High-impedance faults (HIFs) in electrical power distribution systems produce a very random, non-linear and low-magnitude fault current. The conventional overcurrent (OC) relaying-based distribution system protection schemes find difficulty in detecting such low-current HIFs. In this study, a simple two criteria-based protection scheme is proposed for detection and isolation of HIFs in multi-feeder radial distribution systems. It utilises one-cycle sum of superimposed components of residual voltage for HIF detection and the maximum value of one-cycle sum of superimposed components of negative-sequence current for faulted feeder identification. The performance of the proposed scheme is evaluated for a wide variety of possible test cases by generating data through power systems computer-aided design/electro-magnetic transient design and control software. Results clearly show that the proposed scheme can assist conventional OC relay for detection and isolation of HIFs in distribution systems with any grounding connections in a more reliable and faster way.

Most of the HV power equipment with gas–solid insulation suffers a lot from the surface charge accumulation due to corona discharge. The existence of surface charge distorts the local electric field and leads to surface flashover faults in extreme situations. As a result, it is important to figure out the mechanism of surface charge accumulation process. In this study, a simulation model combining both the plasma hydrodynamics and charge trapping–detrapping process was built. The simulation results have a good agreement with the experimental data, the main summary is as follows: in the surface charge accumulation process, the corona discharge intensity increases first and then decreases with time. The curves of the surface potential distributions have different shapes at different times, the central value goes up rapidly with time in the beginning and finally reaches saturation. Surface charges exist in the skin layer of epoxy insulator, some of them may be captured by traps while transporting away under built-in electric field.

For the ultra high voltage (UHV)-DC and UHV-AC transmission lines, their contamination characteristics are different. Thus, researching the contamination polluted degree of UHV-AC and UHV-DC lines by geoaccumulation index and enrichment factor method is an ingenious method. This study analyses and compares the chemical composition of contamination on parallel energised UHV-DC (800 kV) and UHV-AC (1000 kV) overhead transmission lines. The results indicate that the major cations of insulator contamination are Ca²⁺ , and NH₄ ⁺, and the major anions of insulator contamination are SO₄ ²⁻ and NO₃ ⁻ both on UHV-DC and UHV-AC lines. For the UHV-DC line, the concentrations of the same cations on the insulator bottom surface are higher than that of on the top surface. However, on the UHV-AC line, the same cation concentrations on the bottom surface close to the one on the top surface. The metallic elements of Ca²⁺ and Zn²⁺ are in seriously polluted degree. Also, the polluted degree of contamination on UHV-DC insulator is more serious than UHV-AC insulator. This study considers that field charging plays an important role in accumulating contamination.

A huge consumption of energy in the data centres has become a motivation for improvement in computing capability and energy conservation. The dynamic speed scaling and job scheduling are efficient methods to improve the energy efficiency of processors. In this study, an online non-clairvoyant scheduling algorithm arrival time-algorithm (At-ALG) is proposed with an objective to scale the speed of processors and schedule the jobs in a multiprocessor system to minimise the total magnitude-based/weighted flow time plus energy consumed. The traditional power function is adopted, where is a constant. At-ALG is analysed, against an offline adversary, using the potential function analysis. The magnitude/weight/priority of jobs in At-ALG are generated using their processed time (waiting time plus executed time) and speed of any processor depends on the number of active jobs plus sum of processed time of active jobs. At-ALG is -competitive with no resource augmentation.

Automotive instrumentation is an important process to guarantee quality and safety for the drivers and passengers of vehicles. At the same time, it is a time-consuming task, because engineers must setup the system, which includes the passing of cables through the vehicle and the configuration of equipments. A wireless automotive instrumentation system can certainly help on reducing the instrumentation time and its cost. However, it may incur in errors due to the wireless communication between sensors and the base station. In this study, the authors propose a low-cost wireless monitoring system for automotive instrumentation. They compare the proposed system with two commercial instrumentation equipments in terms of features, cost, and precision for monitoring the engine speed. The results indicate that the proposed wireless monitoring system delivers similar performance, but at a lower cost (up to 1114 times cheaper).

