Search Results (3,850)

Corona discharge at the tip of buildings in a thunderstorm environment is an important factor causing changes in the near-ground electric field, but the influence of a quadratic growth law and quantitative research on the parameters is still rare. Therefore, based on the three-dimensional corona discharge model, this paper studies the influence of positive and negative symmetrical triangular wave electric fields with different amplitudes on the corona discharge of an independent lightning rod. Studies have shown that the corona current is synchronized with the peak of the background electric field. Studies have shown that the corona current is synchronized with the peak of the background electric field. When the polarity of the electric field changes from positive to negative, the positive charge accumulated in the positive half-cycle promotes the subsequent negative corona, so the negative corona starts in advance when the polarity reverses. Compared with unipolar discharge, the amplitude of the negative current and the number of negative charges have significantly improved. However, due to the counteraction of neutralization between positive and negative charges, the total corona charge is at a low level, which shows a net negative polarity result. The corona current and the amount of charge increase nonlinearly with an increase in the background electric field amplitude. Under the symmetrical triangular wave electric field, the quantitative fitting relationship between the peak value of the negative corona current in the second half-cycle and the amount of charge is established for the 5 m high independent lightning rod, which is I⁻ = −0.0532 − 0.153$E$ − 0.0682 $E^2$, Q⁻ = −3.18 × 10⁻³ + 7.762 × 10⁻⁴E − 4.671 × 10⁻⁵$E^2$, respectively. The increase in the background electric field amplitude will aggravate the disturbance of the corona discharge to the near-surface electric field. When the direction of the electric field has reverted to zero, the existence of the space charge will lead to a significant change in the strength and polarity of the ground electric field. When the thunderstorm background electric field changes from positive to negative, the corona effect reverses the polarity of the ground electric field in advance, and the larger the peak value of the background electric field, the larger the advance. The corona interference mechanism revealed by this study can provide an important reference for correcting the electric field monitoring data and improving the accuracy of lightning warnings. Full article

Efficient thermal management of lithium-ion batteries is critical for the safety, performance, and longevity of electric vehicles. This work numerically investigates a battery thermal management system (BTMS) for a LiFePO₄ battery, featuring a liquid-cooling plate with novel droplet-shaped turbulators and coolant with different nanofluids. Computational Fluid Dynamics (CFD) simulations were employed to analyze the effects of cooling channel geometry, nanofluid type, nanoparticle volume fraction, coolant inlet velocity, and battery discharge rate on the system’s thermal performance and pressure drop. Results show that the droplet-shaped channel reduces the maximum battery temperature by 1.64 K compared to a conventional straight channel, owing to enhanced turbulence and larger heat-transfer area. Among different coolants, the 6% Cu–water nanofluid demonstrated the highest cooling effectiveness due to its superior thermal conductivity. To balance competing objectives, a multi-objective optimization using Response Surface Methodology (RSM) and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was performed. The optimal design was achieved with a coolant velocity of 0.097 m/s and a volume fraction of Cu nanoparticle of 3.85%, which maintained the maximum battery temperature of 299.7 K with a minimal pressure drop of 26.27 Pa at a 1.03 C discharge rate. These findings highlight that a BTMS combining droplet-shaped turbulators with a Cu–water nanofluid provides a highly effective and energy-efficient thermal management strategy. Full article

