This paper has analyzed the defects of the traditional extended description function (EDF) based LLC small signal modeling method when driving light emitting diode (LED) load and proposed an accuracy improvement method. Detailed small signal model modeling methods have been deduced, and the accuracy of different modeling methods has been compared thoroughly. To suppress the second-order harmonic ripple in the direct current link-induced output current ripple, a quasi-resonant controller (QRC) is adopted to realize active ripple rejection (ARR). Considering the frequency of the second-order harmonic ripple changes with the grid voltage frequency, a single-phase software phase lock loop (SPLL) is adopted to extract the frequency of the second-order harmonic. By dynamically regulating the control parameter of the QRC according to the locked second-order frequency, output voltage ripple active rejection ability immune to grid voltage frequency deviation is obtained. Based on the deduced ac... [more]

The seventeen Sustainable Development Goals (SDGs) aim to address environmental, social, global, and economic challenges. The SDGs were a continuation of the Millennium Development Goals and assumed a common vision for the year 2030. Efforts to achieve the SDGs must be carried out in an integrated manner, respecting the three pillars of sustainable development, which are economic, social, and environmental. This review analyses the viability of Sustainable Development Goal 17 (SDG 17), which aims to build global partnerships for development. It makes specific reference to multi-stakeholder collaboration between all sectors of society. While the first sixteen SDGs are dedicated to concrete actions, SDG 17 Partnerships for Development coordinates and facilitates the implementation of the other goals. SDG 17 promotes the “right way” of collaboration between different actors through the formation of multi-stakeholder partnerships, which are essential to foster sustainable development. Alth... [more]

Wind turbine blades will suffer various surface damages due to their operating environment and high-speed rotation. Accurate identification in the early stage of damage formation is crucial. The damage detection of wind turbine blades is a primarily manual operation, which has problems such as high cost, low efficiency, intense subjectivity, and high risk. The rise of deep learning provides a new method for detecting wind turbine blade damage. However, in detecting wind turbine blade damage in general network models, there will be an insufficient fusion of multiscale small target features. This paper proposes a lightweight cascaded feature fusion neural network model based on YOLOX. Firstly, the lightweight area of the backbone feature extraction network concerning the RepVGG network structure is enhanced, improving the model’s inference speed. Second, a cascaded feature fusion module is designed to cascade and interactively fuse multilevel features to enhance the small target area fea... [more]

Submicron-structured films of thermoelectric materials, exhibiting an improved thermoelectric figure of merit, are reviewed, including methods of fabrication and characterization. The review emphasizes the beneficial role of the grain boundaries in polycrystalline films. The enhanced Seebeck coefficient of lead chalcogenide films is attributed to a potential relief that is built along the grain boundaries. It scatters charge carriers with low energy and does not affect carriers with higher energy. The model that accounts for the thermoelectric properties of the films is described and assessed experimentally. The application of a flexible thermoelectric device (module) based on the nanocrystalline film thermoelectric semiconductors as high sensitivity radiation detectors is suggested.

The Brazilian energy grid is considered as one of the cleanest in the world, because it is composed of more than 80% of renewable energy sources. This work aimed to apply the levelized costs (LCOH) and environmental cost accounting techniques to demonstrate the feasibility of producing hydrogen (H2) by alkaline electrolysis powered by the Brazilian energy grid. A project of hydrogen production, with a lifetime of 20 years, had been evaluated by economical and sensitivity analysis. The production capacity (8.89 to 46.67 kg H2/h), production volume (25 to 100%), hydrogen sale price (1 to 5 USD/kg H2) and the MAR rate were varied. Results showed that at 2 USD/kg H2, all H2 production plant sizes are economically viable. On this condition, a payback of fewer than 4 years, an IRR greater than 31, a break-even point between 56 and 68% of the production volume and a ROI above 400% were found. The sensitivity analysis showed that the best economic condition was found at 35.56 kg H2/h of the pl... [more]

Sustainable transportation refers to low vehicular greenhouse gas (GHG) emissions, energy efficient vehicles, and affordable modes of transportation, including electric and alternative fuel (AF) vehicles [...]

With the aim of arriving at more efficient and sustainable transport, the search for improvements in power electronics converters is the key to systems with a high efficiency and reliability [...]

