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Thermal protection of a flange is critical for preventing tower icing and collapse of wind turbines (WTs) in extremely cold weather. This study aims to develop a novel thermal protection system for the WTs flanges using an electrical heat-tracing element.

A three-dimensional model and the Poly-Hexacore mesh structure are used, and the fluid-solid coupling method was validated and then deployed to analyze the heat transfer and convection process. Intra-volumetric heat sources are applied to represent the heat generated by the heating element, and the dynamic boundary conditions are considered. The steady temperature and temperature uniformity of the flange are the assessment criteria for the thermal protection performance of the heating element.

Enlarging the heating area and increasing the heating power improved the flange's temperature and temperature uniformity. A heating power of 4.9 kW was suitable for engineering applications with the lowest temperature nonuniformity. Compared with continuous heating, the increased temperature nonuniformity was buffered, and the electrical power consumption was reduced by half using pulse heating. Pulse heating time intervals of 1, 3 and 4 h were determined for the spring, autumn and winter, respectively.

The originality of this study is to propose a novel electrical heat-tracing thermal protection system for the WTs flanges. The effect of different arrangements, heating powers and heating strategies was studied, by which the theoretical basis is provided for a stable and long-term utilization of the WT flange.

This paper aims to investigate the impact of combining grain-oriented electrical steel (GOES) grades on specific iron losses and the flux density distribution within a single-phase magnetic core.

This paper presents the results of finite-element method (FEM) simulations investigating the impact of mixing two different GOES grades on losses of a single-phase magnetic core. The authors used different models: a 3D model with a highly detailed geometry including both saturation and anisotropy, as well as a simplified 2D model to save computation time. The behavior of the flux distribution in the mixed magnetic core is analyzed. Finally, the results from the numerical simulations are compared with experimental results.

The specific iron losses of a mixed magnetic core exhibit a nonlinear decrease with respect to the GOES grade with the lowest losses. Analyzing the magnetic core behavior using 2D and 3D FEM shows that the rolling direction of the GOES grades plays a critical role on the nonlinearity variation of the specific losses.

The novelty of this research lies in achieving an optimum trade-off between the manufacturing cost and the core efficiency by combining conventional and high-performance GOES grade in a single-phase magnetic core.

The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

This paper aims to study the possibility of electroplating copper coatings on chemically and chemical-galvanically nickel-plated acrylic fibers, to be further processed into yarn, fabrics, knitwear and nonwoven materials.

Electrically conductive fibers with different copper contents have been obtained, and the effect of electrolyte pH, its composition, current strength at the first and second cathodes, as well as the metallization time on the electrophysical, physical and mechanical properties of copper-containing fibers, has been studied.

The studies have shown that with an increase in the copper content, the electrical conductivity, the uniformity of the coating and the uniformity of the electrophysical properties (for chemical-galvanically nickel-plated fiber) increase. In the case of copper plating of chemically nickel-plated fiber, the coefficient of variation in electrical resistance increases with increasing plating time, even though the copper content increases, and the coefficient of variation in copper content and electrical resistance decreases. The physical and mechanical properties of copper-containing fibers differ slightly from the original (subjected to copper plating) and industrial Nitron fibers. With copper plating, the strength of the fiber practically does not decrease, and the elongation decreases somewhat, compared with the mass-produced Nitron fiber.

The physical and mechanical properties of copper-containing fibers are quite high, which makes it possible to be successfully further processed into yarn, fabrics, knitwear and nonwoven materials.

This study aims to understand the current production scenario emphasizing the significance of green manufacturing in achieving economic and environmental sustainability goals to fulfil future needs; to determine the viability of particular strategies and actions performed to increase the process efficiency of electrical discharge machining; and to uphold the values of sustainability in the nonconventional manufacturing sector and to identify future works in this regard.

A thorough analysis of numerous experimental studies and findings is conducted. This prominent nontraditional machining process’s potential machinability and sustainability challenges are discussed, along with the current research to alleviate them. The focus is placed on modifications to the dielectric fluid, choosing affordable substitutes and treating consumable tool electrodes.