Freshwater scarcity is a major global issue faced by various regions, and the most common portable water sources globally are estuaries, canals, dams, lakes, and rivers. Existing water resources function as the best sinks for the frequent release of effluents from industrial and residential activities. This common practice often results in water pollution, a deterioration in marine biodiversity, and possible health risks for human populations. This study employed standard analytical methods in assessing the physicochemical and microbial characteristics of water samples collected from the Sundays River estuary in Eastern Cape Province (ECP), South Africa (SA). Microbiological assessment revealed that during the spring season, presumptive Escherichia coli (E. coli) colony counts were 1 cfu/100 mL, while total coliforms (TCs) and fecal coliforms (FCs) were recorded at 42.67 cfu/100 mL and 1 cfu/100 mL, respectively. In the summer season, fecal coliform (FC) counts reached 3.5 cfu/100 mL, while Enterococcus levels were higher, ranging up to 77.75 cfu/100 mL. Furthermore, the average standards of physicochemical parameters assessed in water obtained from both spring and summer seasons ranged as follows: pH (8.71–9.31), temperature (20.98–22.21 °C), turbidity (10–35.55 FNU), total alkalinity (22.25–94.00 mg/L), oxidation–reduction potential (ORP) (8.05–151.6 mV), electrical conductivity (EC) (13,915–40,260 uS/cm), salinity (8.07–25.78 psu), dissolved oxygen (DO) (6.79–7.39 mg/L), total dissolved solids (TDSs) (6960.6–20,125 mg/L), and biochemical oxygen demand (BOD) (0.11–2.94 mg/L). The levels of TDS, EC, turbidity, and salinity in the Sundays River estuary water exceeded the World Health Organization (WHO) guidelines of 2017, rendering the water unfit for even recreational purposes. Additionally, the bacterial levels identified in this study were above the values set by the South Africa Department of Water Affairs (SA-DWAF). The identified microorganisms are perceived as essential indicators of fecal contamination and have the potential to multiply in the environment. Possible pollution may be a result of various municipal effluents consistently discharged into the waterbody. Full article

Vacuum degree inside vacuum interrupter (VI) deteriorates due to cracks from long-term operation of VI, gas emitted from internal arc heat, leakage through the joint, etc. Partial discharge occurs between the two contacts inside the VI or between the contact and floating shield, which leads to dielectric breakdown and electrical accidents of high voltage apparatus. In this paper, the study on the vacuum degree monitoring of distribution class vacuum interrupter according to non-contact method of coupling capacitor based on partial discharge was performed. In order to monitor the partial discharge between two contacts inside VI with high accuracy, a partial discharge sensing electrode (PDDE) was designed using the 3D finite element method (FEM). In addition, after calculating the internal capacitance according to the structure and size characteristics inside VI, the capacity of the coupling capacitor to detect the signal was calculated. The partial discharge characteristics according to the vacuum degree were analyzed by applying PDDE and a coupling capacitor. As results, it was found that the partial discharge characteristics inside VI differ depending on the voltage type. In addition, it was confirmed that even if VI has the same internal structure and size, the partial discharge characteristics appear differently. Based on the experimental results, we proposed maintenance criteria for VI for each voltage type. Full article

Optimized dispatch of microgrids is crucial for improving the economic performance and long-term sustainability of modern low-carbon power systems. In particular, accurate economic dispatch modeling for battery energy storage systems (BESSs) is essential for properly evaluating the operational benefits and lifetime costs of microgrids. However, when both battery cycle aging and calendar aging are considered, the resulting scheduling model becomes highly nonlinear, high-dimensional, non-convex, and multimodal, which poses substantial challenges to conventional optimization methods. To alleviate the above problem, a symmetry-guided multi-strategy differential hybrid slime mold algorithm (MDHSMA) is introduced for the day-ahead economic dispatch of microgrids under a refined battery degradation framework. First, a chaotic bimodal mirrored Latin hypercube sampling strategy is designed to exploit symmetry during population initialization, thereby enhancing diversity and improving structured coverage of the search space. Second, a history-driven adaptive differential evolution mechanism is integrated to balance global exploration and local exploitation more effectively during the iterative search process. Third, a state-aware stagnation handling framework is incorporated to maintain population vitality and further improve convergence accuracy and robustness. MDHSMA is evaluated against 12 state-of-the-art optimizers on the CEC2017 and CEC2022 benchmark suites and two representative engineering optimization problems to verify its overall performance. In addition, it is applied to a microgrid case study with refined BESS degradation modeling. The results show that MDHSMA achieves the lowest comprehensive operating cost by effectively coordinating electricity arbitrage and battery life consumption. Moreover, it guides the energy storage system toward shallow charge–-discharge patterns, thereby mitigating accelerated degradation caused by excessive cycling. These results confirm the effectiveness and practical value of the proposed method for sustainable microgrid dispatch in complex nonconvex optimization scenarios. Full article