The propagation of evolving mechanical faults in rotating electric machinery and their corresponding signatures in the machines’ electrical signals is still not elucidated thoroughly. This deficiency implies serious obstructions in the development of using those signals as a complete and reliable condition monitoring technology. This study presents a new method to translate single point outer and inner race bearing faults into specific movements of the rotor with respect to the stator. The method contains the excitation of a simplified mass-spring-damper bearing model by analytical constructed fault-related force functions. Furthermore, a novel approach in order to emulate those obtained specific fault-related rotor movements with the use an experimental test setup is described, dimensioned, simulated and validated. Replacing the drive-end bearing of the induction machine under test by an active magnetic bearing creates the opportunity to continuously manipulate the rotor's position. The estimated single point bearing fault-related rotor movements serve as set-point for the magnetic bearing, resulting in the achievement of a single point bearing fault emulator with high relevance and reproducibility. This study includes experimental results of an emulated single point outer race bearing fault on an 11 kW induction machine.

This study presents a single-stage solar energy conversion system tied to a three-phase grid using a multiple second-order generalised integrator frequency locked loop (MSOGI-FLL)-based control algorithm to improve power quality of the distribution system with DSTATCOM (Distribution Static Compensator) capabilities. The estimated perturb and observe algorithm is used for maximum power point tracking to obtain maximum power from a solar photovoltaic (PV) array. The MSOGI-based control algorithm is used for load balancing, harmonics elimination, and power factor correction and delivering active power to the grid. The MSOGI-FLL has advantages of adaptive nature with frequency variation and better harmonics filtering capabilities when compared with conventional algorithms, which is demonstrated with frequency domain analysis. The comparative performance of amplitude extraction capabilities with conventional algorithms is also demonstrated. This system configuration is simulated in MATLAB®/Simulink. The proposed control algorithm is verified on a developed prototype for various conditions like variable solar insolation level, load balancing, reactive power compensation, PV to DSTATCOM mode, and DSTATCOM to PV mode. The total harmonic distortions of grid voltages and currents are found well within the limits of an IEEE-519 standard.

To achieve an effective feature extraction for power transformer vibration signals, the authors propose a method for signal feature extraction based on empirical wavelet transform (EWT) and multiscale entropy (MSE). First, transformer vibration signals are decomposed into several empirical wavelet functions (EWFs) with the method of EWT. Then, the frequency characteristics of signals are demonstrated in the time-frequency representation by applying a Hilbert transform to each EWF component. Finally, in order to quantify the extracted features, the MSEs of components being highly correlated with the original signals are calculated to construct the eigenvectors of transformer vibration signals. Several experiments are presented showing the effectiveness of this method compared with the classic empirical mode decomposition method.

Time–frequency representation (TFR) is useful for non-stationary signal analysis as it provides information about the time-varying frequency components. This study proposes a novel TFR based on the improved eigenvalue decomposition of Hankel matrix and Hilbert transform (IEVDHM–HT). In the proposed method, first the authors decompose non-stationary signals using the IEVDHM with suitably defined criterion for eigenvalue selection, requirement of number of iterations, and new component merging criteria. Furthermore, the HT is applied on extracted components in order to obtain the TFR of non-stationary signals. The performance of proposed TFR has been evaluated on synthetic signals in clean and white noise environment with different signal-to-noise ratios. The proposed method gives good performance in terms of Rényi entropy measure in comparison with other existing methods. Application of the proposed TFR is also shown for the classification of epileptic seizure electroencephalogram (EEG) signals. The least-square support vector machine (LS-SVM) with radial basis function kernel is used for classification of seizure and seizure-free EEG signals obtained from the publicly available database by the University of Bonn, Germany. The proposed method has achieved classification accuracy 100% for the studied EEG database.

