An active islanding detection scheme for inverter-based DG with frequency dependent ZIP–Exponential static load model

In this paper an analytical design method is proposed for constant voltage controlled inverter based DG with frequency dependent ZIP–Exponential static load model to obtain proper inverter output control and successful islanding detection. The proposed technique is aimed to eliminate the dependency of DG operation point on anti-islanding performance which is unavoidable in case of traditional control strategy. The generalized formulae are derived for calculating the upper and lower limits of the voltage gain, and it is recommended to select the voltage gain within the designed range for effective islanding detection. The proposed approach is tested in MATLAB/Simulink environment and result shows that the proposed scheme is found to be highly effective in islanding detection considering complex network configurations with single and multiple DG systems. The proposed control scheme is able to detect islanding within 10 ms (half cycle) from the event inception, showing the fastness of the developed technique. It is also observed that the percentage of voltage and current THD of the proposed scheme is within permissible limits, indicate that the power quality of the inverter is not degraded by the proposed control strategy, and thus overcomes the drawback of existing active anti-islanding techniques.     

Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network

This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies.     

The structure of turbulent free diffusion flames

The present work is an experimental and theoretical study of the structure of a turbulent free diffusion flame issued from a vertical burner. The main parameters considered are the relative angle between fuel and air jets, airfuel ratio, burner geometry, and fuel and air momenta. Both temperature distributions and concentrations of CO₂ and O₂ were measured. A theory was developed to calculated the flame height, by considering the relative angle between fuel and air jets, taking into account the effect of buoyancy force on the flame height near the forced convention region. This was acheived by combining the law of conservation of mass and the equation for momentum balance with the equation of state of gases. The calculation procedure requires a knowledge of both the density profiles, obtained from the temperature distribution, and the velocity distribution obtained from the law of entrainment. The results enabled the determination of chemical, thermal, visible, and stoichiometric flame heights.     

Effect of yttrium on the physical,elastic, and structural properties of neodymium-doped lead borotellurite glass

In this study, a series of glass systems with a composition of (49???x)H₃BO₃–35TeO₂–15PbO–1.0Nd₂O₃–xY₂O₃ (x?=?0.0, 0.5, 1.0, 1.5, 2.0, and 2.5 mol%) was prepared via melt-quench technique. The effect of Y₂O₃ content on the density, molar volume, oxygen packing density, elastic, and structural properties were investigated. The density and molar volume were found to vary concerning Y₂O₃ content. Ultrasonic non-destructive testing was employed at room temperature for measuring the elastic properties of the prepared glass samples. The density data, ultrasonic velocities, and measured elastic moduli were found to be composition dependent with Y₂O₃ content. The Y₂O₃ modifier was expected to change the physical properties of neodymium-doped lead borotellurite glasses. The structure analyzed using X-ray diffraction was confirmed the amorphous nature of the prepared glasses. Fourier Transform Infrared Spectroscopy has been carried out and reveals that the inclusion of Y₂O₃ into the glass system tends to increase the number of bridging oxygen atoms. All element study of the glass sample was proved by energy dispersive X-ray analysis.

     

Photocatalytic dye degradation using lithium borate-bismuth tungstate glass-ceramics

The disposal of wastewater contaminated with dyes is a prevalent global concern that necessitates the implementation of diverse remediation strategies. There are several methods available for the treatment of wastewater, one of which is photocatalytic treatment. The primary objective of this study is to assess the efficacy of a lithium borate-bismuth tungstate glass-ceramic material (0.7Li₂B₄O₇ - 0.3Bi₂WO₆) in the degradation of methylene blue dye through photocatalysis under visible light irradiation conditions. The glass under consideration was prepared using the conventional melt-quench technique. The characterization of the glass was conducted using X-ray diffraction technique and Raman spectroscopy. Additionally, the glass obtained was subjected to various heat treatments in order to achieve crystallization, as assisted by differential scanning calorimetry as reported. The elemental analysis and morphology of the glass ceramics that were prepared were examined using X-ray photoemission spectroscopy (XPS) and field emission scanning electron microscopy (FE-SEM). The glass-ceramic sample exhibited a dye degradation efficiency of 73% within a time span of 240 min. The evaluation of the active species involved in degradation is also conducted through the utilisation of a scavenger test. The experiments were conducted multiple times to verify the effectiveness of the prepared glass-ceramic material for water purification purposes.     

