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In order to reveal the migration and evolution of gas molecules in the actual oil–paper insulation composite system of transformer from the molecular level, the diffusion behavior of seven gas molecules (H2, CO, CO2, CH4, C2H2, C2H4, C2H6) generated during the operation and aging of oil-immersed transformers in the oil–paper composite insulation system is studied by molecular dynamics. Firstly, based on the molecular dynamics software, the model of the oil–paper composite insulation system and the gas molecule model is constructed. In order to compare and analyze the diffusion properties of gas molecules in a single medium, a single model of insulating oil and cellulose is also constructed. Then, the diffusion coefficients of gas molecules in the insulating oil, cellulose, and oil–paper insulating composite system are simulated and calculated. And the differences in the diffusion properties of gas molecules in the three insulating mediums are discussed. Finally, the microscopic mechanism of diffusion of different gas molecules in the three mediums is analyzed. The simulation results show that among the three mediums, the diffusion coefficient of H2 is the largest, while the diffusion coefficients of the other gas molecules are not very different. The diffusion coefficients of the seven gas molecules are the smallest in the oil-immersed paper composite insulation system, followed by cellulose, while the diffusion coefficients are the largest in mineral oil. It indicates that the diffusion of gas molecules is inhibited in oil–paper insulation systems where the insulating paper is completely immersed in oil. This is mainly due to the fact that the insulating oil completely penetrates into the paper, filling the pores and voids between the fibers, resulting in a reduction in the transition vacancies of the intermediate gas molecules, which hinders the diffusion of the gas molecules. [ABSTRACT FROM AUTHOR]

In this paper, the aging characterization of a kind of insulating paper modified by magnetron sputtering MgO particles based on a microstrip resonant sensor was presented. Firstly, the modified insulating paper with 0, 15 and 30 min MgO particle sputtering times was prepared by a magnetron sputtering device. After that, the properties of the modified insulating paper with different sputtering times were analyzed through microscopic characterization, infrared spectrum, polymerization degree, dielectric constant, AC breakdown strength and thermal aging experiments. The results show that the dielectric constant of the modified insulating paper decreased obviously, the AC breakdown strength increased and the thermal aging resistance was better after 15 min of sputtering. The overall performance of the modified insulating paper after 30 min of sputtering is reduced due to excessive sputtering. In addition, microstrip resonant sensors are introduced to characterize the thermal aging degree of the modified insulating paper, and two microstrip resonant sensors are prepared: a complementary split ring resonator (CSRR) and an interdigital-capacitor-shaped defected ground structure resonator (IDCS-DGS). The resonance frequency deviation of the modified insulating paper samples after aging was measured by microstrip resonance sensors to show the influence of aging temperature on aging degree. The experimental results show that the test results of the microstrip resonance sensors are in good agreement with the traditional characterization methods and can characterize the various aging stages of the modified insulating paper to a certain extent, which proves the feasibility of the characterization method. [ABSTRACT FROM AUTHOR]

Oil–paper insulation is the critical insulation element in the modern power system. Under a harsh operating environment, oil–paper insulation will deteriorate gradually, resulting in electrical accidents. Thus, it is important to evaluate and monitor the insulation state of oil–paper insulation. Firstly, this paper introduces the geometric structure and physical components of oil–paper insulation and shows the main reasons and forms of oil–paper insulation's degradation. Then, this paper reviews the existing condition assessment techniques for oil–paper insulation, such as the dissolved gas ratio analysis, aging kinetic model, cellulose–water adsorption isotherm, oil–paper moisture balance curve, and dielectric response technique. Additionally, the advantages and limitations of the above condition assessment techniques are discussed. In particular, this paper highlights the dielectric response technique and introduces its evaluation principle in detail: (1) collecting the dielectric response data, (2) extracting the feature parameters from the collected dielectric response data, and (3) establishing the condition assessment models based on the extracted feature parameters and the machine learning techniques. Finally, two full potential studies are proposed, which research hotspots' oil–paper insulation and the electrical–chemical joint evaluation technique. In summary, this paper concludes the principles, advantages and limitation of the existing condition assessment techniques for oil–paper insulation, and we put forward two potential research avenues. [ABSTRACT FROM AUTHOR]

The aim of this research is to predict the mechanical properties along with the behaviors of standard insulating paper used in power transformers under thermal aging. This is conducted by applying an artificial neural network (ANN) trained with a multiple regression model and a particle swarm optimization (MR-PSO) model. The aging of the paper insulation is monitored directly by the tensile strength and the degree of polymerization of the solid insulation and indirectly by chemical markers using 2-furfuraldehyde compound content in oil (2-FAL). A mathematical model is then developed to simulate the mechanical properties (degree of polymerization (DPV) and tensile index (Tidx)) of the aged insulation paper. First, the datasets obtained from experimental results are used to create the MR model, and then the optimizer method PSO is used to optimize its coefficients in order to improve the MR model. Then, an ANN method is trained using the MR-PSO to create a nonlinear correlation between the DPV and the time, temperature, and 2-FAL values. The acquired results are assessed and compared with the experimental data. The model presents almost the same behavior. In particular, it has the capability to accurately simulate the nonlinear property behavior of insulation under thermal aging with an acceptable margin of error. Since the life expectancy of power transformers is directly related to that of the insulating paper, the proposed model can be useful to maintenance planners. [ABSTRACT FROM AUTHOR]

Natural and synthetic esters are increasingly being chosen instead of mineral oil for environmental and fire safety reasons. However, their use in power transformers is limited due to insufficiently well-understood ageing processes affecting their properties and the properties of cellulosic materials impregnated with them. The research results presented in many scientific papers prove that the use of esters slows the ageing process of cellulosic materials. This article presents the results of research aimed at answering the question of whether the effect of slowing the ageing process will also occur in the case of insulation with very low initial moisture. The answer to this question will allow us to better understand the role of water in the ageing process of the transformer's insulation system. The thermal ageing process was carried out at a temperature of 150 °C in closed systems. The degree of cellulose polymerisation was taken as a measure of the degree of paper ageing. Great attention was paid to measuring the water content in both paper and electro-insulating liquids at various stages of their ageing. Furthermore, measurements of the properties of electro-insulating liquids were made, which are considered markers of ageing. The test results obtained indicate that in the case of a dry insulation system, corresponding to the initial moisture of the new units, the type of liquid used to impregnate the cellulosic material does not significantly affect its depolymerisation process. However, in the case of paper impregnated with natural esters, a lower dynamic of moisture increase in insulation was observed. [ABSTRACT FROM AUTHOR]