Gas-insulated switchgear (GIS) spacers are made of epoxy resin. However, the surface charge accumulation has been a great concern to the safe operation of GIS, which causes the frequent flashover faults on spacers. In this study, micro-silicon carbide (SiC) particles with non-linear conductivity were added into epoxy matrix and the filler content varied from 0 to 14 vol%. Then, the bulk conductivity and surface potential decay (SPD) tests were conducted. The obtained results showed that the epoxy/SiC composites have obvious non-linear conductivities and the non-linear-conductivity threshold decreases with the increasing filler content. The addition of SiC can effectively resist the rise of surface potential and enhance the surface charge dissipation process. From the trap energy distributions, it can be inferred that the deep traps of ∼0.9 eV should be the intrinsic traps of epoxy and the shallow traps of ∼0.8 eV are considered to be introduced by SiC. Furthermore, the simulation results confirmed that the sharp increase of carrier mobility in non-linear region significantly reduces the remaining time and possibility of a de-trapped charge being recaptured by traps before reaching the grounded electrode. Therefore, the high conductivity in non-linear region contributes a lot to the increase of SPD rate.

In this study, a novel ultra-high frequency (UHF) sensor using an inner grading electrode inside an insulting spacer is employed to detect gas-insulated switchgear (GIS) partial discharge (PD). The simulation of the waveguide modes of the 252 kV GIS and the frequency response characteristics of this UHF sensor are performed by using the finite difference time domain (FDTD) method. Three kinds of typical defects are employed to investigate the PD detection characteristics of this UHF sensor. It is shown that the resonance frequencies of this sensor are extremely abundant below 3 GHz, and the major resonance frequencies around 0.5–1.2 and 2.2–3 GHz. The phase-resolved PD (PRPD) images accumulated by using this UHF sensor present the typical PRPD images of defects. The main frequency spectrum of the metal protrusion on a high-voltage conductor and floating potential defects are distributed below 1.5 GHz, which is consistent with waveguide mode simulation. A resonance frequency of a grading electrode UHF sensor appears at about 115 MHz, which is close to the simulation value of a resonance frequency at 140 MHz. The PD detection sensitivity of this sensor is much higher than that of an external sensor; however, it is a little lower than that of an internal sensor.

Conducting polymer composites are attractive alternatives for applications such as electromagnetic shielding in which metals are conventionally used. They have unique advantages like light weight, ease of processing and good strength to weight ratio. This makes them economically viable especially in industries like avionics where weight is an important criterion. However, a major challenge in using conducting polymer composites in many of the applications is its limited conductivity. Even though many models exist to describe the conductivity of the composites at the macro level taking into account the interparticle conductivity, very few studies are conducted to understand the conductivity of the composites directly from basic principles. In this study, Monte Carlo (MC) simulations are carried out to study the conductivity in such composites. The results obtained using the MC model showed good agreement with the Mamunya model and the experimental measurements. The effect of various parameters like filler diameter and filler conductivity on the final composite conductivity is studied for spherical and fibrous carbon fillers in silicone rubber. The method can be easily adopted for any other filler–polymer combination and can also be used as a predictive tool for designing simple composites of required electrical properties.

In this study, a modern adaptive signal processing technique called variational mode decomposition (VMD) has been used for power quality (PQ) events detection. Numerous single, as well as multiple PQ events, are simulated according to IEEE std. 1159-2009 and laboratory experimental signals are collected and passed through the VMD algorithm. VMD decomposes the signal into different modes and from these modes, different features have been extracted. To reduce the dimension of the feature set Fischer linear discriminant analysis (FDA) has been used. As a new contribution to the literature, VMD aided FDA-based feature selection with reduced kernel extreme learning machine technique has been used for detection and classification of multiple PQ disturbances. The performance of the proposed combined technique shows higher classification accuracy while classifying multiple PQ disturbances and the results are comparable with many existing methods.