Improving mass transfer in gas diffusion layers is critical to achieving high-performance proton-exchange membrane fuel cells (PEMFCs). Leaks through the interface between the gas and the membrane electrode assembly frame have been widely investigated, and the controllability of the cathode gas diffusion has not been achieved in most studies. In this study, we develop a structural parameter to investigate the controllability of the gas diffusion mechanism in the cathode in order to improve upon the design and performance of PEMFCs. This parameter accounts for the cathode gas diffusion layer porosity and carbon loading inside the catalyst layer. It is comprehensively calculated to relax the two segments’ distribution along three directions of the coordinate axis. The experimental and simulation results show that the obtained values of the parameter vary and change during voltage stabilization. According to the results, regardless of the materials in the cathode gas diffusion layer, the... [more]

Experimental data associated with the thermophysical properties (TPPs) of various nanofluids (NFs) are essential for their diverse applications in energy storage and conversion, as well as thermal management. This study experimentally investigated important TPPs such as thermal conductivity (TC), thermal diffusivity, density and viscosity, as well as the electrical conductivity of two new types of NFs, namely silica (SiC) and boron nitride (BN) nanofluids. The NFs are prepared at five low concentrations of nanoparticles from 0.01 to 0.05 vol.% dispersed into a mixture of ethylene glycol (EG) and distilled water (DW). The TPPs are measured, and their enhancements are evaluated in comparison with their base fluids. The results show a good increase in TC and thermal diffusivity for both types of nanofluids with increasing concentrations until reaching the maximum enhancement of about 4.4% for the SiC nanofluid and about 7.0% for the BN nanofluid at the same concentration (0.05 vol.%). On... [more]

This study presents a simulation of potential changes in groundwater in three wells within a Quaternary gravel aquifer in the city of Ljubljana when groundwater cooled by about 4 °C is reinjected into it. The research focuses on the mass transport of calcite in the vicinity of boreholes. According to our results, the impact of the changes in the geochemical composition of the water is relatively small (around 1%). Although the waters are approximately in equilibrium, calcite may be dissolved and sometimes precipitated within the aquifer when cooled water is reinjected into it. The amounts of precipitated calcite always decrease with decreasing temperatures of the reinjected water, which can lead to calcite dissolution if the temperature difference is large enough and the water is only slightly oversaturated. This novel finding is significant since previously published studies have mostly focused on understanding the scaling (precipitation) of calcite and not its dissolution. The mass t... [more]

Predicting multiphase flow in complex fractured reservoirs is essential for developing unconventional resources, such as shale gas and oil. Traditional numerical methods are computationally expensive, and deep learning methods, as an alternative approach, have become an increasingly popular topic. Fourier neural operator (FNO) networks have been shown to be a hundred times faster than convolutional neural networks (CNNs) in predicting multiphase flow in conventional reservoirs. However, there are few relevant studies on applying FNO to predict multiphase flow in reservoirs with complex fractures. In the present study, FNO-net and U-net (CNN-based) were successfully applied to predict pressure and gas saturation fields for the 2D heterogeneous fractured reservoirs. The tested results show that FNO can accurately depict the influence of fine fractures, while the CNN-based method has relatively poor performance in the treatment of fracture systems, both in terms of accuracy and computatio... [more]

A piezoelectric energy harvester (PEH) transduces mechanical energy into electrical energy, which can be utilized as an energy source for self-powered or low-power devices. Therefore, maximizing the power of a PEH is a crucial design objective. It is well known that structural designs are firstly conducted for controlling resonance characteristics, and then circuit designs are pursued through impedance matching for improving power. However, a PEH contains solid mechanics, electrostatics, and even a circuit-coupled multi-physics system. Therefore, this research aims to design a PEH considering a circuit-coupled multi-physics. As a design process, a conceptual design is developed by topology optimization, and a detailed design is developed sequentially by applying size optimization as a post-processing step to refine the conceptual design results for manufacturable design. In the two optimization processes, design optimizations of a structure coupled with circuit resistor are performed t... [more]

The kick-off process is an important aspect of the proper operation of an agricultural biogas plant. At this stage, various operational problems may arise, mainly related to the stabilization of the fermentation process and reaching the full biogas production capacity. This paper presents the results of research on the kick-off of the fermentation process carried out on three selected biogas plants located in Poland. For the experiments, titration, potentiometric, and spectroscopic methods (ICP-MS) were used. The biogas plants during the kick-off period operated on the following substrates: a mixture of cattle and pig manure, corn silage, and whey liquor. Special attention was paid to the dosing process of the formulation developed by the authors (CMP-S1) containing Mo, Co, Ni, Se, and Mn for the fermentation chambers, to which the mixture of the selected microelements was not dosed. The study was carried out under real conditions on an engineering scale. The study showed that suppleme... [more]