Chemical compounds dissolved in insulating oil, as indicators can excellently monitor the paper aging condition, which has attracted increasing interest in areas of transformer condition monitoring and fault diagnosis. Because of their outstanding features, such as good correlation with the degree of polymerization of cellulose paper and the aid of non-destructive online monitoring, chemical indicators have been effectively used for transformer condition assessment. In this study, a comprehensive, in-depth insight into the indicators of the aging of insulating paper from aging characteristics, physico-chemical characteristics, shortcomings of various compounds, generation pathways and mechanisms, and monitoring technologies are provided. It is expected that these chemical indicators can provide better guidance for the evaluation of paper insulation performance and transformer aging. In addition, the latest research progress, as well as current challenges and future prospects are also outlined. This study provides a theoretical basis and reference for chemical indicators in the fields of microscopic formation mechanism, diffusion equilibrium phenomenon, and insulation aging state assessment. [ABSTRACT FROM AUTHOR]

The pulp and paper industry (PPI) has several opportunities to contribute to meeting prevailing climate targets. It can cut its own CO2 emissions, which currently account for 2% of global industrial fossil CO2 emissions, and it has an opportunity to produce renewable energy, fuels, and materials for other sectors. The purpose of this study is to improve understanding of the decarbonization prospects of the PPI. The study provides insights on the magnitude of needed annual renewal rates for several possible net-zero target years of industrial fossil CO2 emissions in the PPI and discusses decarbonization opportunities, namely, energy and material efficiency improvement, fuel switching, electrification, renewable energy production, carbon capture, and new products. The effects of climate policies on the decarbonization opportunities are critically evaluated to provide an overview of the current and future business environment of the European PPI. The focus is on Europe, but other regions are analyzed briefly to widen the view. The analysis shows that there are no major technical barriers to the fossil-free operation of the PPI, but the sector renovates slowly, and many new opportunities are not implemented on a large scale due to immature technology, poor economic feasibility, or unclear political environment. [ABSTRACT FROM AUTHOR]

In the field of intelligent transportation, the planning of traffic flows that meet energy-efficient driving requirements necessitates the acquisition of energy consumption data for each vehicle within the traffic flow. The current methods for calculating vehicle energy consumption generally rely on longitudinal dynamics models, which require comprehensive knowledge of all vehicle power system parameters. While this approach is feasible for individual vehicle models, it becomes impractical for a large number of vehicle types. This paper proposes a digital model for vehicle driving energy consumption using vehicle speed, acceleration, and battery state of charge (SOC) as inputs and energy consumption as output. The model is trained using an optimized CNN-BiLSTM-Attention (OCBA) network architecture. In comparison to other methods, the OCBA-trained model for predicting PHEV driving energy consumption is more accurate in simulating the time-dependency between SOC and instantaneous fuel and power consumption, as well as the power distribution relationship within PHEVs. This provides an excellent framework for the digital modeling of complex power systems with multiple power sources. The model requires only 54 vehicle tests for training, which is significantly fewer than over 2000 tests typically needed to obtain parameters for power system components. The model's prediction error for fuel consumption under unknown conditions is reduced to 5%, outperforming the standard error benchmark of 10%. Furthermore, the model demonstrates high generalization capability with an R2 value of 0.97 for unknown conditions. [ABSTRACT FROM AUTHOR]

A transpiration-type thermoelectric-power-generating paper based on previously developed carbon nanotube (CNT) composite paper, which is a composite material of CNTs and pulp that can generate thermoelectric power, was developed. The newly developed thermoelectric-power-generating material does not require an external high-temperature heat source due to the ability of paper to absorb liquid through capillary action and heat of vaporization generated when the liquid evaporates. The aim of this study is to investigate the feasibility of realizing the transpiration-type thermoelectric-power-generating paper. To begin with, the type of paper used as raw material for the composite paper was examined, and the fabrication process was modified in order to obtain more efficient liquid absorption based on capillary action. Then, the absorbing ability of the liquid was evaluated. Next, the feasibility of thermoelectric power generation using the heat of vaporization was confirmed. Moreover, for more efficient thermoelectric conversion, multisheet structures were also studied. Through several experiments, the material's feasibility was verified, and it was confirmed that more power can be easily obtained through the use of multiple sheets. Specifically, a single sample spontaneously generated a temperature difference of up to 1.7 °C due to the heat of vaporization, generating an electromotive force of 36 μ V. From the sample with a five-sheet structure, an electromotive force of 356 μ V was obtained at a temperature difference of 2 °C. This material can be used in watery environments, such as rivers, lakes, and hot springs, and is expected to become a new energy-harvesting device. [ABSTRACT FROM AUTHOR]

The treatment and disposal of sewage sludge is one of the most important and critical issues of wastewater treatment plants. One option for sludge liquidation is the production of fuel in the form of pellets from mixed sewage and paper mill sludge. This study presents the results of the combustion of pelletized fuels, namely sewage and paper mill sludge, and their 2:1 and 4:1 blends in a fluidized bed combustor. The flue gas was analysed after reaching a steady state at bed temperatures of 700–800 °C. Commonly used flue gas cleaning is still necessary, especially for SO2; therefore, it is worth mentioning that the addition of paper mill sludge reduced the mercury concentration in the flue gas to limits acceptable in most EU countries. The analysis of ash after combustion showed that magnesium, potassium, calcium, chromium, copper, zinc, arsenic, and lead remained mostly in the ash after combustion, while all cadmium from all fuels used was transferred into the flue gas together with a substantial part of chlorine and mercury. The pellets containing both sewage and paper mill sludge can be used as an environmentally friendly alternative fuel for fluidised bed combustion. The levelized cost of this alternative fuel is at the same current price level as lignite. [ABSTRACT FROM AUTHOR]

The article presents studies on the impact of the significant process parameters of a paper machine with a Yankee cylinder on its production capacity and heat energy consumption for drying the paper web. Parameters such as machine speed, web moisture content before and after pressing, parameters of steam supplied to the cylinder and parameters of hot air flowing from the nozzles of the hood were analyzed. The study's results were used to optimize production to improve the energy efficiency and performance of the machine. In order to use the possible methods of improving the production capacity and heat energy consumption, the parameters of the production process were measured and the basic indicators characterizing the operation of the machine were calculated in the Yankee cylinder–dryer hood system. The correct functioning of the machine components and the possibility of their modernization were also analyzed. Technological and construction changes introduced based on the research results made it possible to increase the production capacity by 10% and to reduce the consumption of heat energy per 1 ton of produced paper by 16.3%. The article presents a description of changes in the technology of paper production and modernization of the tissue machine made in the years 2013–2022. [ABSTRACT FROM AUTHOR]