A simple, low cost liquid level measurement technique for all types of liquids has been proposed in this study. A force resistive sensor has been used to sense the height of liquid level in a storage tank. The force resistive sensor gives the information of the height of liquid level in terms of resistance. The resistance of the sensor corresponding to the height of liquid level is converted into a voltage signal with the help of a resistance to voltage converter. The resistance-to-voltage converter output has been passed through signal conditioning circuit and voltage-to-current converter to transmit the signal to a remote location like a control room. The theoretical equations explaining the operation of the force resistive sensor for the liquid level have been derived. The whole unit has been designed, fabricated and its function has been studied experimentally. The experimental results are reported in this study. A very good linear characteristic of the proposed transmitter has been observed with very good repeatability and with a very small uncertainty of measurement.

Standard capacitors form an important component of the measurement and instrumentation in the electrical laboratory. A high-voltage (HV) standard capacitor of 100 pF, 12 kV (rms) is designed using the charge simulation method (CSM). CSM is a semi-analytical method and it provides inherent advantage in designing a capacitor from the first principle. The capacitance is obtained from the magnitude of the simulating charges of the CSM-based model and the corresponding potential. The design details of HV standard capacitor are discussed along with the analysis of the potential and the electric stress distribution. The electric stress everywhere in the capacitor, which is designed, is assured to be <5 kV/cm, which was set as the limiting (maximum permissible) stress. The capacitance of the fabricated unit is measured in the HV laboratory. The CSM-based result of the capacitance of the designed HV capacitor agree well with the results of the laboratory experimental measurement. The inherent advantage of CSM in designing a capacitor is confirmed by comparing with the results of method of moments (MoM).

This study develops a robust Gaussian particle filter (RGPF) based on modifying the likelihood function by Huber's M-estimation theory. In the developed RGPF, the innovations are reweighted based on the Huber's cost function, resulting in a modified likelihood function which is then used to update the weights of the involved particles. In the normal case, the developed RGPF has a comparable performance in terms of accuracy with the original GPF and better filtering consistency. When there are outliers and contaminated distributions in the measurements, the RGPF can outperform the GPF in terms of both accuracy and consistency. The validity of the developed algorithm is demonstrated through numerical simulation studies.

Studying the effect of adding nanosized ZrO₂ to mineral transformer oil on the AC breakdown voltage is presented. The study is carried out considering different concentration levels of nanosized ZrO₂. These concentrations are 0, 0.001, 0.002, 0.003 and 0.006%w. The AC breakdown voltage of both nanofilled and base oil is measured according ASTM D1816 standard at room temperature. The evaluation is carried out based on AC breakdown voltage for the nanofilled and base oil considering average and Weibull statistical techniques. Both 50 and 10% breakdown voltage probabilities are obtained and analysed for all samples. Also, the effect of temperature (to take the effect of real operating conditions) on breakdown voltage of base and nanofilled oil is experimentally evaluated. The studied temperatures are 50, 80 and 130°C. The obtained results show that the performance of nanoparticles is significantly affected by increasing the temperature of nanofilled transformer oil. Finally, a proposed mechanism for the effect of temperature on the nanofluids breakdown strength is introduced.

As a physical layer of body area network, human body communication (HBC) has become a prospective candidate with advantages of less interference and intrinsic transmission for implanted devices. Currently, its bit error rate (BER) performance has not been thoroughly reported with high confidence because the traditional BER testing method in commonly used wireless radio and optical system communication, if directly applying in HB channel, is both time-consuming and problematic due to significant physiological limitations. In this study, a time-efficient approach using jitter characteristics is proposed to tackle this problem. To practically measure the BER in HBC channel, experiments based on human arms are carried out with 600 records of jitter data (5 subjects, 3 modulation schemes, 4 separation distances, and 10 transmit power levels). By using both normal probability plot and Kolmogorov–Smirnov test, the authors found that the HBC experimental jitter data mainly followed normal distribution. Additionally, the comparison between estimated BERs using their approach match well with those via the theoretical prediction based on additive white Gaussian noise channel. Finally, the proposed approach can be an effective measurement method not only for the BER of body channel, but also applicable in other similar low rate systems.