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Sustainability has been one of the most important topics discussed lately-part of sustain ability strategies focusing on global warming and food security issues. Alternative energy sources of various kinds have been explored and applied to mitigate the impact of fossil fuels in the last decade. The electricity generation from living plants has evolved as a new alternative renewable energy source known as a plant microbial fuel cell (PMFC). This paper investigated the bioelectricity generation in economic crops at aquaponics systems using PMFC. The result reveals that economic crops could generate bioelectricity using the PMFC. In the experiment, a single-chamber PMFC configuration was conducted on two economic crops, chilli and okra, with graphite felt as an electrode. As a result, chilli generated 19.58 nW while okra generated 17.00 nW, where chilli outperformed the okra in terms of power generation.

The intent of this research paper is to examine the AC withstand voltage of palm oil based CuO nanofluids while considering varieties of surfactants. Refined, Bleached and Deodorized Palm Oil (RBDPO) was used in this investigation, whereas mineral oil was used as a reference. This experimental work used Cetyl Trimethyl Ammonium Bromide (CTAB), Sodium Dodecyl Sulfate (SDS) and Oleic Acid (OA) as surfactants. The ratio of the volume concentration surfactant to the nanoparticles was fixed to 1:2. The AC breakdown voltage tests for RBDPO and mineral oil were conducted at gap distance of 1 mm according to ASTM D1816 of which the AC withstand voltage at 1% probability was obtained using Weibull distribution. It is found that the AC withstand voltage at 1% probability is much greater for RBDPO-based CuO with various surfactants than that mineral oil.

This study presents an examination of partial discharge (PD) localization in oil based on acoustic emission technique utilizing fuzzy logic. First, the PD measurement and localization systems are developed. In total, 2 coordinates of needle-plane electrodes that represent the PD location and 336 acoustic emission sensor (AES) coordinates are examined. The electrical PD is measured through an impedance matching circuit (IMC). The acoustic PD is acquired through AES and its signal is boosted by a preamplifier gain unit. The acoustic and electrical PDs are collected once the voltage reaches 30 kV. The data are first preprocessed by discrete wavelet transform (DWT) whereby it will be further analyzed by time of arrival (TOA), fuzzy logic Mamdani (FLM), and fuzzy logic Takagi–Sugeno (FLTS) methods. The arrival of time and distance between PD and AES are calculated based on TOA to find the PD location. Next, TOA and distance to PD location are used to define the input and output membership functions for FLM and FLTS to determine the PD location. It is found that FLTS has a great potential to be used for localization of the PD in oil whereby it has the lowest errors between actual PD location and AES. The performance of FLM and TOA is inferior to FLTS whereby the errors between actual PD location and AES are quite high for both PD locations.

This paper proposes a new version of the perturb and observe (P&O) algorithm which is able to recognize the global maximum power point (GMPP) among the multiple maximum peaks that exist in the P-V curve under the effect of the partial shading condition (PSC). For the first time, Trapezoidal rule concept is employed in P&O approach as a new consideration in the tracking process to calculate the best path for precisely tracking the GMPP. The new algorithm allows the search to continue until the extremum maximum is identified among numerous local maximums, rather than being imprisoned at one of the local maximums as is the case with the standard algorithm. Furthermore, the algorithm is able to achieve the MPP efficiently under the presence of rapid and abrupt changes in irradiation levels. The proposed Trapezoidal rule based P&O algorithm is evaluated under three conditions: (1) under uniform irradiance (2) under shading conditions and (3) under sudden and step changes in irradiation levels as well as the transition between shading patterns. The feasibility and effectiveness of the suggested algorithm, as well as the well-designed boost converter, are validated using two different methodologies: a simulation model in MATLAB/Simulink and hardware implementation by the (TMS320F28335) digital signal processing controller. Both simulation and hardware results confirm that the proposed algorithm provides excellent efficiency of 100% and 99.6% respectively. The GMPP is achieved within less than 100 ms, which is extremely advantageous tracking time, that avoids the power losses. In addition, the minimal steady-state oscillation is shown, with the desired level of simplicity without the need to complicated computations or random particles.

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.