To address the application requirements of energy storage devices for new energy electric vehicles—including high energy density, high-power density, fast charging and discharging, and long-term cycling stability—traditional symmetric supercapacitors are often limited by low energy density and poor compatibility between the anode and cathode, making it difficult to meet the high-efficiency energy storage demands under the dynamic operating conditions of electric vehicles. This study focuses on the regulation of hierarchical thin-film structures and the innovative heterogeneous coating interface engineering with precise slurry coating and film-forming optimization and designs and fabricates NiCo₂O₄/NiFeO composite thin-film electrodes and Mn-doped porous carbon (Mn-PC) thin-film electrodes. The uniform, compact and stable coating formation on nickel foam substrates via controllable slurry coating facilitates the efficient integration of active materials and conductive supports. The electrode slurries were coated onto conductive nickel foam substrates, and high-performance aqueous supercapacitors were assembled using an asymmetric configuration. A systematic study was conducted covering material preparation, structural characterization, electrochemical testing, and full-device performance evaluation. Using techniques such as XRD, XPS, SEM, TEM, BET, and an electrochemical workstation, the study revealed the structure–activity relationships among material morphology, crystalline phases, pore structure, and electrochemical performance, elucidating the charge storage mechanisms of the composite electrode films and the principles of synergistic adaptation between the anode and cathode. The results indicate that NiCo₂O₄ nanowires decorated with in situ-grown NiFeO nanosheets to form a composite structure; when coated onto nickel foam, this forms a uniform, porous electrode film with a specific surface area of 171.3 m²/g, a specific capacitance as high as 1746 F/g at 1 A/g, and a capacity retention rate of 94.0% after 10,000 cycles. After coating and film formation, the Mn-PC anode introduced pseudocapacitive active sites through uniform Mn doping, resulting in a film electrode specific capacitance of 348 F/g and significantly improved rate and cycling performance. The assembled NiCo₂O₄/NiFeO//Mn-PC asymmetric supercapacitor exhibits a thin-film electrode specific capacitance of 153 F/g at 1 A/g, with a maximum energy density of 52 Wh/kg. Even at a power density of 9000 W/kg, it maintains 45 Wh/kg, and retains 89.5% of its capacity after 10,000 cycles, with overall performance outperforming most previously reported transition metal-based devices. This coating-engineered electrode fabrication strategy breaks through the interface mismatch and structural instability bottlenecks of traditional thin-film electrodes, providing a novel material system and an efficient coating assembly strategy for high-performance supercapacitor thin-film electrodes in new energy electric vehicles, and offers experimental evidence and technical references for the development and application of high-power energy storage coating devices for automotive use, as well as the innovative design of electrode coating engineering in energy storage fields. Full article

This study presents an optimized and comparative investigation of four intelligent energy management strategies—Proportional–Integral–Derivative (PID), Fuzzy Logic Control (FLC), Equivalent Consumption Minimization Strategy (ECMS), and Artificial Neural Network (ANN)—applied to a photovoltaic–fuel cell–battery hybrid electric vehicle (PV–FC–HEV). A high-fidelity MATLAB/Simulink model integrates a 6 kW proton-exchange membrane fuel cell (PEMFC), a 500 W photovoltaic subsystem with MPPT, and a lithium-ion battery (LiB) pack. While 1000 W/m² represents Standard Test Conditions (STC), the level of 400 W/m² was specifically selected to simulate average cloudy conditions common in urban driving environments, rather than standard NOCT (800 W/m²), to test the EMS’s robustness under significantly reduced PV support and stressed battery conditions (initial SOC = 30%). While surface contamination and the resulting performance degradation significantly impact real-world results, this study assumes a clean surface to establish an idealized performance baseline for the control algorithms. However, the authors acknowledge that contaminant accumulation is a key factor; future work will incorporate a degradation factor (e.g., a 10–15% efficiency penalty) to evaluate the reliability of these EMS strategies under actual operating conditions. ECMS achieved the lowest hydrogen consumption, saving up to 10 L compared with PID, while ANN maintained the most stable state of charge (SOC > 80%), minimizing deep discharge cycles and improving operational stability. FLC provided balanced operation under fluctuating irradiance. Overall, ANN offered the most harmonized energy flow and dynamic stability, whereas ECMS maximized fuel economy. The findings provide practical guidance for designing sustainable and intelligent control systems in next-generation hybrid electric vehicles. Full article

