magnetic Resonance (NMR) spectroscopy and Frequency Domain Spectroscopy (FDS) are performed to analyze the effect of acid ageing on the physicochemical changes and the dipolar orientation of liquid dielectric. From FDS spectra, the inflection points in differential capacitance spectrum are derived from which the defect densities of the prepared oil samples are estimated. From the results of inflection point and defect density, three ageing sensitive parameters are identified and their empirical correlations with ageing severity were established.

This article analyzes the effects of aging on the dielectric properties of mineral oil (MO), natural ester (NE), and synthetic ester (SE), with artificially acid-induced changes estimated through the analysis of the relaxation frequency distribution (RFD) spectrum. For this purpose, liquid insulation samples having equivalent acid-induced aging periods of 0, 5, 10, 15, and 20 years are emulated by adding formic, acetic, and levulinic acids to the mineral and ester oils. Thereafter, Fourier transform infrared (FTIR) spectroscopy and relaxation current measurement are conducted on these aged samples to investigate the impact of aging on physicochemical changes and different polarization characteristics of the insulation liquid, respectively. The RFD spectrum is derived from the relaxation current for different-aged samples. The analysis of the RFD spectrum reveals different dipolar relaxation-sensitive zones. Every zone of the RFD spectrum carries signature information about the dipolar characteristics relating the aging state with respect to the acid content of the liquid insulation. From the RFD spectrum, four aging-sensitive parameters (peaks and corresponding frequencies of the RFD spectrum) are identified, and based on these parameters, two empirical relations are derived. Experimental investigation shows that the four parameters can be good indicators of the aging status of liquid insulation.

This research investigated the influence of insulating (Al2O3), semiconducting (TiO2), and conducting (Fe3O4) Nanoparticles (NPs) on the breakdown strength of Nomex-based polymeric Nanocomposites (NCs). Seven samples were fabricated and thermally aged at 145 °C for 600 h to simulate accelerated degradation. Fourier Transform Infrared Spectroscopy (FTIR) was conducted to unaged, 300 h, and 600 h aging durations to examine the chemical alteration and understand the NP-induced resistance of meta-aramid polymeric chains against the thermal aging. The AC Breakdown Voltage (ACBDV) was measured every 100 h of aging, and the results were analyzed using the Weibull distribution to extract the scale parameters, shape parameters, and p-values. Cumulative breakdown probabilities at 1%, 10%, and 50% risk levels were evaluated to assess the impact of different NPs on the breakdown mechanism. After 600 h of aging, the incorporation of 1 wt% Al2O3 improved the BDV of pristine Nomex by 28.2%. At a 50% risk probability, BDV enhancements of 63.16% (Al2O3), 48.89% (TiO2), and 42.39% (Fe3O4) were achieved, demonstrating the superior performance of NP-reinforced Nomex insulation under thermal stress..

In this work, a hardware module is developed to monitor real-time power consumption of home appliances at regular time intervals. The module comprises one microcontroller units, a voltage sensor, and five current sensors. This paper introduces a cost-effective and easy to deploy Hybrid Power Factor (PF) Selection Algorithm (HPFSA), which enables active power measurement with good accuracy and minimizes the required hardware components for this module. The developed module considers PF computation error with supply frequency variation through HPFSA and gives accurate value of true power in real-time. Additionally, it can sense the total energy consumption of various appliances distributed throughout the home and send the consumed power data to the cloud for remote monitoring. This real-time load monitoring of home appliances is essential for applications such as energy conservation, smart home automation, and load management.

In this study, aging impact analysis on dielectric behaviour of mineral oil, natural and synthetic ester is performed and their aging status is estimated using the hump phenomenon obtained from dielectric modulus spectrum. For this purpose, equivalent aging of 5, 10, 15 and 20 years of each oil are emulated by mixing formic, acetic, and levulinic acid with mineral and ester oils. Thereafter, Fourier Transform Infrared Spectroscopy and Frequency Domain Spectroscopy (FDS) are conducted on the prepared aged samples to assess the impact of aging on physicochemical alteration and low-frequency interfacial polarization characteristics at different temperatures, respectively. Based on the FDS results, dielectric modulus spectrum is obtained from which hump phenomenon is identified. Besides, another important factor i.e. conduction dominance factor (CDF) is introduced to quantitatively investigate the dominance of conduction mechanism over relaxation polarization. Based on the experimental results, a correlation with the aging status of liquid insulation with the three aging sensitive parameters (hump frequency, hump peak and CDF) is established which can reliably be used for estimation of their aging status.