The pulp and paper industry is recognized as a well-established sector, which throughout its process, generates a vast amount of waste streams with the capacity to be valorized. Typically, these residues are burned for energy purposes, but their use as substrates for biological processes could be a more efficient and sustainable alternative. With this aim, it is essential to identify and characterize each type of waste to determine its biotechnological potential. In this context, this research highlights possible alternatives with lower environmental impact and higher revenues. The bio-based pathway should be a promising alternative for the valorization of pulp and paper industry wastes, in particular for bioproduct production such as bioethanol, polyhydroxyalkanoates (PHA), and biogas. This article focuses on state of the art regarding the identification and characterization of these wastes, their main applied deconstruction technologies and the valorization pathways reported for the production of the abovementioned bioproducts. [ABSTRACT FROM AUTHOR]

Forecasting has extreme importance in industry due to the numerous competitive advantages that it provides, allowing to foresee what might happen and adjust management decisions accordingly. Industries increasingly use sensors, which allow for large-scale data collection. Big datasets enable training, testing and application of complex predictive algorithms based on machine learning models. The present paper focuses on predicting values from sensors installed on a pulp paper press, using data collected over three years. The variables analyzed are electric current, pressure, temperature, torque, oil level and velocity. The results of XGBoost and artificial neural networks, with different feature vectors, are compared. They show that it is possible to predict sensor data in the long term and thus predict the asset's behaviour several days in advance. [ABSTRACT FROM AUTHOR]

Carbon emissions from the Yangtze River Economic Belt are an important element of China's carbon emission endeavor, and a study of its emission reduction pathway can provide a reference for the country's overall management of carbon emission reduction. From the perspective of energy consumption, this paper uses the carbon emission factor method to estimate the carbon emissions of the transportation industry in the Yangtze River Economic Belt during 2006–2020, based on the extended STIRPAT model, considering the influence of seven factors, i.e., population size, urbanization rate, GDP per capita, transportation added value, energy structure, energy intensity, and transportation intensity, on carbon emissions. Based on these factors, a scenario analysis, combined with a forecasting model, is used to predict the peak carbon performance of the transportation industry under different development scenarios. The results show that the overall carbon emissions of transportation in the YEB from 2006 to 2020 show a fluctuating upward trend, and the downstream carbon emissions are significantly higher than those in other regions. The main factors influencing carbon emissions from transportation in different upstream, midstream, and downstream regions vary, with both population and economic factors contributing to carbon emissions, while technical factors affect them differently. There are significant differences in the peak carbon performance of transportation under different development scenarios, and the government should take effective measures to work towards achieving the goals of the low-carbon or enhanced low-carbon scenarios. [ABSTRACT FROM AUTHOR]

Although there are opportunities to reduce electrical energy demand in unit processes of mechanical pulp-based paper and paperboard production, this may not be financially beneficial. This is generally because energy optimization opportunities connected to reduced refiner electricity demand in mechanical pulping systems also results in less steam available for the drying of the paper. As modern high consistency refiner systems produce approximately one ton of steam for each MWh of electricity when producing one ton of pulp, a reduction in electric energy demand leads to increased fuel demand in steam boilers to compensate for the steam shortage. In this study, we investigated what the financial and environmental situation would look like if we were to expand the system border from a paper mill to a larger system consisting of a mechanical pulp-based paper or paperboard mill, a district heating system with an incineration boiler and a chemical pulp mill. Mechanical pulp production has a wood to product yield of >90%, a high electric energy demand to separate woodchips to pulp and is a net producer of heat and steam while chemical pulp-based production has a wood to product yield of 50%, a low electric energy demand and is a net heat and electricity producer due to the combustion of dissolved wood polymers. The aim of this research is to create useful and robust models of how to use excess heat from certain industry sites to cover the steam shortage in other industry sites by means of utilizing and optimizing the district heating systems connecting these sites. For this purpose, we used a simulation tool which dynamically allows us to evaluate different scenarios. Our results shows that there is great potential to reduce both carbon dioxide emissions and production costs for industry sites and society by means of these tools. [ABSTRACT FROM AUTHOR]

Insulation cellulose paper is a basic measure for a power transformer's remaining useful life, and its advantageous low cost, electrical, and mechanical properties have made it an extensive insulation system when impregnated in a dielectric liquid. Cellulose paper deteriorates as a result of ageing due to some chemical reactions like pyrolysis (heat), hydrolysis (moisture), and oxidation (oxygen) that affects its degree of polymerization. The condition analysis of cellulose paper has been a major concern since the collection of paper samples from an operational power transformer is almost impossible. However, some chemicals generated during cellulose paper deterioration, which were dissolved in dielectric liquid, have been used alternatively for this purpose as they show a direct correlation with the paper's degree of polymerization. Furthermore, online and non-destructive measurement of the degree of polymerization by optical sensors has been proposed recently but is yet to be available in the market and is yet generally acceptable. In mitigating the magnitude of paper deterioration, some ageing assessments have been proposed. Furthermore, researchers have successfully enhanced the insulating performance of oil-impregnated insulation paper by the addition of various types of nanoparticles. This study reviews the ageing assessment of oil-paper composite insulation and the effect of nanoparticles on tensile strength and electrical properties of oil-impregnated paper insulation. It includes not only significant tutorial elements but also some analyses, which open the door for further research on the topic. [ABSTRACT FROM AUTHOR]

The building sector contributes to 40% of the total final energy consumption and 36% of CO2 emissions in Europe, and these are set to increase in the coming years. International directives are pushing towards a decarbonisation roadmap to improve the quality of cities and the health of citizens. Buildings have a potentially central role in terms of energy transition as a means to produce and save energy. Photovoltaic shading devices (PVSDs) protect buildings from direct solar radiation and overheating while producing renewable electricity onsite and increasing the users' thermal comfort. Even though the potential of the PVSD is considerable, the sector is still unexplored, and few studies on the topic are available in the literature. This systematic review aims to present an exhaustive overview of the current literature on state-of-the-art PVSDs by analysing the scientific framework in terms of the status of the research. It presents a performance-based approach focusing on innovative products, PVSD design strategies, and energetic performance in distinct climate conditions and configurations. In particular, 75 articles and about 250 keywords were identified, selected, and analysed. The literature review serves as a basis for further R&D activities led by both the industrial and the academic sectors. [ABSTRACT FROM AUTHOR]

Numerical simulation of polypropylene laminated paper insulation is a serious challenge, as it must take into account the layered structure and presence of longitudinal and radial gaps in the coils of the winded tape for cables with sector-shape conductive cores. Thus far, it has been performed only with serious simplifications. We propose a technique for numerical modeling of electric parameters in this type of insulation by reducing a complex 3D problem to a simplified 2D model that takes into account the main influencing factors. The results of modeling the distribution of electric field strength and current density in insulation are presented, and the influence of the location of gaps between the edges of winded tape on the conductivity of cable insulation is estimated. Analytical expressions are obtained for estimating the electrical resistance of insulation while taking into account the parameters of the butt gap between the insulating tapes. The results of calculations, numerical modeling, and experimentally measured values of electrical resistance are compared, showing that there is a good match. The main effects affecting the properties of polypropylene laminated paper insulation are described. [ABSTRACT FROM AUTHOR]