This article presents a microcontroller-based direct current (DC) energy data logger developed by adapting low-cost ATmega328 by measuring the PV system DC and voltage characteristics while simultaneously recording the measured value over time to compute the energy production Watt-hour (Wh). The prototype logger has been tested on a live 1 kW standalone PV system where the voltage sensor detects PV series array output voltage ranging between 0–50 VDC by a voltage divider sensing circuit. For accurate sensing of the current output measurement from the PV array, 50A ACS756 hall effect IC was integrated as the current sensor. The data was measured and saved in text format with comma-separated values (CSV) in an SD card, read using Microsoft Excel software. The liquid crystal display (LCD) showed the actual value of the recording process’s current, voltage, power, and duration in minutes. The recorded data has been compared to the standard laboratory digital multimeter for calibration manually to justify the measurement value. The error is minimized to 0.6% average by varying the constant float value in the programming code. The advantage of developing this logger is that the development cost is much cheaper than the standard commercial PV energy meter, can be reproduced for other DC application energy measurements, and easily modify the voltage and current range to suit the application. Apart from that, this logger also provides high accuracy performance, and its independent characteristic is practical for off-grid or off-site PV system use.

This work examines the impact of multi pre-exponential factors on the lifetime modelling of the paper in oil-immersed transformers. First, the corresponding pre-exponential factor was determined based on the concentrations of the three parameters known as oxygen, moisture and acid. Next, the pre-exponential factor for each of the parameters at different concentrations was combined based on the summative approach to obtain the overall impact on the lifetime of the paper. It is found that the expected life of the paper for overall multi pre-exponential factors is higher than either single or double pre-exponential factors. For a single pre-exponential factor, the expected life of the paper decreases by a factor of 59.8 as the oxygen concentration increases from 15,000 ppm to 210,000 ppm. Moisture can decrease the expected life of the paper by a factor of 34 as it increases from 0.5% to 5%. Low molecular weight acid (LMA) has a higher impact than high molecular weight acid (HMA), whereby its impact is further enhanced through multi pre-exponential factor effect whereby the expected life of the paper decreases by a factor of 7.9 as the moisture content increases from 0.5% to 5% and oxygen increases from 300 ppm to 20,000 ppm.

An oil-filled transformer should be able to operate for a long time with proper maintenance. One of the best diagnostic methods for oil-immersed transformer condition is dissolved gas analysis (DGA). However, there are times where the produce of stray gassing event might lead to fault indication in the transformer. Machine learning algorithms are used to classify the DGA data into normal condition and corresponding faults based on IEEE limits and Duval pentagon method. The algorithms that will be used include boosted trees, RUS boosted trees and subspace KNN, which belongs to the same ensemble group. Data resampling technique (SMOTETomek) is applied and shows further improvement on the accuracy of predictions by machine learning algorithms when deal with imbalance data. The algorithms are able to achieve the accuracy of 82.6% (boosted trees), 81.2% (RUS boosted trees) and 72.5% (subspace KNN), respectively, when validated with actual transformer condition.

This article presents a microcontroller-based direct current (DC) energy data logger developed by adapting low-cost ATmega328 by measuring the PV system DC and voltage characteristics while simultaneously recording the measured value over time to compute the energy production Watt-hour (Wh). The prototype logger has been tested on a live 1 kW standalone PV system where the voltage sensor detects PV series array output voltage ranging between 0–50 VDC by a voltage divider sensing circuit. For accurate sensing of the current output measurement from the PV array, 50A ACS756 hall effect IC was integrated as the current sensor. The data was measured and saved in text format with comma-separated values (CSV) in an SD card, read using Microsoft Excel software. The liquid crystal display (LCD) showed the actual value of the recording process’s current, voltage, power, and duration in minutes. The recorded data has been compared to the standard laboratory digital multimeter for calibration manually to justify the measurement value. The error is minimized to 0.6% average by varying the constant float value in the programming code. The advantage of developing this logger is that the development cost is much cheaper than the standard commercial PV energy meter, can be reproduced for other DC application energy measurements, and easily modify the voltage and current range to suit the application. Apart from that, this logger also provides high accuracy performance, and its independent characteristic is practical for off-grid or off-site PV system use.

