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This paper presents an alternative approach to determine the simplified top-oil temperature (TOT) based on the pathway of energy transfer and thermal-electrical analogy concepts. The main contribution of this study is the redefinition of the nonlinear thermal resistance based on these concepts. An alternative approximation of convection coefficient, h, based on heat transfer theory was proposed which eliminated the requirement of viscosity. In addition, the lumped capacitance method was applied to the thermal-electrical analogy to derive the TOT thermal equivalent equation in differential form. The TOT thermal model was evaluated based on the measured TOT of seven transformers with either oil natural air natural (ONAN) or oil natural air forced (ONAF) cooling modes obtained from temperature rise tests. In addition, the performance of the TOT thermal model was tested on step-loading of a transformer with an ONAF cooling mode obtained from previous studies. A comparison between the TOT thermal model and the existing TOT Thermal-Electrical, Exponential (IEC 60076-7), and Clause 7 (IEEE C57.91-1995) models was also carried out. It was found that the measured TOT of seven transformers are well represented by the TOT thermal model where the highest maximum and root mean square (RMS) errors are 6.66 °C and 2.76 °C, respectively. Based on the maximum and RMS errors, the TOT thermal model performs better than Exponential and Clause 7 models and it is comparable with the Thermal-Electrical 1 (TE1) and Thermal-Electrical 2 (TE2) models. The same pattern is found for the TOT thermal model under step-loading where the maximum and RMS errors are 5.77 °C and 2.02 °C. [ABSTRACT FROM AUTHOR]

This paper presents a study on the application of the Markov Model (MM) to determine the transformer population states based on Health Index (HI). In total, 3195 oil samples from 373 transformers ranging in age from 1 to 25 years were analyzed. First, the HI of transformers was computed based on yearly individual oil condition monitoring data that consisted of oil quality, dissolved gases, and furanic compounds. Next, the average HI for each age was computed and the transition probabilities were obtained based on a nonlinear optimization technique. Finally, the future deterioration performance curve of the transformers was determined based on the MM chain algorithm. It was found that the MM can be used to predict the future transformers condition states. The chi-squared goodness-of-fit analysis revealed that the predicted HI for the transformer population obtained based on MM agrees with the average computed HI along the years, and the average error is 3.59%. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study on the AC breakdown voltages of Refined, Bleached and Deodorized Palm Oil (RBDPO) Olein and Coconut Oil (CO) in the presence of conductive (Iron (II,III) Oxide, Fe3O4), semi-conductive (Copper (II) Oxide, CuO) and insulative (Aluminium Oxide, Al2O3) nanoparticles without and with surfactant. The type of surfactant used in this study was Cetyl Trimethyl Ammonium Bromide (CTAB). The volume concentrations range of Fe3O4, CuO and Al2O3 was varied from 0.001% to 0.05%. Transmission Electron Microscope (TEM) was used to characterize the nanoparticles in RBDPO and CO. AC breakdown voltage tests were carried out for RBDPO and CO of which the AC breakdown voltage at 1% probability was determined based on Weibull distribution. It is found that only Al2O3 can improve the average AC breakdown voltage of RBDPO and CO. The AC breakdown voltages at 1% probability for RBDPO and CO can be improved through introduction of Fe3O4, CuO and Al2O3 at certain volume concentrations. Al2O3 provides the highest enhancement of AC breakdown voltages at 1% probability for RBDPO and CO with the highest percentage of improvement can be up to 52%. CTAB has no clear effect on the improvement of AC breakdown voltages of RBDPO and CO based Fe3O4, CuO and Al2O3 nanofluids. [ABSTRACT FROM AUTHOR]

This paper presents an investigation on the resonant oscillations of an 11 kV layer-type winding transformer under standard and chopped lightning impulse overvoltage conditions based on calculated parameters. The resistances, inductances and capacitances were calculated in order to develop the transformer winding equivalent circuit. The impulse overvoltages were applied to the high voltage (HV) winding and the resonant oscillations were simulated for each of the layers based on different electrostatic shield placement configurations. It is found that the placement of grounded shields between layer 13 and layer 14 results in the highest resonant oscillation and non-linear initial voltage distribution. The oscillation and linear stress distributions are at the lowest for shield placement between the HV and low voltage (LV) windings. [ABSTRACT FROM AUTHOR]