The hot pressing parameters and fiber ratio have an important influence on the dielectric properties of aramid insulating paper. In order to deeply explore its influence and the mechanism behind it, aramid insulating papers were made with different hot pressing temperatures and pressures as well as fiber ratios. Its tightness, dielectric constant, and AC breakdown strength were tested, and its microstructure was analyzed by scanning electron microscopy. It was found that with an increase in hot pressing temperature, pressure, and fibrid content, the overall dielectric constant of the insulating paper showed a slight upward trend, while the tightness and AC breakdown strength continued to increase. Hot pressing temperature and pressure have a synergistic effect on the dielectric properties of insulating paper. The effects of these two parameters on the dielectric properties of insulating paper are similar, while the AC breakdown strength is greatly affected by the fiber ratio. In this paper, the influence mechanism by which the microstructure and fiber crystallinity of insulating paper is affected in the hot pressing process is discussed. [ABSTRACT FROM AUTHOR]

Recently, as the use of wearable devices and the demand for eco-friendly energy have increased, many studies have been conducted on triboelectric nanogenerators (TENGs), which can economically harvest energy. Paper is considered a promising substrate and frame material that can be used to manufacture self-powered TENGs, owing to its flexibility, low cost, and accessibility. Herein, we present a sandwich-structured foldable paper-based TENG (FP-TENG) that comprises flexible materials and uses paper as a substrate. The FP-TENG can generate up to 572 mW/m2 of power via contact–separation of the triboelectric electrified body at the top and bottom. With more folds of the FP-TENG, the triboelectric cross-sectional area increases, and, thus, the electrical output increases. In addition, the proposed TENG exhibits excellent durability without signal degradation under 5000 cycles of repeated pushing motions. To demonstrate its practicality, the FP-TENG was manufactured in the form of a wristwatch Velcro and connected to an electronic watch panel to supply power. Various deformations are possible with origami, and they can drive wristwatches through external forces. Therefore, the FP-TENG is expected to be utilized as a sustainable and promising eco-friendly energy source for small electronic devices. [ABSTRACT FROM AUTHOR]

In this paper, the combustion behavior of low rank coal and its product after hydrothermal carbonization with paper sludge hydrochar were studied. The Raman technique was used to compare the structural differences between raw coal and the product. Thermogravimetric analysis was employed to conduct experiments of single sample and their mixtures with different proportions at a heating rate of 20 °C/min, the activation energy of chemical reactions was calculated. The results showed that upgraded product had higher carbon ordering degree than raw coal and the ignition temperature and burnout temperature of the product were advanced. Compared with raw coal, the combustion characteristic parameters C and S of the product were higher, indicating that its combustibility was better. As for the mixture, when the paper sludge hydrochar ratio was not more than 10%, the mixed fuel combustion curve was still similar to coal curve. After the paper sludge hydrochar ratio exceeded 10%, the activation energy of the mixed combustion reaction of paper sludge hydrochar and upgraded coal was lower than that of raw coal and paper sludge hydrochar. These results indicated that the mixture of upgraded coal and paper sludge hydrochar as mixed fuel was a better option. [ABSTRACT FROM AUTHOR]

The paper reports the results of a comparative assessment concerned with the effectiveness of identifying the basic forms of partial discharges (PD) measured by the acoustic emission technique (AE), carried out by application of selected machine learning methods. As part of the re-search, the identification involved AE signals registered in laboratory conditions for eight basic classes of PDs that occur in paper-oil insulation systems of high-voltage power equipment. On the basis of acoustic signals emitted by PDs and by application of the frequency descriptor that took the form of a signal power density spectrum (PSD), the assessment involved the possibility of identifying individual types of PD by the analyzed classification algorithms. As part of the research, the results obtained with the use of five independent classification mechanisms were analyzed, namely: k-Nearest Neighbors method (kNN), Naive Bayes Classification, Support Vector Machine (SVM), Random Forests and Probabilistic Neural Network (PNN). The best results were achieved using the SVM classification tuned with polynomial core, which obtained 100% accuracy. Similar results were achieved with the kNN classifier. Random Forests and Naïve Bayes obtained high accuracy over 97%. Throughout the study, identification algorithms with the highest effectiveness in identifying specific forms of PD were established. [ABSTRACT FROM AUTHOR]

The aim of the work was to prepare and test a paper-oil insulation system according to the recommendations of CIGRE (Conseil International des Grands Réseaux Électriques) with the parameters X = 50% and Y = 30%. Pressboard was moistened to a water content of (5.0 ± 0.2) wt.% The loss tangent was measured using a DIRANA meter (FDS-PDC dielectric response analyzer) in the frequency range 10−4 Hz–5000 Hz for 6 temperatures from 293.15 K to 333.15 K with a step of 8 K. The waveforms simulated by the DIRANA software were fitted to the experimental dependence of the loss tangent. The fitting process was performed using two methods. In the first method, the measuring temperature value as well as X and Y values were entered into the software. The estimated moisture content of the insulation varied from about 1.4 to about 5.2 wt.%. The average value of moisture content was (3.73 ± 1.11) wt.%. In the second method, only the measuring temperature value was entered into the software. This improved the quality of matching. The estimated average moisture content was (5.83 ± 0.25) wt.%. It was found that the dimensions of the oil channel clearly affected the quality of the fitting process. By not taking into consideration real values of oil channel, the quality of the moisture content estimation was significantly improved. [ABSTRACT FROM AUTHOR]

A helium (He) dielectric barrier discharge plasma jet (DBD jet) was used for the first time for treating graphite foil as the current collector of a paper-based fluidic aluminum-air battery. The main purpose was to improve the distribution of the catalyst layer through modification and functionalization of the graphite foil surface. The plasma functionalized the graphite foil surface to enhance the wettability where the more hydroxyl could be observed from XPS results. The 30 s-He DBD jet treatment on the graphite foil significantly improved the battery performance. The best current density of 85.6 mA/cm2 and power density of 40.98 mW/cm2 were achieved. The energy density was also improved to 720 Wh/kg. [ABSTRACT FROM AUTHOR]

The paper describes the digital twin of a Li-ion battery cell based on the MATLAB/Simulink generic model. The digital twin is based on measured data for constant current/constant voltage charging and discharging cycles with State of Health (SoH) up to 79%, also including fast charging. Mathematical equations used for the digital twin are obtained by 3D data fitting of measured SoH, battery capacity, and battery cell current. The input to the proposed digital twin is only the measured battery cell current, and its output includes State of Charge (SoC), SoH, and battery cell voltage. The designed digital twin is tested and compared with MATLAB/Simulink generic model and battery cell measurements for constant discharging current and dynamically generated discharging current profile. The results show significant improvement in the generic MATLAB/Simulink model. [ABSTRACT FROM AUTHOR]