In this study, statistical distribution model (SDM) is used to predict the health index (HI) of transformers by utilizing the condition parameters data from dissolved gas analysis (DGA), oil quality analysis (OQA), and furanic compound analysis (FCA), respectively. First, the individual condition parameters data were categorized based on transformer age from year 1 to 15. Next, the individual condition parameters data for every age were fitted while using a probability plot to find the representative distribution models. The distribution parameters were calculated based on 95% confidence level and extrapolated from year 16 to 25 through representative fitting models. The individual condition parameters data within the period were later calculated based on the estimated distribution parameters through the inverse cumulative distribution function (ICDF) of the selected distribution models. The predicted HI was then determined based on the conventional scoring method. The Chi-square test for statistical hypothesis reveals that the predicted HI for the transformer data is quite close to the calculated HI. The average percentage of absolute error is 2.7%. The HI that is predicted based on SDM yields 97.83% accuracy for the transformer data.

Nanoparticles are generally anti-lipophilic and have a tendency to aggregate when they are embedded in nanofluids. Thus, surfactants have a major role in achieving long term dispersion stability of nanofluids through surface modification of nanoparticles. However, the surfactant changes the structure of the interfacial zone around nanoparticles and can have a crucial impact on the dielectric properties of dielectric nanofluids. Accordingly, this paper aims to clarify the role of interfacial zone on dielectric properties of vegetable oil based Al 2 O 3 nanofluids including relative permittivity, dissipation factor, and AC breakdown voltage. Moreover, a polarization model of nanofluids was proposed to calculate their relative permittivity considering surfactant effect. Different filler levels ranging from 0.01 wt% to 0.05 wt% were used and various temperature ranges were considered to validate the proposed model. Relative permittivity calculated from the proposed model was almost in line with experimental results. Proposed model depicted that surfactant contributes for orientational polarization of nanoparticles in the relative permittivity calculation. So, improvement in the relative permittivity of dielectric nanofluids has been attained from 0.01 wt% to 0.05 wt% of Al 2 O 3 nanoparticles due to both internal and orientational polarization of nanoparticles. Regarding dissipation factor of prepared nanofluids, it decreased against the weight percentage of nanoparticles, while the mean AC breakdown voltage increased against the weight percentage. All these effects were discussed considering the structure of interfacial zone and its impact on the alignment of oil chains and the energy loss of electrons.

PV–TEG hybrid system is widely discussed nowadays, as an alternative way to maximize solar radiation energy which is from both of its light and heat. In recent years, the idea of using thermoelectric generators (TEGs) to extract energy from heat waste has increased with applications varying from milliwatts to kilowatts. To form a circuit, numbers of TEG modules can be connected in series and/or parallel configuration to produce the required voltage and/or current. In the PV–TEG systems, due to operating environments, each TEG module’s power generation is subject to temperature mismatch. There is also considerable variability in the electro-thermal output and mounting pressure of each TEG module in a circuit, resulting in a significant inconsistency. Therefore, when each TEG in the array is active, a varying electrical operating point will occur at which peak energy can be obtained and problems with lower power output will occur. In this work, an individual TEG module test method was used to measure and analyze data from specific types of TEG, and a record of the maximum power output under different temperature variations is obtained. Then, the performance of the TEG system is measured and evaluated with a test bench where the modules are attached at different backside areas of generic PV panels. The non-uniform heat distribution condition created in the experiment showed an average 33 % drop in power production from the maximum power that would be available in case each TE series circuit operates under uniform heat distribution. This experimental finding demonstrates the problem and the outcomes discussed in this paper validated a thorough examination of the effect of nonuniform operating temperatures on a range of thermoelectric generator’s energy output.

This experimental study aims to examine the partial discharge (PD) properties of palm oil and coconut oil (CO) based aluminum oxide (Al2O3) nanofluids with and without surfactants. The type of surfactant used in this study was sodium dodecyl sulfate (SDS). The volume concentrations range of Al2O3 dispersed in oil samples was varied from 0.001% to 0.05%. The ratio of surfactants to nanoparticles was set to 1:2. In total, two different types of refined, bleached and deodorized palm oil (RBDPO) and one type of CO were measured for PD. Mineral oil (MO) was also examined for comparison purpose. PDIV measurements for all samples were carried out based on rising voltage method whereby a needle-sphere electrode configuration with a gap distance of 50 mm was chosen in this study. Al2O3 improves the PDIVs of RBDPO, CO and MO whereby the highest improvements of PDIVs are 34%, 39.3% and 27%. The PD amplitude and repetition rate of RBDPO improve by 38% and 81% while for CO, it can increase up to 65% and 80% respectively. The improvement of PD amplitude and repetition rate for MO are 18% and 95%, regardless with and without SDS. Without SDS, the presence of Al2O3 could cause 26%, 75% and 65% reductions of the average emission of light signals for RBDPOA, RBDPOB and CO with the improvement of PD characteristics but both events do not correlate at the same volume concentration of Al2O3. On the other hand, the average emission of light signal levels of the oils increases with the introduction of SDS. The emission of light signal in MO does not correlate with the PD characteristics improvement either with or without SDS.