Permanent magnet synchronous generator (PMSG) wind power system with full power rating converter configuration is especially suitable for wind energy applications. Direct model predictive control (DMPC) has led to more possibilities in terms of choice because of its straightforward concept for PMSG wind turbine systems in high-power off-shore wind farms. However, due to complete dependence on the model knowledge, parameter mismatches will seriously deteriorate the system control performances. This work presents a model/parameter-independent predictive control method with a novel mechanism to update current/power variations online. The proposed method makes use of only two measurements from the former intervals and the selected control vectors to estimate all variations of the candidate vectors in the present interval. Benefiting from this updating mechanism, the proposed method is completely independent of the model parameters in the state prediction. However, it still has a very low c... [more]

This article presents a brushless DC motor (BLDCM) drive for a maritime electric vehicle (MEV) application. The presented BLDCM drive uses a bridgeless Cuk-buckboost (BL-Cuk-BB) converter for input-side power factor (PF) improvement. The BL-Cuk-BB converter uses the buckboost converter for the negative half-cycles of the input AC voltages and the Cuk converter for the positive half-cycles. In the case of MEVs, the drive systems are generally fed by diesel engine generators (DEGs). The asymmetric BL-Cuk-BB converter is operated in a discontinuous inductor current mode (DICM) in the present work to attain better power quality. The usage of a second-order buckboost converter with a fourth-order Cuk converter results in a decrement in the net order of the system. Additionally, the input inductor of the Cuk converter also participates as the filter component along with capacitor C2 during buckboost converter operation to enhance the power quality. The total component count reduction in the... [more]

In recent years, gasification gained attention again, both as an industrial application and as a research topic. This trend has led to the necessity to understand the process and optimize reactors for various materials and configurations. In this article, the thermal structure of a counter-current reactor is investigated to demonstrate that constraints on the temperature mainly determine the oxidation and the pyrolysis region. A non-dimensional set of equations is written and numerically solved using the method of lines (MOL) with spatial discretization based on a spectral algorithm. The results show that four thermal structures can be identified, two of which are the most common ones found in reactors of practical applications. Two stationary operation positions have been determined, one in the upper and one in the lower part of the reactor. Existence and stability conditions have been discussed based on non-dimensional parameters. The knowledge derived from this analysis was applied... [more]

The depletion of fossil fuel sources has encouraged the authorities to use renewable resources such as wind energy to generate electricity. A backup/storage system can improve the performance of wind turbines, due to fluctuations in power demand. The novelty of this study is to utilize a hybrid system for a wind farm, using the excess electricity generated by the wind turbines to produce hydrogen in an alkaline electrolyzer (AEL). The hydrogen storage tank stores the produced hydrogen and provides hydrogen to the proton-exchange membrane fuel cell (PEMFC) to generate electricity once the power demand is higher than the electricity generated by the wind turbines. The goal of this study is to use the wind profile of a region in Iran, namely the Cohen region, to analyze the performance of the suggested integrated system on a micro scale. The output results of this study can be used as a case study for construction in the future, based on the exact specification of NTK300 wind turbines. Th... [more]

Injecting power plant flue gas into a goaf stores CO2 in the flue gas and effectively prevents the spontaneous combustion of the coal remaining in the goaf. Here, we investigated the adsorption behavior of three types of coal at normal temperature and pressure using a self-developed adsorption experimental device. We used a specific surface area and porosity analyzer to study the effects of pore structure, mineral content, and moisture content on CO2 adsorption in coal. Based on the experimental data, we designed a multifactor CO2 adsorption prediction model based on a backpropagation (BP) neural network. The results indicated that the pore size of most micropores in coal was in the range of 0.5−0.7 and 0.8−0.9 nm. The specific surface area and pore volume were positively correlated with the CO2-saturated adsorption capacity, whereas the mean pore diameter, mineral content, and moisture content were inversely associated with the CO2-saturated adsorption amount. The accuracy of the mult... [more]

The relevance of the application of hydraulic thruster technology is determined by the technological limitations of drilling both vertical and horizontal wells. The existing experimental studies confirm the effectiveness of the technology, but its widespread implementation is hindered by the lack of scientific foundations for its operation in combination with a downhole motor and bit. Our research methodology includes methods for analyzing scientific and technical information as well as methods of numerical modeling using programming languages and ready-made software packages for CFD calculations. Verification of the simulation results was carried out on the basis of the experimental field studies previously conducted with the participation of the authors of the article. This article presents the results of the analysis of the current state of the problem and computer physical and mathematical modeling of the work of the thruster together with the bit and downhole motor when drilling a... [more]