In this framework, experimental tests on different battery technologies, BMS and cooling systems are extremely important to extend the battery life and BEV performance (Sehil et al. [[13]]). Electrical machines and magnetic components, high-voltage voltage power converters, and battery storage systems are some basic bricks to build an effective and efficient energy conversion environment. Electrical Machines and Power Converters The electrical power conversion from renewable energy sources plays a crucial role in the development of a sustainable society. Finally, the fil rouge of every contribution in this section is oriented to investigate the power converters, electrical machines, magnetic components, and battery storage systems in actual energy conversion applications for renewable energy sources integration by a modelling approach. [Extracted from the article]

Finding sustainable solutions to the increasing waste generation in Ghana has received a lot of attention in recent years. Through several waste-to-energy processes, the energy potential of municipal solid waste has recently witnessed significant technological advancements. The Renewable Energy Master Plan has projected the production of about 122 MWp from waste-to-energy installations by 2030 in Ghana. To help policymakers and engineers achieve national goals, this paper reviews the waste generation in Ghana estimated from 2010 to 2030 and the status of various bioenergy technologies in Ghana. This paper further estimates the energy recovery potential of municipal solid waste in Ghana under incineration, anaerobic digestion, and landfill gas recovery technologies. The review establishes that, by 2030, municipal solid waste generation will increase by 123% of the 2023 quantities and may produce 1484.25 MW of installed electricity capacity and 13,002.03 GWh per year, which would amount to nearly 59% of Ghana's 2030 renewable energy target. Additionally, it was determined that anaerobic digestion, incineration, and landfill gas recovery technologies, when properly developed, will add 105.33 MW, 301.4 MW, and 377.31 MW of installed electrical capacity, respectively, to Ghana's energy mix in 2028. [ABSTRACT FROM AUTHOR]

This paper focuses on proton exchange membrane fuel cell (PEMFC) operation at current densities in the order of 6 A/cm2. Such high current densities are conceivable when the traditional carbon fiber papers are replaced with perforated metal plates as the gas diffusion layer to enhance waste heat removal, and at the same time the relative humidity inside the fuel cell is kept below 100% by applying appropriate operating conditions as was found in previous one-dimensional modeling work. In the current paper, we applied a three-dimensional, multi-phase computational fluid dynamics model based on Ansys-CFX to obtain additional insight into the underlying physics. The calculated pressure drops are in very good agreement with previous one-dimensional modeling work, and the current densities in all case studies are in the order of 5–6 A/cm2, but different from the previous one-dimensional study, the results suggest that the relative humidity is very close to 100% throughout the entire channel length when the inlet relative humidity is 100%, ensuring best hydration cell conditions and hence best performance. Importantly, the model results suggest that fuel cell performance at a high current density in conjunction with relatively low stoichiometric flow ratios around 1.5–2 is possible. [ABSTRACT FROM AUTHOR]

Microgrids (MGs) are the new paradigm of decentralized networks of renewable energy sources, loads, and storage devices that can operate independently or in coordination with the primary grid, incorporating significant flexibility and supply reliability. To increase reliability, traditional individual MGs can be replaced by networked microgrids (NMGs), which are more dependable. However, when it comes to operation and control, they also pose challenges for cyber security and communication reliability. Denial of service (DoS) is a common danger to DC microgrids with advanced controllers that rely on active information exchanges and has been recorded as the most frequent cause of cyber incidents. It can disrupt data transmission, leading to ineffective control and system instability. This paper proposes digital twin (DT) technology as an integrated solution, with new, advanced analytics technology using machine learning and artificial intelligence to provide simulation capabilities to predict and estimate future states. By twinning the cyber-physical dynamics of NMGs using data-driven models, DoS attacks targeting cyber-layer agents will be detected and mitigated. A long short-term memory (LSTM) model data-driven digital twin approach for DoS attack detection and mitigation is implemented, tested, and evaluated. [ABSTRACT FROM AUTHOR]

Mineral oil is widely used as liquid insulation in high voltage equipment. Due to environmental considerations, recently natural esters have been considered as naturally friendly liquid insulation candidates for high voltage transformers. In this experiment, transformer insulation paper was subjected to get accelerated aging test with copper strip in natural ester in a hermeneutical heat-resistant glass bottle at temperatures of 120 °C and 150 °C for 336 h, 672 h and 1008 h. The experimental results of Fourier transform infrared spectroscopy (FTIR) showed that the intensity of the absorbance peak of the O-H functional group decreased with aging, while the intensity of the C-H and C=O functional group absorbance peaks have increased with aging and the intensity of the C-O functional group absorbance peak has a tendency to increase with aging. The energy dispersive X-ray spectroscopy (EDS) experimental results showed that the weight percent of the element C increased with aging and the weight percent of the element O has decreased with aging. The experimental results show a good correlation between the degree of polymerization (DP) and the weight percent of O element. This indicates that EDS may be used as a new method for estimating the DP of transformer insulation paper. [ABSTRACT FROM AUTHOR]

The increasing global water pollution leads to the need for urgent development of rapid and accurate water quality monitoring methods. Microbial fuel cells (MFCs) have emerged as real-time biosensors for biochemical oxygen demand (BOD), but they grapple with several challenges, including issues related to reproducibility, operational stability, and cost-effectiveness. These challenges are substantially shaped by the selection of an appropriate air-breathing cathode. Previous studies indicated a critical influence of the cathode on both the enduring electrochemical performance of MFCs and the taxonomic diversity at the electroactive anode. However, the effect of different gas diffusion electrodes (GDE) on 3D-printed single-chamber MFCs for BOD biosensing application and its effect on the bioelectroactive anode was not investigated before. Our study focuses on comparing GDE cathode materials to enhance MFC performance for precise and rapid BOD analysis in wastewater. We examined for over 120 days two Pt-coated air-breathing cathodes with distinct carbonaceous gas diffusion layers (GDLs) and catalyst layers (CLs): cost-effective carbon paper (CP) with hand-coated CL and more expensive woven carbon cloth (CC) with CL pre-applied by the supplier. The results show significant differences in electrochemical characteristics and anodic biofilm composition between MFCs with CP and CC GDE cathodes. CP-MFCs exhibited lower sensitivity (16.6 C L mg−1 m−2) and a narrower dynamic range (25 to 600 mg L−1), attributed to biofouling-related degradation of the GDE. In contrast, CC-MFCs demonstrated superior performance with higher sensitivity (37.6 C L mg−1 m−2) and a broader dynamic range (25 to 800 mg L−1). In conclusion, our study underscores the pivotal role of cathode selection in 3D-printed MFC biosensors, influencing anodic biofilm enrichment time and overall BOD assessment performance. We recommend the use of cost-effective CP GDL with hand-coated CL for short-term MFC biosensor applications, while advocating for CC GDL supplied with CL as the preferred choice for long-term sensing implementations with enduring reliability. [ABSTRACT FROM AUTHOR]