This work examines the failure rate of the transformer population through the application of the Markov Model (MM) and Health Index (HI). Overall, the condition parameters data extracted from 3,192 oil samples were analysed in this study. The samples were from 370 transformers with the age range between 1 and 25 years. First, both HIs and failure rates of transformers were determined based on the condition parameters data of the oil samples known as Oil Quality Analysis (OQA), Dissolved Gas Analysis (DGA), Furanic Compounds Analysis (FCA) and age. A two-parameter exponential function model was applied to represent the relationship between the HI and failure rate. Once the failure rate state was obtained, the non-linear optimisation was used to determine the transition probability for each age band. Next, the future failure rate of the transformer population was computed through the MM prediction model. The goodness-of-fit test and Mean Absolute Percentage Error (MAPE) were utilised to determine the performance of the predicted failure rate. The current study reveals that the future state of the transformer population and failure rate could be predicted through MM based on updated transition probabilities. It is observed that the MAPE between predicted and computed failure rates is 7.3%.

This paper presents a statistical study on the AC Breakdown Voltage (BDV) of Refined, Bleached and Deodorized Palm Oil (RBDPO) olein under the influence of moisture. Different moisture contents of the RBPDPO were prepared by drying the RBDPO in the oven at different time intervals. The AC BDV test of RBDPO was performed whereby the distance between 2 electrodes was set to 1 mm. The statistical analyses of AC BDV data for RBDPO were carried out based on normal, lognormal and Weibull distributions. It was shown that as the moisture content increased, the AC BDV of RDBPO decreased exponentially. Statistical analyses revealed that the AC BDV data with different moisture contents had platykurtic distributions. Moisture could influence the skewness of the distribution whereby the tail shifted from right to left as the content increased. At different moisture contents of RBDPO, most of the AC BDV data of RBDPO could be represented by Weibull distribution.

This paper presents a statistical study on the AC Breakdown Voltage (BDV) of Refined, Bleached and Deodorized Palm Oil (RBDPO) olein under the influence of moisture. Different moisture contents of the RBPDPO were prepared by drying the RBDPO in the oven at different time intervals. The AC BDV test of RBDPO was performed whereby the distance between 2 electrodes was set to 1 mm. The statistical analyses of AC BDV data for RBDPO were carried out based on normal, lognormal and Weibull distributions. It was shown that as the moisture content increased, the AC BDV of RDBPO decreased exponentially. Statistical analyses revealed that the AC BDV data with different moisture contents had platykurtic distributions. Moisture could influence the skewness of the distribution whereby the tail shifted from right to left as the content increased. At different moisture contents of RBDPO, most of the AC BDV data of RBDPO could be represented by Weibull distribution.

Sustainable materials, such as vegetable oils, have become an effective alternative for liquid dielectrics in power transformers. However, currently available vegetable oils for transformer application are extracted from edible products with a negative impact on food supply. So, it is proposed in this study to develop cottonseed oil (CSO) as an electrical insulating material and cooling medium in transformers. This development is performed in two stages. The first stage is to treat CSO with tertiary butylhydroquinone (TBHQ) antioxidants in order to enhance its oxidation stability. The second and most important stage is to use the promising graphene oxide (GO) nanosheets to enhance the dielectric and thermal properties of such oil through synthesizing GO-based CSO nanofluids. Sodium dodecyl sulfate (SDS) surfactant was used as surfactant for GO nanosheets. The nanofluid synthesis process followed the two-step method. Proper characterization of GO nanosheets and prepared nanofluids was performed using various techniques to validate the structure of GO nanosheets and their stability into the prepared nanofluids. The considered weight percentages of GO nanosheets into CSO are 0.01, 0.02, 0.03 and 0.05. Dielectric and thermal properties were comprehensively evaluated. Through these evaluations, the proper weight percentage of GO nanosheets was adopted and the corresponding physical mechanisms were discussed.