This paper presents an investigation on the sensitivity of frequency response of a 500 kVA, 11/0.433 kV distribution transformer with and without the presence of a winding clamping structure. Frequency response analysis (FRA) measurements of multiple test configurations were carried out with and without the presence of a winding clamping structure. Statistical analyses based on Pearson's correlation coefficient (PCC), Spearman's correlation coefficient (SCC), Kendall's correlation coefficient (KCC), cross-correlation coefficient (CCF), root mean square error (RMSE), absolute sum of logarithmic error (ASLE), hypothesis test (F-test) and relative factor (RF) were applied to determine the effect of the winding clamping structure. It was found that the removal of the winding clamping structure has an impact on the frequency response signature at the frequency less than 2 kHz during offline measurement. It was found that ASLE and F-test are suitable methods that can be used to indicate the variation of frequency response caused by clamping structure removal of the distribution transformer under study. [ABSTRACT FROM AUTHOR]

This paper presents a study to estimate individual condition parameters of the transformer population based on Markov Model (MM). The condition parameters under study were hydrogen (H2), methane (CH4), acetylene (C2H2), ethylene (C2H4), ethane (C2H6), carbon monoxide (CO), carbon dioxide (CO2), dielectric breakdown voltage, interfacial tension, colour, acidity, water content, and 2-furfuraldehyde (2-FAL). First, the individual condition parameter of the transformer population was ranked and sorted based on recommended limits as per IEEE Std. C57. 104-2008 and IEEE Std. C57.106-2015. Next, the mean for each of the condition parameters was computed and the transition probabilities for each condition parameters were obtained based on non-linear optimization technique. Next, the future states probability distribution was computed based on the MM prediction model. Chi-square test and percentage of absolute error analysis were carried out to find the goodness-of-fit between predicted and computed condition parameters. It is found that estimation for majority of the individual condition parameter of the transformer population can be carried out by MM. The Chi-square test reveals that apart from CH4 and C2H4, the condition parameters are outside the rejection region that indicates agreement between predicted and computed values. It is also observed that the lowest and highest percentages of differences between predicted and computed values of all the condition parameters are 81.46% and 98.52%, respectively. [ABSTRACT FROM AUTHOR]

In this paper, a maintenance cost study of transformers based on the Markov Model (MM) utilizing the Health Index (HI) is presented. In total, 120 distribution transformers of oil type (33/11 kV and 30 MVA) are examined. The HI is computed based on condition assessment data. Based on the HI, the transformers are arranged according to its corresponding states, and the transition probabilities are determined based on frequency of a transition approach utilizing the transformer transition states for the year 2013/2014 and 2012/2013. The future states of transformers are determined based on the MM chain algorithm. Finally, the maintenance costs are estimated based on future-state distribution probabilities according to the proposed maintenance policy model. The study shows that the deterioration states of the transformer population for the year 2015 can be predicted by MM based on the transformer transition states for the year 2013/2014 and 2012/2013. Analysis on the relationship between the predicted and actual computed numbers of transformers reveals that all transformer states are still within the 95% prediction interval. There is a 90% probability that the transformer population will reach State 1 after 76 years and 69 years based on the transformer transition states for the year 2013/2014 and 2012/2013. Based on the probability-state distributions, it is found that the total maintenance cost increases gradually from Ringgit Malaysia (RM) 5.94 million to RM 39.09 million based on transformer transition states for the year 2013/2014 and RM 37.56 million for the year 2012/2013 within the 20 years prediction interval, respectively. [ABSTRACT FROM AUTHOR]

In this paper, an assessment on the health index (HI) of transformers is carried out based on Neural-Fuzzy (NF) method. In-service condition assessment data, such as dissolved gases, furans, AC breakdown voltage (ACBDV), moisture, acidity, dissipation factor (DF), color, interfacial tension (IFT), and age were fed as input parameters to the NF network. The NF network were trained individually based on two sets of data, known as in-service condition assessment and Monte Carlo Simulation (MCS) data. HI was also obtained from the scoring method for comparison with the NF method. It is found that the HI of transformers that was obtained by NF trained by MCS method is closer to scoring method than NF trained by in-service condition assessment method. Based on the total of 15 testing transformers, NF trained by MCS data method gives 10 transformers with the same assessments as scoring method as compared to eight transformers given by NF trained by in-service condition data method. Analysis based on all 73 transformers reveals that 62% of transformers have the same assessments between NF trained by MCS data and scoring methods. [ABSTRACT FROM AUTHOR]