This paper presents the influence of superconducting tape insulation on the recovery time of superconducting fault current limiters. The analysis is based on the experimental results of short-circuit tests. The reduction in the thermal and dynamic effects of the passage of a fault current can be achieved by limiting the short-circuit time and the value of the surge current. An ideal fault current limiter is required to have almost zero impedance at operating currents and significant impedance at fault conditions. A superconducting fault current limiter (SFCL) meets these requirements under certain conditions. The recovery time—a very important parameter—shows the ability of the limiter to return to the superconducting state to be ready to limit the subsequent short circuit. The experimental results show that the recovery time can be significantly reduced with the application of thin-film insulation and an appropriate design of the conduction cooling of the HTS tape. [ABSTRACT FROM AUTHOR]

Mass-impregnated (MI) cables have been used for many years as cables in high-voltage direct current (HVDC) systems. In line commutated converter (LCC) HVDC systems, polarity reversal for power flow control can induce significant electrical stress on MI cables. Furthermore, the mass oil and kraft paper comprising the impregnated insulation have significantly different coefficients of thermal expansion. Load fluctuations in the cable lead to expansion and contraction of the mass, creating pressure within the insulation and causing redistribution of the impregnant. During this process, shrinkage cavities can form within the butt gaps. Since the dielectric strength of the cavities is lower than that of the surrounding impregnation, cavitation phenomena in impregnated paper insulation are considered a factor in degrading insulation performance. Consequently, this study analyzes the electrical conductivity of thermally aged materials and investigates the transient electric field characteristics within the cable. Additionally, it closely analyzes the formation and dissolution of cavities in MI cables during polarity reversal based on a numerical model of pressure behavior in porous media. The conductivity of the impregnated paper indicates that it has excellent resistance to thermal degradation. Simulation results for various load conditions highlight that the interval of load-off time and the magnitude of internal pressure significantly influence the cavitation phenomenon. Lastly, the study proposes stable system operation methods to prevent cavitation in MI cables. [ABSTRACT FROM AUTHOR]

Breakdown strength is an important electrical property of insulating paper. Oil-impregnated paper of various aging states was prepared. Its breakdown voltage was then measured at pulsating direct current (DC) voltage with various ripple factors, and alternating current (AC) and DC voltage for comparison, respectively. The AC breakdown voltage is the smallest, and pulsating DC (r = 1/5) breakdown voltage is the greatest before the paper reaches its end of life. A dielectric model was adopted to investigate the difference in magnitude of breakdown voltage at different voltage waveforms. Meanwhile, it was found that breakdown voltage fluctuated and even increased occasionally during the thermal aging process, and a somewhat opposite changing tendency versus aging time was observed for breakdown voltage at DC voltage and pulsating DC voltage with small ripple factors (r = 1/5 and 1/3), compared with AC voltage. The degree of polymerization (DP) and moisture content of the paper were measured, and the characteristics of the pores and cracks of the paper were obtained to investigate the possible influencing factors of breakdown voltage at different aging states. The results showed that the moisture content, oil absorption ability associated with pores and cracks of paper, and the damage to paper structure all contributed to the variation of the breakdown voltage versus aging time, while the importance of their influence differed as the aging state of paper varied. [ABSTRACT FROM AUTHOR]

Heat pumps have the potential for several applications across various industrial sectors, showcasing significant promise, especially in sectors such as pulp and paper, food and beverage, chemical, non-metallic minerals, and machinery. Envisioning the near future, there is confidence that heat pumps can achieve temperatures above 200 °C, offering substantial potential for utilization in these sectors. Nevertheless, a crucial aspect for the advancement of high-temperature heat pumps is the selection of the fluid. Fluid selection involves considerations of both thermodynamic efficiency and environmental impact, requiring fluids with zero ODP, negligible GWP, and no PFAS. Moreover, it is essential to consider the risks to human health associated with a specific fluid. Despite extensive research, particularly in the realm of vapour compression heat pumps, choosing the most suitable working fluid for these applications is a complex undertaking. Therefore, this paper conducts a theoretical analysis to evaluate potential fluids with suitable thermodynamic properties for high-temperature heat pumps (HTHPs). The comparative results gleaned from this study provide valuable insights for the comprehensive analysis of fluids, showing promise within temperature ranges dictated by specific applications. The metrics employed in the comparison emphasise the merits of fluids in terms of the overall performance, dimensions, and operating ranges of applicable compressor, heat exchange capacity, transport properties, and safety. One noteworthy finding from the analysis is that maintaining a constant HTHP lift (at 40 K) results in having the highest COP across all fluids when the condensing temperature ranges between 85% and 90% of their respective critical temperatures. According to the results of the analysis, natural fluids, including water and alcohols like ethanol or methanol, emerge as particularly compelling candidates. [ABSTRACT FROM AUTHOR]

This paper analyzes the digital signal processing techniques and estimates induction motor (IM) rotational speed operating in stationary or non-stationary conditions. Rotor slot harmonics present in the stator current waveform are used to estimate the induction motor speed with a given or identified rotor slot numbers. This paper's contribution is the following: First, zoom improved short-time Chirp-Z transform is used to find supply frequency and the rotor slot harmonic frequency to improve the estimation accuracy without increasing computing complexity. Second, a technique is described that can be used to determine whether or not a motor can generate principal slot harmonics (PSH). Finally, an algorithm is designed to figure out the perfect window length and estimate the motors' speed. This proposed technique was investigated when the motor was fed by an inverter-fed supply driving a variable load and operating in non-stationary conditions. Experimental test results on 5.5 kW and 22 kW induction motors have confirmed the correctness of this method. [ABSTRACT FROM AUTHOR]