Trans-esterified vegetable oils, which are biodegradable and can be used as a substitute for conventional dielectric fluids, provide pollution-free machining with enhanced surface finish and material removal rates. Modifying the dielectric fluid with specific nanomaterials could increase the machining rate and demonstrate a decrease in machining flaws such as micropores, globules and microcracks. Tool electrodes subjected to cryogenic treatment have shown reduced tool metal consumption and downtime for the setup.

The findings suggested eco-friendly machining techniques and optimized control settings that reduce energy consumption, lowering operating expenses and carbon footprints. Using eco-friendly dielectrics, including vegetable oils or biodegradable dielectric fluids, might lessen the adverse effects of the electrical discharge machine operations on the environment. Adopting sustainable practices might enhance a business’s reputation with the public, shareholders and clients because sustainability is becoming increasingly significant across various industries.

A detailed general review of green nontraditional electrical discharge machining process is provided, from high-quality indexed journals. The findings and results contemplated in this review paper can lead the research community to collectively apply it in sustainable techniques to enhance machinability and reduce environmental effects.

The ionization of the air surrounding the phase conductor in high-voltage transmission lines results in a phenomenon known as the Corona effect. To avoid this, Corona rings are used to dampen the electric field imposed on the insulator. The purpose of this study is to present a fast and intelligent surrogate model for determination of the electric field imposed on the surface of a 120 kV composite insulator, in presence of the Corona ring.

Usually, the structural design parameters of the Corona ring are selected through an optimization procedure combined with some numerical simulations such as finite element method (FEM). These methods are slow and computationally expensive and thus, extremely reducing the speed of optimization problems. In this paper, a novel surrogate model was proposed that could calculate the maximum electric field imposed on a ceramic insulator in a 120 kV line. The surrogate model was created based on the different scenarios of height, radius and inner radius of the Corona ring, as the inputs of the model, while the maximum electric field on the body of the insulator was considered as the output.

The proposed model was based on artificial intelligence techniques that have high accuracy and low computational time. Three methods were used here to develop the AI-based surrogate model, namely, Cascade forward neural network (CFNN), support vector regression and K-nearest neighbors regression. The results indicated that the CFNN has the highest accuracy among these methods with 99.81% R-squared and only 0.045468 root mean squared error while the testing time is less than 10 ms.

To the best of the authors’ knowledge, for the first time, a surrogate method is proposed for the prediction of the maximum electric field imposed on the high voltage insulators in the presence Corona ring which is faster than any conventional finite element method.

To prevent the coil from burning or getting damaged, it is necessary to estimate the duration of its operation as long as its temperature does not exceed the permissible limit. This paper aims to investigate the effect of switching on the thermal behavior of impregnated and nonimpregnated windings. Also, the safe operating time for each winding is determined.

The power loss of the winding is expressed as a function of the winding specifications. Using homogenization techniques, the equivalent thermal properties for the homogenized winding are calculated and used in a proposed thermal equivalent circuit for winding modeling and analysis. The validity and accuracy of the proposed model are determined by comparing its analysis results and simulation and measurement results.

The results show that copper windings have better thermal behavior and lower temperature compared to aluminum windings. On the other hand, by impregnating or increasing the packing factor of the winding, the thermal behavior is improved. Also, by choosing the right duty cycle for the winding current source, it is possible to prevent the burning or damage of the winding and increase its lifespan. Comparing the measurement results with the analysis results shows that the proposed equivalent circuit has an error of less than 4% in the calculation of the winding center temperature.

In this paper, the effect of temperature on the electrical resistance of the coil is ignored. Also, rectangular wires were not investigated. Research in these topics are considered as future work.

By calculating the thermal time constant of the winding, its safe operation time can be calculated so that its temperature does not exceed the tolerable value (150 °C). The proposed method analyzes both impregnated and nonimpregnated windings with various schemes. It investigates the effects of switching on their thermal behavior. Additionally, it determines the safe operating time for each type of winding.