This paper proposes an alternative approach to extract transformer’s winding parameters of resistance (R), inductance (L), capacitance (C) and conductance (G) based on Finite Element Method (FEM). The capacitance and conductance were computed based on Fast Multiple Method (FMM) and Method of Moment (MoM) through quasi-electrostatics approach. The AC resistances and inductances were computed based on MoM through quasi-magnetostatics approach. Maxwell's equations were used to compute the DC resistances and inductances. Based on the FEM computed parameters, the frequency response of the winding was obtained through the Bode plot function. The simulated frequency response by FEM model was compared with the simulated frequency response based on the Multi-conductor Transmission Line (MTL) model and the measured frequency response of a 33/11 kV, 30 MVA transformer. The statistical indices such as Root Mean Square Error (RMSE) and Absolute Sum of Logarithmic Error (ASLE) were used to analyze the performance of the proposed FEM model. It is found that the simulated frequency response by FEM model is quite close to measured frequency response at low and mid frequency regions as compared to simulated frequency response by MTL model based on RMSE and ASLE analysis.

In this paper, we propose enhanced adaptive step size Perturb and Observe (P&O) maximum power point tracking (MPPT) with properly organized comparison sequences which lead to achieving the actual maximum power point (MPP) effectively in the presence of partial shading conditions, taking into account the optimization of all aspects of high-performance MPPT to be novel, simpler, fast, and accurate, with the best efficiency reaching up to almost 100%. In this study, the proposed algorithm, along with a boost converter, was designed and simulated in MATLAB/Simulink to validate the performance of the suggested technique. Four different levels of partial shading conditions were considered for system examination: weak, moderate, and two different levels of strong shading. Each case was applied separately first and then combined in a sequence arrangement to provide robust and comprehensive testing which can provide a guaranteed assessment of the proposed algorithm. The performance of the suggested technique is discussed and compared with that of conventional P&O and conventional incremental conductance (IC) MPPT techniques. The failure of the conventional techniques to work efficiently in the presence of partial shading conditions was observed from the simulation results. Meanwhile, the success of the proposed technique and its high performance were clearly confirmed under partial shading conditions with no increase in complexity or convergence time.

The convenient design of a maximum power point tracking (MPPT) controller is key to the success of photovoltaic (PV) system performance in order to maximize the extracted power, which is affected significantly by weather fluctuations, particularly partial shading condition (PSC). This paper proposes a novel hybrid MPPT approach based on a modified Perturb and Observe (P&O) assisted by the Extremum Seeking Control (ESC) strategy, combining the benefits of these simple algorithms and, meanwhile, eliminating their drawbacks. The proposed algorithm is able to track the maximum possible power under any level of weather fluctuation, with comprehensive enhancement on all aspects of high performance, boosting the PV array efficiency to 100%, reducing the convergence time to less than 100 ms, completely eradicating the oscillations around the achieved power, and maintaining the simplicity levels of both involved strategies. More importantly, this algorithm is applicable for any PV array configuration, which enhances the robustness and novelty of the algorithm. The performance is verified using MATLAB/Simulink. A boost converter is used for controlling DC to DC (direct current to direct current) power. The proposed algorithm’s performance is compared with the conventional P&O and incremental conductance (IC) algorithms under four different cases of weather conditions. The shortcomings of these algorithms are illustrated and the analysis confirms the effectiveness of the proposed algorithm accordingly.

This study presents an investigation on the effect of shield placement for mitigation of transient voltage in a 33/11 kV, 30 MVA transformer due to Standard Switching Impulse (SSI) and Oscillating Switching Impulse (OSI) surges. Generally, the winding and insulation in transformers could experience severe voltage stress due to the external impulses i.e. switching events. Hence, it is important to examine the voltage stress and identify the mitigation action i.e. shield placements in order to reduce the adverse effect to the transformer windings. First, the resistances, inductances, and capacitances (RLC) were calculated for disc type transformer in order to develop the winding RLC equivalent circuit. The SSI and OSI transient voltage waveforms were applied to the High Voltage (HV) winding whereby the transient voltages were simulated for each disc. The resulting voltage stresses were mitigated through different configurations of electrostatic shield placements. The resonant oscillations generated due to switching surges were analysed through initial voltage distribution. The analyses on the transient voltages of the transformer winding and standard error of the slope (SEb) reveal that the location of shield placement has a significant effect on the resonant switching voltages. The increment of the shield number in the windings does not guarantee optimize mitigation of the resonant switching transient voltages. It is found that the voltage stress along the windings is linear once a floating shield is placed between the HV and Low Voltage (LV) windings of the disc-type transformer under the SSI and OSI waveforms. These findings could assist the manufacturers with appropriate technical basis for mitigation of the transformer winding against the external transient switching overvoltage surges.