Impact of TeO2–B2O3 manipulation on physical,structural, optical and radiation shielding properties of Ho/Yb codoped mixed glass former borotellurite glass

In this work, (75-x)B₂O₃-xTeO₂-11Bi₂O₃–10Li₂O-1Ho₂O₃-3Yb₂O₃ (x = 10–60 mol%) mixed glass former (MGF) glasses were prepared by using the melt-quenching method to investigate the effect of mixed glass former between B₂O₃ and TeO₂ on the structural, optical and radiation shielding properties of glass. The amorphous nature of the glass samples was confirmed through XRD measurement. Optical ultraviolet–visible light (UV–Vis) spectroscopy revealed that the direct and indirect optical band gap (E_opt) decreased as TeO₂ content increased except for the anomaly at x = 30 mol% due to the interchanging dominance of bridging oxygen (BO) and non-bridging oxygen (NBO) in the glass network. Both direct and indirect refractive indices, n posted an increment except for x = 30 mol% due to polarizability influence of BO and NBO. Urbach energy, E_u declined thus indicating lesser disorder and less defects on the glass structure. The radiation shielding properties of the glass samples were determined for 15 keV–15 MeV photon energy range by using Phy-X/PSD software. Atomic number-dependent parameters such as mass attenuation coefficient (MAC) and effective atomic number (Z_eff) demonstrated an enhanced performances caused by higher Z of Te over B. Meanwhile, density-dependent parameters such as linear attenuation coefficient (LAC), mean-free path (MFP), half-value layer (HVL) and tenth-value layer (TVL) all exhibited an improvement over TeO₂ concentration due to higher density data obtained.     

Metallurgical and mechanical properties of hydrogen charged carbide-free bainitic weld metals

Hydrogen embrittlement is a major concern during the welding of high-strength steels. The susceptibility of the welds to hydrogen embrittlement increases with increase in weld strength. The ever-increasing demand to increase the strength of steels necessitates the development of novel welding procedures and fillers to produce welds of high strength and with resistance to hydrogen embrittlement. In this current work, the susceptibility of carbide-free bainitic weld metals to hydrogen embrittlement is studied with varying volume fractions of constituent phases. Using three different weld metal compositions, six different weld metal microstructures of carbide-free bainite were generated. The hydrogen saturation behaviour of the various weld metals was studied by cathodic electrolytic charging and subsequent diffusible hydrogen measurements by the hot extraction method. Tensile tests were conducted on various weld metals with and without hydrogen charging to evaluate their susceptibility to hydrogen embrittlement. The results show that the carbide-free bainite weld metals are highly resistant to hydrogen embrittlement despite their very high strength.     

Machine learning-assisted tri-objective optimization inspired by grey wolf behavior of an enhanced SOFC-based system for power and freshwater production

In recent years paying attention to the generation of clean and sustainable power and fresh water along with having lower cost and emission has increased. In the present research, a novel scheme for generating efficient power using the flame-assisted fuel cell is introduced, which has higher efficiency than ordinary fuel cells due to increased hydrogen concentration in the flame-rich combustion chamber. The waste heat is then introduced to a multi-effect desalination unit through a heat recovery steam generation unit to generate fresh, drinkable water. In order to make the system have higher efficiency, lower cost, and lower emission, the machine learning techniques are applied to optimize the operational conditions of the system, and find out the best solution point based on the cutting-edge algorithm of the grey wolf. Also, a complete techno-economic analysis and a parametric study are necessary to figure out the best solution point based on the TOPSIS method. The results indicate that the maximum value of exergy efficiency and drinkable water generation is 67.5% and 3.4 kg/s, respectively, while the minimum energy cost is 90.1 $/MWh. Moreover, results show that for the second optimization scenario considering the drinkable water production, energy cost, and pollution index as the objectives, the net produced power, energy efficiency, exergy efficiency, and water mass flowrate improve by around 1059 kW, 5.1%, 1.3%, and 1.6 kg/s than the design condition. Besides, energy cost and emission index are reduced by about 22 $/MWh and 51.9 kg/MWh, respectively.     

Performance improvement of PEM fuel cell power system using fuzzy logic controller-based MPPT technique to extract the maximum power under various conditions

Power generation of a fuel cell (FC) is mostly dependent upon operational variables such as cell temperature and membrane water content. There is an individual maximum power point (MPP) on the P-I curve of the FC. The location of the MPP varies with respect to the MPP position. Thus, an MPP tracking (MPPT) system should exist to guarantee that the FC works at the MPP in order to maximize the functionality. Due to their straightforward structure, prevalent MPPT methods had strong functionality. However, their primary limitations include fluctuations around the MPP and inefficiency under abrupt variations of operating conditions. The primary objective of this paper is to maintain the PEMFCs operation at an efficient power point. To this purpose, the efficiency of PEM-FC is tested and enhanced using a variety of MPPT-based smart controller techniques. To determine the appropriate MPPT controller parameters, the modified fluid search optimization (MFSO) approach and fuzzy logic controller (FLC) are employed. Furthermore, the MFSO method is deployed to adjust the membership functions (MFs) of the FLC. The MFSO is an excellent approach for coping with the stochastic behavior of the PEM-FC system when the temperature and water content of the membrane change. In terms of improved dynamic behavior, better convergence rate, reduced oscillations, and better tracking of the MPP, the results obtained by employing the suggested strategy demonstrate the superior functionality of the system compared to case using other methods. Moreover, the power generated by the PEMFC system is less than the nominal capacity for the temperature's rated capacity. Therefore, the deficit in power would be covered by transacting power with the grid.