Electrical characteristics of transformer oil (TO) have been studied during normal and thermal aging conditions. In this paper, breakdown voltage (BDV), partial discharge (PD), heat transfer results and the physical mechanisms considering the impact of varying the diameter of Al₂O₃ nanoparticles (NPs) have been investigated. Different quantities of the two sizes of Al₂O₃ were added to the oil using a two-step method to determine the positive effect of NPs on the electrical and thermal properties of TO. Finally, the physical mechanisms related to the obtained experimental results have been performed.

The implementation of nanoparticles in this paper was provided by US Research Nanomaterials, Inc., USA. The provided Al₂O₃ NPs have an average particle size of 20–80 nm and a specific surface area of 138 and 58 m²/g, respectively, which have a purity of over 99%. Thermal aging has been done. The IEC 60156 standard has been implemented to calculate the BDV, and a 500-mL volume test cell (Apar TO 1020) has been used. PD test is performed according to Standard IEC 60343, and a JDEVS-PDMA 300 device was used for this test.

BDV tests indicate that 20 nm Al₂O₃ is more effective at improving BDV than 80 nm Al₂O₃, with an improvement of 113% compared to 99% for the latter. The analysis of Weibull probability at BDV indicates that 20 nm Al₂O₃ performs better, with improvements of 141%, 125% and 112% at probabilities of 1, 10 and 50%, respectively. The results of the PD tests using the PDPR pattern also show that 20 nm Al₂O₃ is superior. For the heat transfer test, 0.05 g/L of both diameters were used to ensure fair conditions, and again, the advantage was with 20 nm Al₂O₃ (23% vs 18%).

The effect of Al₂O₃ NP diameter (20 and 80 nm) on various properties of virgin and aged TO has been investigated experimentally in this paper to examine the effect of proposed NP on electrical improvement of TO.

This study aims to investigate the feasibility of proposed microgrid (MG) that comprises photovoltaic, wind turbines, battery energy storage and diesel generator to supply a residential building in Grindelwald which is chosen as the test location.

Three operational configurations were used to run the proposed MG. In the first configuration, the electric energy can be vended and procured utterly between the main-grid and MG. In the second configuration, the energy trade was performed within 15 kWh as the maximum allowable limit of energy to purchase and sell. In the third configuration, the system performance in the stand-alone operation mode was investigated. A whale optimization technique is used to determine the optimal size of MG in all proposed configurations. The cost of energy (COE) and other measures are used to evaluate the system performance.

The obtained results revealed that the first configuration is the most beneficial with COE of 0.253$/KWh and reliable 100%. Furthermore, the whale optimization algorithm is sufficiently feasible as compared to other techniques to apply in the applications of MG.

The value of the proposed research is to investigate to what extend the integration between MG and main-grid is beneficial economically and technically. As opposed to previous research studies that have focused predominantly only on the optimal size of MG.

Across the USA, local municipalities and providers struggle to reliably supply water and electricity when faced with severe weather events induced by climate change. Previous research suggests those at higher risk for experiencing the detrimental effects of climate change have higher climate-related concerns. Additionally, research demonstrates variation in trust in institutions and perceptions of environmental justice along racial lines, which can influence concern for access to resources. Informed by this research, the authors ask two questions: how do Oklahomans’ trust in institutions, environmental justice perceptions and global climate change risk perceptions differ based on race, and how do these factors influence concern for water and electrical infrastructure? The purpose of this study is to better understand Oklahomans’ trust in information from institutions, environmental justice perceptions, global climate change risk perceptions and concern for water and electrical infrastructure.

This study uses a series of nested regression models to analyze the survey responses of 2,687 Oklahoman adults. The data were pulled from Wave 3 of the Oklahoma Meso-scale Integrated Socio-geographic Network survey, which is part of the National Science Foundation EPSCoR S3OK project.

The findings demonstrate the complex interplay of riskscapes – or risk landscapes – that encompass institutional trust, perceptions of environmental justice, climate change and infrastructure in Oklahoma. The authors find evidence that education and income are better predictors of institutional trust and environmental justice than race among our respondents. Political ideology emerges as a significant predictor across all hypotheses.

This study contributes to the understanding of complex dynamics involving race, perceptions of environmental justice, trust in information from institutions, risk perceptions of climate change and concerns for water and electrical infrastructure in Oklahoma.