Tree contact discharge is a key contributing factor to wildfires caused by medium-voltage insulated conductors. Prolonged abrasion of the insulation layer by branches gradually creates weak points in the insulation. When subjected to lightning strikes, these areas are prone to forming lightning-induced pinholes, which can subsequently trigger partial discharge and even ignition. This study systematically investigates the discharge-induced ignition mechanism for 10 kV overhead insulated conductors in tree contact scenarios by establishing an experimental platform integrated with high-speed imaging, ultraviolet detection, and simulation methods. Three types of typical defects were set up in the experiments: complete insulation abrasion, lightning puncture holes accompanied by localized abrasion, and lightning puncture holes without abrasion. The development process and characteristics of different discharge forms were observed and analyzed. The results indicate that the tree contact discharge ignition mechanism can be categorized into two types: thermal accumulation and direct arcing. The former occurs when insulation abrasion or composite defects exist, where sustained partial discharge or a high-resistance current leads to gradual heat accumulation, resulting in an ignition delay lasting tens of seconds. The latter occurs when only small defects such as lightning puncture holes exist in the insulation layer. A concentrated arc forms due to gap breakdown under high voltage, leading to a millisecond-level ignition process. The study found that different discharge forms produce significantly distinct ablation and carbonization patterns on both the insulation layer and the branch surface, reflecting differences in energy transfer pathways. Simulation analysis further indicated that the thickness of the insulation layer affects the electric field distribution in the tree contact gap, with the initial discharge field strength decreasing as the thickness increases. This study provides experimental evidence and classification guidance for tree contact fault monitoring, insulation condition assessment, and wildfire prevention and control in medium-voltage distribution networks. Full article

External electricity supplementation for islanded microgrids at expressway service areas is often settled under tiered electricity pricing based on cumulative energy consumption, where marginal prices increase discontinuously once tier thresholds are exceeded. This mechanism reshapes battery dispatch behavior and may alter economically optimal storage sizing. This paper proposes a unified planning–-operation optimization framework for wind–PV–battery microgrids that jointly determines the storage capacity and hourly scheduling while enforcing power balance, battery state-of-charge dynamics, and tiered settlement costs. By introducing tier-wise energy allocation variables and tier cap constraints, the nonlinear settlement rule is reformulated into an equivalent piecewise-linear structure, leading to a mixed-integer linear programming (MILP) model that can be solved using standard optimization solvers. A season-weighted annualized case study using four typical seasonal days reveals critical cross-tier dispatch behaviors, where charging–discharging schedules shift near tier boundaries and external electricity purchases are actively suppressed from entering higher-priced tiers. The proposed framework quantifies the premium-avoidance value of storage and provides a practical decision support tool for premium risk-aware sizing and operation of islanded expressway service-area microgrids. Full article