The authors of this study designed and optimized a charging landing pad system that mitigates the landing accuracy issues of unmanned aerial vehicles (UAVs). The study looks at the charging process, energy conversion during periodic landing on a unique platform, and an onboard and on-ground scheme design procedure. The circuit is fixed on the UAV platform and comprises six integrated bridge rectifier diodes to alter the four connection pin terminals’ charge polarity. The inclusion of a current indicator shows the flow of charge during successful docking. The charging platform consists of square conductive copper plates of specific dimensions that provide positive and negative polarity in a chess form to ensure the contact of various polarities. This design considers two power supply options: a solar panel and a standard mains supply. The contact point coordinate probability when landing is the crucial aspect of this design. A first version of the proposed system was implemented to measure its effectiveness for commercial drones. This system provides an automated recharge station with reliable performance. Numerical experiments showed that the system’s energy conversion remains efficient regardless of drone orientation over the platform or the environment’s nature.

This paper presents the investigation on the breakdown characteristics and pre-breakdown streamer propagation of Palm Oil (PO) impregnated aged pressboard under positive lightning impulse voltages. The experimental work was carried out under a non-uniform field with needle-plane electrodes configuration. The streamer stopping length and breakdown voltage of 2 types of refined, bleached, and deodorized palm oil were examined in the presence of new and aged pressboards. The pressboard was placed in parallel to the needle-plane electrode at a gap distance of 50 mm. The lightning breakdown voltage was applied to the samples based on 1 shot per step rising voltage method under positive polarity as per IEC 60897. The presence of impregnated pressboard in both PO slightly increases the 50% positive lightning breakdown voltages. PO impregnated pressboards have lower 50% positive lightning breakdown voltages than MO. After subjected to ageing, the positive lightning breakdown voltages for PO and MO impregnated pressboards decrease. In the presence of aged pressboard, the streamers in PO generally propagate further than MO at the same voltage level.

An efficient charging station is a necessity for Unmanned Aerial Vehicle (UAV) systems. However, if that implementation adds more complexity and onboard weight, then that exercise becomes a burden rather than a benefit since UAV's engineers aim to improve efficiency by reducing the energy consumed by the software and hardware of the complete aeronautical system. This article recommends a fully automatic contact charging station for UAVs, which can charge UAVs and thus resolve flight endurance restrictions of the UAV. The ground station consists of square copper plates that are positively and negatively polarized successively in a chessboard with particular sizes to guarantee electric contact at the landing. The design methodology used with the loading station takes into account the differences in UAV orientation once the platform has landed. In addition, this innovation uses independent charging after touchdown. Thus, this technology relaxes common flight times and help to enhance general mission times. This paper presents a unique charging platform in a “chessboard” configuration, which is devised as an interconnecting interface to facilitate the charging process and overcome inaccuracies with the landing. The solution devised in this research requires few components and presents two power source options (solar & mains power). Additionally, this work presents, to the best of our knowledge, a uniquely innovative recharging landing platform, which incidentally requires no additional software or changes to the UAV’s onboard software settings.

Vegetable oils have emerged as insulating fluids in transformer applications and as a prominent and effective alternative for traditional dielectric fluids. However, most of vegetable oils are edible causing their application on a large scale to be limited. In the present work, a novel non-edible vegetable oil is developed as an insulating fluid. The developed oil is oxidation-inhibited cottonseed oil (CSO) based nanofluids. Tertiary butylhydroquinone was used as antioxidant. The concept of nanofluids was used to overcome the limited dielectric and thermal properties of cottonseed oil. Hexagonal Boron Nitride (h-BN) nanoparticles at low weight fractions (0.01 - 0.1 wt%) were proposed as nanofillers to achieve adequate dielectric strength and improved thermal conductivity. Stability of prepared CSO based nanofluids was analyzed using Ultraviolet-visible (UV-Vis) spectroscopy. Then, the prepared nanofluids were tested for dielectric and thermal properties under a temperature range between 45 °C and 90 °C. The dielectric properties include breakdown strengths under AC and lightning impulse voltages, dielectric constant, dissipation factor, and resistivity, while thermal properties include thermal conductivity and thermogram analysis. The dielectric and thermal properties were significantly improved in CSO based nanofluids. The creation of electric double layer at nanoparticle/oil interface and the lattice vibration of nanoparticles were used to clarify the obtained results. The proposed CSO based h-BN nanofluids open up a great opportunity in both natural ester insulating fluid applications and thermal energy management systems.