Anaerobic digestion (AD) of food waste (FW) is considered an environmentally sustainable process that can divert the disposal of FW to landfill and prevent greenhouse gas (GHG) emissions in managing the FW. Although several studies have attempted to demonstrate the AD of FW, low methane yields and a high incidence of process instability have been reported due to the rapid generation and accumulation of volatile fatty acids (VFAs). This paper reviews the recent research and development with high variation in FW composition, such as the carbon-to-nitrogen (C/N) ratio and, consequently, the effect of its physicochemical composition on process performance and methane yields. The paper highlights the significance of optimizing the anaerobic co-digestion (AcoD) of FW with carbon-rich substrates such as garden waste (GW) and/or the addition of trace elements as strategies that can improve the process performance and methane yields from FW. This review focuses on the factors effecting the feasibility of food organics and garden organics (FOGO) as a substrate for methane production. The review also critically analyses the prospects of enhancement of biomethane yield by optimizations of the impactful parameters. The progress in research related to these methods and identifying existing limitations to efficient AD of FOGO are the key findings of this review. This review also assesses the impact of nanotechnology on the process performance of the digester. The integration of FO and GO in AD processes has demonstrated enhanced biogas yields, improved process stability, and better waste management outcomes compared to the digestion of either substrate alone. Despite these advantages, challenges such as feedstock variability, process optimization, and the need for advanced pretreatment methods remain. Addressing these issues through continued research and technological innovations will be crucial for maximizing the efficiency and scalability of AD systems. Moreover, the economic feasibility and policy frameworks supporting AD need further development to promote broader adoption. [ABSTRACT FROM AUTHOR]

This paper proposes firstly a Second Order Sliding Mode Control (SOSMC) based on a Super Twisting Algorithm (STA) (SOSMC-STA) combined with a Direct Field-Oriented Control (DFOC) strategy of a Five-Phase Induction Motor (FPIM). The SOSMC-STA is suggested for overcoming the shortcomings of the Proportional Integral Controller (PIC) and the Conventional Sliding Mode Controller (CSMC). Indeed, the main limitations of the PIC are the slower speed response, the tuning difficulty of its parameters, and the sensitivity to changes in system parameters, including variations in process dynamics, load changes, or changes in setpoint. It is also limited to linear systems. Regarding the CSMC technique, its limitation is the chattering phenomenon, characterized by the rapid switching of the control signal. This phenomenon includes high-frequency oscillations which induce wear and tear on mechanical systems, adversely affecting performance. Secondly, this paper also proposes a Loss Model Controller (LMC) for FPIM energy optimization. Thus, the suggested LMC chooses the optimal flux magnitude required by the FPIM for each applied load torque, which consequently reduces the losses and the FPIM efficiency. The performance of the optimized DFOC-SOSMC-STA based on the LMC is verified using numerical simulation under the Matlab environment. The analysis of the simulation results shows that the DFOC-SOSMC-STA guarantees a high dynamic response, chattering reduction, good precision, and robustness in case of external load or parameter disturbances. Moreover, the DFOC-SOSMC-STA, combined with the LMC, reduces losses and increases efficiency. [ABSTRACT FROM AUTHOR]

In the ongoing debate about the feasibility of enforcing a transition to decentralized energy conversion systems, arguments are often presented that lack scientific rigor. Granted, the issue is multi-faceted and fundamentally multi-disciplinary, and possible solutions strongly depend on the selection of location as well as on local climate and demographics. Furthermore, decentralizing the final energy distribution leads to potential socio-economic considerations that involve value judgements. However, the most serious problem is that media have appropriated the topic and are often publishing opinion papers authored by non-specialists and even by representatives of interest groups. The present paper proposes an approach that is innovative on two counts: first, it treats "final energy" as any other commodity and therefore expands the field of investigation to the problems arising from the decentralization of a generic production line or technological chain; second, it argues that a method solidly rooted in Thermodynamics, the Extended Exergy Accounting, may be used to quantify the total amount of primary exergy resources requested by a decentralized strategy (as opposed to a centralized one), so that a comparison can be performed and discussed on a rational, unbiased and scientific basis. This is an introductory paper that reports some theoretical results of the method: realistic applications are perforce excluded because the idea is that the procedure must be drafted in such a way to be applicable to different socio-economic scenarios and locations and to remain valid under a broad range of boundary conditions. [ABSTRACT FROM AUTHOR]

Accurate power load forecasting can provide crucial insights for power system scheduling and energy planning. In this paper, to address the problem of low accuracy of power load prediction, we propose a method that combines secondary data cleaning and adaptive variational mode decomposition (VMD), convolutional neural networks (CNN), bi-directional long short-term memory (BILSTM), and adding attention mechanism (AM). The Inner Mongolia electricity load data were first cleaned use the K-means algorithm, and then further refined with the density-based spatial clustering of applications with the noise (DBSCAN) algorithm. Subsequently, the parameters of the VMD algorithm were optimized using a multi-strategy Cubic-T dung beetle optimization algorithm (CTDBO), after which the VMD algorithm was employed to decompose the twice-cleaned load sequences into a number of intrinsic mode functions (IMFs) with different frequencies. These IMFs were then used as inputs to the CNN-BILSTM-Attention model. In this model, a CNN is used for feature extraction, BILSTM for extracting information from the load sequence, and AM for assigning different weights to different features to optimize the prediction results. It is proved experimentally that the model proposed in this paper achieves the highest prediction accuracy and robustness compared to other models and exhibits high stability across different time periods. [ABSTRACT FROM AUTHOR]

To address the global warming issue, China is prioritizing the development of clean energy sources such as wind and solar power under its "dual carbon target". However, the expansion of these resources is constrained by their intermittency and the spatial and temporal distribution of wind and solar energy. This paper systematically reviews the evolution of wind and solar energy reserves, their development potential, and their current status in China from a geographical perspective. In conjunction with existing research, this paper anticipates future exploration in the realm of wind–solar complementary development or multi-energy complementary development, viewed through the lens of resource quantity. The anticipated findings are intended to furnish a theoretical foundation for further studies on the development and utilization of wind and solar energy resources within China. [ABSTRACT FROM AUTHOR]

The integration of the Internet of Things (IoT) with renewable energy technologies is revolutionizing modern power systems by enhancing efficiency, reliability, and sustainability. This paper examines the role of the IoT in optimizing the integration and management of renewable energy sources, such as solar and wind power, into the electrical grid. The IoT enables real-time monitoring, data analysis, and automation, facilitating advanced load management, demand response, and energy storage solutions. Key advancements in IoT technologies, including smart grids and energy management systems, are discussed, highlighting their impact on improving grid stability and promoting the use of renewable energy. The paper also finds some challenges such as data security, privacy, and the need for standardized communication protocols. Furthermore, it finds how the IoT optimizes electric vehicle performance through advanced battery management, real-time energy consumption monitoring, and improved interaction with the electrical grid. Future research directions emphasize the potential of the IoT to further enhance renewable energy integration through artificial intelligence and machine learning, driving the transition towards a more sustainable and resilient energy future. [ABSTRACT FROM AUTHOR]