This paper presents a numerical study on thermal energy mining from hot dry rock (HDR) using an enhanced geothermal system (EGS). In these simulations, the thermal−hydraulic−mechanical (THM) coupling model is employed on the basis of the embedded discrete fracture model. The evolution of physical fields of the fractured reservoir, including temperature field, pressure field, and stress field is studied over time, and the effects of different controllable factors, such as fracture morphology, fluid injection rate, and the distances between the injection well and producing well on the heat recovery capacity are investigated. The results show that the fracture morphology significantly influences heat extraction performance. The working fluid mainly flows along with the fracture networks, which causes locally low temperatures and low mean effective stress near fractures. The porosity and permeability increase due to the decrease in mean effective stress. For reservoir models with inclined... [more]

Photovoltaic (PV) cells are a major part of solar power stations, and the inevitable faults of a cell affect its work efficiency and the safety of the power station. During manufacturing and service, it is necessary to carry out fault detection and classification. A convolutional-neural-network (CNN)-architecture-based PV cell fault classification method is proposed and trained on an infrared image data set. In order to overcome the problem of the original dataset’s scarcity, an offline data augmentation method is adopted to improve the generalization ability of the network. During the experiment, the effectiveness of the proposed model is evaluated by quantifying the obtained results with four deep learning models through evaluation indicators. The fault classification accuracy of the CNN model proposed here has been drawn by the experiment and reaches 97.42%, and it is superior to that of the models of AlexNet, VGG 16, ResNet 18 and existing models. In addition, the proposed model ha... [more]

The European building sector is responsible for approximately 40% of total energy consumption and for 36% of greenhouse gas emissions. Identifying technological solutions capable of reducing energy consumption and greenhouse gas emissions is one of the main objectives of the European Commission. Ground source heat pumps (GSHPs) are of particular interest for this purpose, promising a considerable reduction in greenhouse gas emissions of HVAC systems. This paper reports the results of the energetic analysis carried out within the EU research project GEO4CIVHIC about the performance of geothermal heat pumps working with low-GWP refrigerants as alternatives for R134a and R410A. The work has been carried out through computer simulations based on base and regenerative reverse cycles. Several heat sink and heat source temperature conditions have been considered in order to evaluate the GSHPs’ performance in the whole range of real conditions that can be found in Europe. Particular attention... [more]

As social and environmental issues become increasingly serious, both fuel costs and environmental impacts should be considered in the cogeneration process. In recent years, combined heat and power economic emission dispatch (CHPEED) has become a crucial optimization problem in power system management. In this paper, a novel reinforcement-learning-based multi-objective differential evolution (RLMODE) algorithm is suggested to deal with the CHPEED problem considering large-scale systems. In RLMODE, a Q-learning-based technique is adopted to automatically adjust the control parameters of the multi-objective algorithm. Specifically, the Pareto domination relationship between the offspring solution and the parent solution is used to determine the action reward, and the most-suitable algorithm parameter values for the environment model are adjusted through the Q-learning process. The proposed RLMODE was applied to solve four CHPEED problems: 5, 7, 100, and 140 generating units. The simulatio... [more]

The Middle East, Gulf Cooperation Council Countries (GCC), and Kuwait, in particular, are currently experiencing a similar transition as the USA in the 1970s regarding the empowerment and independence of women, fueled by a declining birth rate from four per women to less than two. In addition, the percentage of women with university degrees has been increasing at a logarithmic rate every decade since the 1960s in the USA and since 1990 in Kuwait, resulting in women comprising well over half of all university graduates. This has led to women obtaining better jobs and enjoying greater independence to make their own decisions. In the 1960s, Toyota and other Japanese car manufactures used this phenomenon to penetrate the US market, with significant success. Their selling points were lower maintenance requirements, higher reliability, safety, better environment friendliness and slicker interior designs, the last being especially adapted to women’s tastes. We believe that Chinese and Korean... [more]

This paper presents a novel approach to tackle the problem of optimal neutral wire grounding in bipolar DC networks including asymmetric loading, which naturally involves mixed-integer nonlinear programming (MINLP) and is challenging to solve. This MINLP model is transformed into a recursive mixed-integer quadratic (MIQ) model by linearizing the hyperbolic relation between voltage and powers in constant power terminals. A recursive algorithm is implemented to eliminate the possible errors generated by linearization. The proposed recursive MIQ model is assessed in two bipolar DC systems and compared against three solvers of the GAMS software. The results obtained validate the performance of the proposed MIQ model, which finds the global optimum of the model while reducing power losses for bipolar DC systems with 21, 33, and 85 buses by 4.08%, 2.75%, and 7.40%, respectively, when three nodes connected to the ground are considered. Furthermore, the model exhibits a superior performance wh... [more]