Faced with the increasingly serious energy crisis and environmental pollution problems, traditional internal combustion engine vehicles are receiving more and more resistance, which has rapidly promoted the development of new energy electric vehicles. Permanent magnet synchronous motors are widely used in new energy electric vehicles and in other fields because of their simple structure, light weight, small size, and high power density. With the continuous advancement of production technology, the requirements of accuracy, rapidity, and stability in permanent magnet synchronous motor systems have gradually increased. Among many advanced control technologies, this paper proposes an optimized model predictive torque control strategy based on voltage vector expansion. This strategy involves the construction of a reference stator flux linkage vector based on the analytical relationship between electromagnetic torque, reference stator flux linkage amplitude, and rotor flux linkage and the transfer of the separate control of electromagnetic torque and flux linkage amplitude into flux linkage vector control. At the same time, the optimal duty cycle corresponding to the two adjacent extended voltage vectors and the zero vector is calculated according to geometric relationships so as to realize the three voltage vector duty cycle optimization control. Experimental results show the effectiveness and superiority of the proposed strategy. [ABSTRACT FROM AUTHOR]

In recent years, the imminent environmental problems and increasing attention to the global energy crisis have prompted the need for new opportunities and technologies to meet higher demands for clean and sustainable energy systems. As a result, new energy electric vehicles have been developed to replace fossil fuel cars. Therefore, this paper presents a three-phase interleaved parallel bidirectional buck–boost converter, which is the core factor of electrical energy flow regulation and management between the battery pack and motor drive inverter within the high voltage direct current bus and converts the voltage from two directions. Corresponding circuit topology, mathematical model, and control strategy are analyzed in three operation states: charge buck, discharge boost, and electric energy interaction modes. The digital implementation with double closed loop, power feedforward compensation, and bidirectional switching logic are realized by XDPTM Digital Power Controllers XDPP1100-Q040 of Infineon Technologies AG. Finally, the experimental results of the proposed converter clearly show that it achieves the objectives, namely, the feasibility and practicality of the system. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) farms currently play a vital role in the generation of electrical power in different countries, such as Malaysia, which is moving toward the use of renewable energy. Malaysia is one of the countries with abundant sunlight and thus can use solar PV farms as alternative sources for electricity generation. However, lightning strikes frequently occur in the country. Being installed in open and flat areas, solar PV farms, especially their electronic components, are at great risk of damage caused by lightning. In this paper, the effects of lightning currents with different peak currents and waveshapes on grid-connected solar PV farms were determined to approximate the level of transient effect that can damage solar PV modules, inverters and transformers. Depending on the location of the solar PV farm, engineer can obtain information on the peak current and median current of the site from the lightning location system (LLS) and utilise the results obtained in this study to appropriately assign an SPD to protect the solar panel, inverter and the main panel that connected to the grid. Therefore, the simulation results serve as the basis for controlling the effects of lightning strikes on electrical equipment and power grids where it provides proper justification on the 'where to be installed' and 'what is the rating' of the SPD. This judgment and decision will surely reduce the expensive cost of repair and replacement of electrical equipment damages due to the lightning. [ABSTRACT FROM AUTHOR]

This paper presents lightning (1.2/50 µs) breakdown voltages of palm oil (PO), coconut oil (CO) and mineral oil (MO) in a quasi-uniform sphere to sphere electric field at two gap distances. The type of PO used in this study is Refined Bleached Deodorized Palm Oil (RBDPO) Olein type. The effect of voltage polarities (positive and negative) and testing methods (rising voltage, up and down and multiple level) on the lightning breakdown performance were investigated. The results indicated that lightning breakdown voltages of CO and RBDPO are comparable to those of MO under various test conditions. The results indicated that there is no polarity effect for lightning impulse breakdown tests in a quasi-uniform field. The testing methods, including rising voltage method, up and down method and multiple level method have a notable influence on the breakdown voltages. The effect of the 50% breakdown voltage on rising voltage method, up and down method and multiple level method for RBDPO and CO is comparable to MO. The withstand voltage at 1% and 50% breakdown probabilities were obtained using the Normal distribution fitting on the cumulative probability plot of impulse shots. Based on a normal distribution fitting, withstand voltages 1% breakdown probability of POA were close to the MO. Finally, based on statistical studies and simulation using ANSYS software, the prediction formulas for breakdown voltage for larger gap distances for all samples were derived. [ABSTRACT FROM AUTHOR]