Surface discharge-induced degradation poses a significant threat to the operational reliability of high-voltage insulation systems. This research investigates the dielectric endurance of polyester-based nanocomposites reinforced with seven distinct nano-additives: iron oxide (Fe₃O₄), copper oxide (CuO), titanium oxide (TiO₂), aluminum oxide (Al₂O₃), silicon dioxide (SiO₂), zinc borate (ZnB) and graphene oxide (GO). Specimens were fabricated at 0.5% and 0.75% weight concentrations and subjected to constant AC electrical stress of 4.5 kV at 50 Hz until failure using the first-plane tracking method. To accurately monitor the aging process, a sophisticated signal processing framework involving Hankel-matrix-enhanced Robust Principal Component Analysis (RPCA) was developed to extract high-frequency discharge features from captured leakage current signals. The degradation characteristics were quantified using various statistical metrics, including Kurtosis, RMS and Burst Discharge Index (BDI). Experimental findings demonstrate that the incorporation of nanoparticles significantly extends the time-to-failure compared to neat polyester, although the effectiveness is highly dependent on both additive type and concentration. At 0.5 wt.%, ZnB exhibited the superior performance in delaying carbonized track formation. However, at 0.75 wt.%, Al₂O₃ emerged as the most effective additive, achieving a maximum endurance time of 31.61 min. In contrast, certain additives like TiO₂ showed a performance decline at higher loadings, likely due to nanoparticle agglomeration. The Hankel-RPCA methodology successfully isolated discharge-specific signatures from background noise, establishing a strong correlation between signal features and material failure stages. This study confirms that the synergy between advanced nanomaterial modification and robust signal processing provides an effective diagnostic tool for monitoring insulation health, offering a vital pathway for the designing of high-performance dielectrics for real-world power system applications. Full article

Surface topography characterization is essential for evaluating the effects of texturing processes and for describing surface-dependent phenomena. Assessing the relationships between manufacturing, surface geometries, and functional properties requires, firstly, a detailed characterization of surfaces. Conventional parameters defined in ISO 25178-2 describe the statistical distribution of surface heights relative to the mean plane, as well as the arrangement, spacing, and directionality of surface features. They also include height and spatial descriptors, functional properties derived from the Abbott–Firestone curve, and characteristics of individual topographic features, such as peaks and valleys, including their shape, volume, and distribution. While these parameters provide a valuable description of the surface, they are not intrinsically multiscale and provide only a single aggregated descriptor of the surface. Therefore, multiscale parameters complement this description by capturing relative areas and area-scale fractal-like complexity across geometrically decomposed surface features over a range of scales from the nano and micro to the macro scale. The main objective of this study is to evaluate correlations between conventional and multiscale topographic parameters, based on surfaces produced by electrical discharge machining (EDM). The novelty of this study lies in the integrated analysis of correlations between conventional and multiscale parameters, enabling a more comprehensive framework for surface characterization. Full article

Efficient thermal management is critical for maintaining the safety, durability, and performance of lithium-ion batteries used in electric vehicles (EVs). In this study, a comprehensive numerical investigation is conducted to evaluate the heat transfer characteristics of mono- and hybrid-nanofluids in a microchannel-cooled lithium-ion battery module. A three-dimensional computational model of a 5S7P battery module composed of cylindrical 21700 cells is developed. Battery heat generation during 3C high discharge rate operation is predicted using the Newman-Tiedemann-Gu-Kim (NTGK) electrochemical model, while coolant flow and heat transfer are simulated using the governing conservation equations for mass, momentum, and energy. The cooling system consists of six liquid-cooling plates with circular microchannels. The performance of water-glycol (50/50) coolant is compared with several mono nanofluids of Al₂O₃ and Cu, and hybrid nanofluids of Al₂O₃-Cu, Al₂O₃-MWCNT, Al₂O₃-Graphene, Cu-MWCNT, and Cu-Graphene across multiple coolant flow rates from 1–5 LPM. The results demonstrate that nanofluids significantly enhance convective heat transfer and reduce battery temperature compared with the conventional water-glycol coolant. Among the investigated coolants, the Al₂O₃-Cu hybrid nanofluid (0.45–0.45%) operating at 1 LPM achieves the best overall thermo-hydraulic performance with a performance evaluation criterion (PEC) of 1.065. Further analysis of nanoparticle composition ratios shows that a Cu-dominant hybrid mixture (Al₂O₃-Cu: 0.27–0.63%) slightly improves the PEC to 1.0657, indicating marginally superior cooling performance. The findings highlight the potential of hybrid nanofluids as advanced coolants for microchannel-based battery thermal management systems in EVs, particularly under moderate coolant flow conditions. Full article