In recent years, global efforts towards a future with sustainable energy have intensified the development of renewable energy sources (RESs) such as offshore wind, solar photovoltaics (PVs), hydro, and geothermal. Concurrently, green hydrogen, produced via water electrolysis using these RESs, has been recognized as a promising solution to decarbonizing traditionally hard-to-abate sectors. Furthermore, hydrogen storage provides a long-duration energy storage approach to managing the intermittency of RESs, which ensures a reliable and stable electricity supply and supports electric grid operations with ancillary services like frequency and voltage regulation. Despite significant progress, the hydrogen economy remains nascent, with ongoing developments and persistent uncertainties in economic, technological, and regulatory aspects. This paper provides a comprehensive review of the green hydrogen value chain, encompassing production, transportation logistics, storage methodologies, and end-use applications, while identifying key research gaps. Particular emphasis is placed on the integration of green hydrogen into both grid-connected and islanded systems, with a focus on operational strategies to enhance grid resilience and efficiency over both the long and short terms. Moreover, this paper draws on global case studies from pioneering green hydrogen projects to inform strategies that can accelerate the adoption and large-scale deployment of green hydrogen technologies across diverse sectors and geographies. [ABSTRACT FROM AUTHOR]

Geothermal energy is a unique energy source in the energy policy mix that would help the clean energy transition and energy independence, supporting the energy needs in heating and electricity. Although there have been studies on the opportunities and challenges of renewable energy, this paper is the first paper that concentrates on geothermal energy for three distinct countries, Italy, Belgium, and Iceland, for the first time. Using semi-structured interviews that will cover the stakeholders representing the quadruple helix (academia, citizens, policymakers, and industry), this paper aims to find the unique and common opportunities and barriers the geothermal sector has. Shared challenges include financial barriers, regulatory complexities, environmental issues, and the need for improvement in the social acceptability of geothermal energy. Despite these challenges, geothermal energy, a promising energy source for clean transition, could create opportunities like improved household welfare through combined uses in district heating and electricity and have the potential to generate employment opportunities. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources (RES) into smart grids has been considered crucial for advancing towards a sustainable and resilient energy infrastructure. Their integration is vital for achieving energy sustainability among all clean energy sources, including wind, solar, and hydropower. This review paper provides a thoughtful analysis of the current status of the smart grid, focusing on integrating various RES, such as wind and solar, into the smart grid. This review highlights the significant role of RES in reducing greenhouse gas emissions and reducing traditional fossil fuel reliability, thereby contributing to environmental sustainability and empowering energy security. Moreover, key advancements in smart grid technologies, such as Advanced Metering Infrastructure (AMI), Distributed Control Systems (DCS), and Supervisory Control and Data Acquisition (SCADA) systems, are explored to clarify the related topics to the smart grid. The usage of various technologies enhances grid reliability, efficiency, and resilience are introduced. This paper also investigates the application of Machine Learning (ML) techniques in energy management optimization within smart grids with the usage of various optimization techniques. The findings emphasize the transformative impact of integrating RES and advanced smart grid technologies alongside the need for continued innovation and supportive policy frameworks to achieve a sustainable energy future. [ABSTRACT FROM AUTHOR]

In the context of rapid growth in renewable energy installations and increasingly severe consumption issues, this paper designs a 100% green electricity supplied zero-carbon integrated energy station. It aims to analyze its configuration focusing on the following three core features: zero carbon emissions, 100% green electricity supply, and a centralized–distributed system structure. It discusses equipment selection and provides models for configuring upstream green electricity resources, power generation, energy storage, transformer, and energy conversion. The study examines the synergy between lithium-ion battery storage and modular molten salt thermal storage, along with the virtual energy storage characteristics formed by thermal load inertia, supported by mathematical models. Based on the data from a green electricity system in an Eastern Chinese city and typical load profiles, the paper validates a specific configuration for a 100% green electricity supplied zero-carbon integrated energy station, confirming model accuracy and calculating the required scale of upstream green electricity resources. It proves that establishing an electro-thermal storage synergy system is crucial for addressing the significant fluctuations in renewable energy output. It also argues that leveraging thermal load inertia to create virtual storage can reduce the investment in energy storage system construction. [ABSTRACT FROM AUTHOR]

The use of mobile robots in substations improves maintenance efficiency and ensures the personal safety of staff working at substations, which is a trend in the development of technologies. Strong electric and solid magnetic fields around high-voltage equipment in substations may lead to the breakdown and failure of inspection devices. Therefore, safe operation range measurement and coordinated planning are key factors in ensuring the safe operation of substations. This paper first summarizes the current developments that are occurring in the field of fixed and mobile safe operating range sensing methods for substations, such as ultra-wideband technology, the two-way time flight method, and deep learning image processing algorithms. Secondly, this paper introduces path-planning algorithms based on safety range sensing and analyzes the adaptability of global search methods based on a priori information, local planning algorithms, and sensor information in substation scenarios. Finally, in view of the limitations of the existing range awareness and path-planning methods, we investigate the problems that occur in the dynamic changes in equipment safety zones and the frequent switching of operation scenarios in substations. Furthermore, we explore a new type of barrier and its automatic arrangement system to improve the performance of distance control and path planning in substation scenarios. [ABSTRACT FROM AUTHOR]

This paper reviews sintered silver (s-Ag) die-attach materials for wide band gap (WBG) semiconductor packaging. WBG devices that die-attach with s-Ag have attracted a lot of attention owing to their low energy loss and high temperature operation capabilities. For their practical operation, a reliability design should be established based on the failure of physics of the s-Ag die layer. This paper first focuses on the material characteristics of the s-Ag and tensile mechanical properties. Then, the s-Ag die-attach reliability is assessed with high-temperature storage, power cycling, and thermal shock tests. Each fracture mode was discussed by considering both the fracture surface analysis results and its mechanical properties. Finally, the effective reliability design parameters of the s-Ag die layer are introduced. [ABSTRACT FROM AUTHOR]

The widespread use of static converters for controlling electrical machines and the concern for electrical power quality in industrial environments provide an opportunity for utilizing these devices to enhance the power quality. In this context, this work presents a back-to-back converter model for driving induction machines. The converter is designed to correct the power factor of the point common coupling (PCC), compensate for harmonic currents (acting as an active filter), and withstand voltage sags. The necessary control system models were developed, and an alternative implementation for these functions in the converter was proposed. The results demonstrate the technical feasibility of this solution, as the converter operated within its nominal limits by compensating for harmonics and reactive power. Moreover, the equipment showed resilience to severe voltage sags. The contribution of this paper focuses on the multifunctionality of the frequency converter for driving induction machines. It emphasizes the advantage of the inverter in improving power quality in industrial environments through reactive power compensation and harmonic current compensation, thus functioning as an active power filter. Additionally, it is worth highlighting its ability to handle voltage dips. In this regard, this paper contributes by providing an operational strategy for driving the induction machine during such transients. [ABSTRACT FROM AUTHOR]