This study proposes an advanced method for sensing the aging state of epoxy nanocomposite insulation. For this purpose, five types of epoxy nano-composites (EPNC) samples (i.e. pure epoxy, epoxy with alumina or titania having concentration of 1wt% or 2wt%) have been prepared in the laboratory. The prepared test samples were undergone through accelerated electro-thermal aging (at 6 kV, 50-Hz and 100°C temperature) for 600 hours. After every 100 hours of aging duration, different lightning impulse voltage (both standard and non-standard) were applied on those test samples and corresponding impulse response current were recorded using the developed experimental arrangement. From the recorded signal, three aging-sensitive parameters are identified i.e. tail-time (T_t), peak impulse current (I_P), and area under the curve (A). Thereafter, those three parameters are correlated with the aging state of the insulation through three novel empirical relations. Finally, the effectiveness of the proposed empirical relationships is validated using a separate set of laboratory-prepared EPNC insulations having known aging state. The analysis of the validation results shows that the T_t, I_P, and A can sense the aging state of EPNC with maximum errors of 2.55%, 4.03%, and 3.60%, respectively. It is yet to be mentioned here that; this advanced methodology for assessing insulation aging state that is less susceptible to noise interference and consume less measurement time. Hence, this method leverages the analysis of three newly identified aging-sensitive parameters extracted from current responses under impulse voltage testing for establishing the empirical relations with aging.

This article presents a novel approach to accurately measure moisture levels in power transformer oil-paper insulation by analyzing dielectric response currents under standard and nonstandard lightning impulse (NSLI) voltages. Laboratory-prepared samples emulating transformer paper insulation with varying moisture levels are impregnated in different oils (mineral, vegetable, or their nanofluids) and are subjected to lightning impulse testing. Response currents are recorded, and transfer functions are evaluated by examining applied voltage and response current. Five coefficients (three from the numerator, ${a}2$ , ${a}1$ , and ${a}0$ , and two from the denominator, ${b}1$ and ${b}0$ ) are found sensitive to moisture content variations. Therefore, empirical relationships between these coefficients and paper moisture content (%pmc) are developed and are validated using newly prepared samples with different moisture contents, yielding maximum errors below 2.75% for NSLI and 3.5% for SLI. These findings offer valuable insights into transformer insulation conditions, enabling timely preventive measures to mitigate transformer failure.

In this work, a novel method is adopted to sense the condition of the transformer oil based nanofluid insulation considering moisture content by dielectric relaxation current. For this investigation, mineral oil, vegetable oil and their nano-fluids (TiO₂ and Al₂O₃ based) impregnated paper insulation prototypes with different moisture content are prepared in the laboratory. It is to be mentioned here that, lifespan of a transformer predominantly relies on the state of its insulation which consists of oil and paper. From the experimentally measured dielectric relaxation current data, Relaxation Frequency Distribution (RFD) spectrum of the prepared samples is evaluated. From RFD spectrum, the condition of oil and paper can be sensed distinctly. In addition, from the RFD spectrum, various parameters are identified to be moisture sensitive. Using these parameters, empirical relations are proposed to sense the moisture content and activation energy which are further verified experimentally. The experimental results show that the suggested moisture sensing method is reliable for assessing the insulation condition which can pave a new way for maintenance plan of transformers.

In this paper, a microcontroller based smart Fault Handling System (FHS) is proposed which is capable of early sensing and managing the Thermal Runaway (TR) event in real-time Battery Management System (BMS) through online Internal Resistance (IR) computation method. In overcharging region of Lithium-ion (Li-ion) Batteries (LIBs), TR is one of the critical issues which occur when used in Electric Vehicles (EVs) and Battery Energy Storage Systems (BESSs). Therefore, a proper sub-system is utmost required in the BMS for detecting the TR event quite early, which will automatically prevent the battery modules from critical accidents like fire, explosion, etc. The developed smart FHS utilizes an efficient, cost-effective and reliable online IR sensing based Early Thermal Runaway Sensing (ETRS) system which detects the TR event !+3.9 minutes prior to the TR onset point (outperforming the other detection methods) and shuts down the charging mechanism. Additionally, this system sends an IoT based Short Message Service (SMS) alert notification to the users allowing them to take necessary preventive steps.

This article proposes a methodology to estimate the aging state of the Nomex based dry-type nano-composite (NDNC) insulation. For this purpose, seven types of NDNC insulation samples are prepared in the laboratory for experimental investigation. The test samples are undergone through accelerated thermal aging at 145°C for 600 hours in steps of 100 hours. The dielectric spectroscopy measurements are conducted on the NDNC type insulation samples at each aging stages. Three aging sensitive parameters (i.e. transfer function pole, de-trapped charge and hopping conductivity) are extracted from the experimental results obtained by dielectric spectroscopy (i.e. polarization and depolarization current (PDC) and complex permittivity). From the experimental results, it is observed that these three parameters are altered with the duration of the thermal aging. This fact signifies that these parameters can be utilized as aging sensitive markers. Therefore, using these three aging sensitive parameters, three empirical relationships are derived to correlate the thermal aging status of the NDNC insulation. Finally, the derived relationships are validated through different set of test samples having known aging status. Hence, this experimental investigation reveals that the proposed technique can suitably assess the thermal aging state of the NDNC insulation.