This study investigates the mechanism of cell death associated with discharge plasma treatment from the perspective of electrical energy injection, using equivalent circuit network analysis to represent cells, buffer solutions, and well plates as electrical components. Our analysis demonstrated that the observed cell death cannot be adequately explained by a One-Step Model, which assumes that cell death occurs when the total injected electrical energy simply reaches a specific threshold. Accordingly, we proposed a Two-Step Model that explicitly incorporates biological tolerance to external stimuli. In this model, a stimulus accumulates only when the instantaneous power exceeds a primary threshold, and cell death is induced only when this accumulated stimulus surpasses a secondary threshold of energy. The proposed Two-Step Model successfully reproduced the experimental cell death data. These findings suggest that plasma-induced cell death is not a simple physical destruction process governed solely by cumulative energy, but instead reflects a biologically regulated response characterized by a specific power-dependent tolerance. Consequently, this Two-Step Model could provide a theoretical foundation for future optimization of delivery conditions for macromolecules such as messenger RNA (mRNA). Full article

The Vehicle-to-Grid (V2G) technology is considered one of the best solutions for integrating renewable energy systems; however, most literature reports favorable economic results using synthetic data, without accounting for seasonal or market limitations. The current research presents the results of the MATLAB R2023b (Version 23.2, MathWorks, Natick, MA, USA) simulation of the 100-household energy community in Debrecen, Hungary, with 30 electric vehicles (EVs) using entirely simulation-based Lithium Iron Phosphate (LiFePO4) batteries, a simulation-based 150 kW solar photovoltaic (PV) system, and a simulation-based 200 kW wind power system, using real meteorological data for January 2024. The optimization of charging/discharging for electric vehicles was performed using a multi-objective genetic algorithm (GA) over 30 days at a 15 min time resolution, accounting for stochastic loads and temperature effects on battery degradation, with a sensitivity analysis of key parameters. The results of the optimized solution for the electric vehicle charging/discharging were unexpected: the total energy cost increased by 68.9% ($4337.65 to $7327.54), the peak demand increased by 266.2% (31.9 to 116.9 kW), the degradation cost was $479.63, the load factor was reduced from 0.847 to 0.722, and the SOC constraint was violated for 0.758% of measurements. The V2G is not economically viable under current Hungarian pricing and Central Europe winter conditions. Results are robust for varying parameters using sensitivity analysis and Pareto front tracing. The break-even point is achieved when ratios of peak-to-off-peak prices are above 3.5:1. Seasonal policies and market reforms are critical for V2G viability. Importantly, the influence of inherent design deficiencies in the optimization model on the reported results cannot be ruled out. Full article

Electric discharge cavitation is an effective method for water treatment that combines physical and chemical effects within a single process. It enables water disinfection, extraction acceleration, dispersion of solid particles, and enhancement of porous material permeability. Compared to conventional chemical treatment, it reduces the demand for reagents and minimizes secondary pollution. This new and developing technology significantly contributes to the preservation of natural aquatic ecosystems by providing a sustainable alternative to traditional decontamination methods, thereby reducing the overall anthropogenic pressure on the environment. This study focuses on developing a reliable method for assessing electric discharge cavitation intensity and controlling water purification processes. The proposed approach is based on the oxidation of iodide ions to molecular iodine by reactive species generated during electric discharge cavitation. The adapted iodometric method is sensitive, reproducible, and does not require complex optical or acoustic equipment. Experimental results confirmed that iodometry provides an accurate evaluation of cavitation intensity, allowing control of specific energy consumption and optimization of treatment parameters. Optimal operating conditions were established to control the water processing by electric discharge cavitation: stainless-steel electrodes, specific input energy not exceeding 280 kJ·L⁻¹, the presence of a free liquid surface in the working chamber, and a discharge pulse frequency below 10 Hz. The proposed method supports the development of energy-efficient, low-waste technologies for wastewater and natural water treatment and facilitates the integration of electric discharge systems into existing water treatment infrastructure, particularly under resource-limited conditions. Full article