To increase the adhesion of thick film on a substrate, boron oxide (B2O3) was added to titanium dioxide (TiO2), and the change in the morphology, crystallinity and band gap of TiO2 thick film was investigated. TiO2 and TiO2-B2O3 pastes were prepared and deposited on the microscopic glass using screen-printing technique and then annealed under air at different temperatures of 400°C, 450°C and 500°C for 30 min. The morphology, elemental composition, structure and absorption of the thick films were characterized using FESEM, EDX, XRD and UV–visible spectroscopy. The TiO2 and TiO2-B2O3 thick films were fabricated as gas sensors and exposed to 100–1000 ppm of hydrogen at an operating temperature of 300°C. The results revealed that the addition of B2O3 increased the crystallinity of anatase phases and rutile phases in TiO2 as annealing temperature increased. The TiO2-B2O3(T500) gas sensor exhibited the highest response to various concentrations of hydrogen (100–1000 ppm) at an operating temperature of 300°C.

The paper presents the description for diagnostic methods of induction motor's stator windings fault. The presented methods use Frequency Response Analysis (FRA) technique for detection of Winding Faults in Induction Motor . This method is previously reliable method for faults diagnosis and detection in many parts of transformers including transformer windings. In this paper, this method was used for motor windings faults detection. This paper presents the FRA response interpretation on internal short circuit (SC) fault at stator winding on three cases studies of different three-phase induction motors (TPIM), were analysed according to two status: healthy induction motor at normal winding status and same motor with windings shorted of main windings. A conclusion of this paper provides the interpretation of and validation the FRA response due to internal SC fault case by using NCEPRI algorithm, which is considered as one of certified statistical indicators. The proposed method in this paper had a useful result for detect and diagnosis of stator windings faults of TPIM. The applications of developed method can be used to detece the other machines types faults.

In this paper, the effect of different types of surfactants on the lightning breakdown voltages of palm oil (PO) and coconut oil (CO) based aluminium oxide (Al2O3) nanofluids is investigated. Three different types of surfactants were used in this study known as cationic (cetyl trimethyl ammonium bromide (CTAB)), anionic (sodium dodecyl sulfate (SDS)) and non-ionic (oleic acid (OA)). The volume percentage concentrations of Al2O3 dispersed into PO and CO were varied from 0.001% to 0.05%. The ratio of surfactant to the nanoparticles was set to 50% from the volume concentration of nanoparticles which equivalent to 1:2. In total, two types of refined, bleached and deodorized palm oil (RBDPO) and one type of CO were examined for lightning breakdown voltage. The test was carried out based on needle-sphere electrodes configuration with 25 mm gap distance. The presence of Al2O3 improves both positive and negative lightning breakdown voltages of RBDPO and CO. Under the positive and negative polarities, the CTAB does provide further improvements on the lightning breakdown voltages of RBDPOA (1st type of samples) and CO at most of the volume of concentration of Al2O3. SDS and OA could also further improve the lightning breakdown voltage of CO at certain volume concentration of Al2O3. On the other hand, the lightning breakdown voltage of RBDPOB based Al2O3 nanofluid (2nd type of samples) does not further improve with the introduction of surfactants. At most of the volume concentration of Al2O3, the introduction of CTAB further increases the times to breakdown and decrease the average streamer velocities of RBDPOA under both polarities. The same finding is observed for CO under positive polarity with CTAB and SDS as well as under negative polarity in the presence of all surfactants. The streamer velocities and times to breakdown patterns of RBDPOB based Al2O3 nanofluid are inconsistent in the presence of all surfactants. It is found that RBDPO and CO based Al2O3 nanofluids have s