Search Results (1,164)

The simulation of wind power, electricity load, and natural gas prices will allow commodity traders to see the future movement of prices in a more probabilistic manner. The ability to observe possible paths for wind power, electricity load, and natural gas prices enables traders to obtain valuable insights for placing their trades on electricity prices. Since the above processes involve a seasonality factor, the seasonality component was modeled using a truncated Fourier series, and the random component was modeled using stochastic differential equations (SDE). It is evident from the literature that all the above processes are mean-reverting processes; thus, three mean-reverting Ornstein–Uhlenbeck (OU) processes were considered the model for wind power, the electricity load, and natural gas prices. Industry experts believe there is a correlation between wind power, the electricity load, and natural gas prices. For example, when wind power is higher and the electricity load is lower, natural gas prices are relatively low. The novelty of this study is the incorporation of the correlation structure between processes into the mean-reverting OU process using a copula function. Thus, the study utilized a vine copula and integrated it into the simulation. The study was conducted for the Texas energy market and used daily time scales for the simulations, and it was able to conclude that the proposed novel mean-reverting OU process outperforms the classical mean-reverting process in the case of wind power and the electricity load. Full article

Linear passive electrical devices/components are usually characterized in the frequency domain by their impedance, i.e., the ratio of the voltage and current phasors. The use of the impedance concept does not raise particular concerns in low-frequency regimes; however, things become more complicated when it comes to rapid time-varying phenomena, mainly because the voltage depends not only on the position of the points between which it is defined but also on the choice of the integration path that connects them. In this article, based on first principles (Maxwell equations and Poynting vector flow considerations), we discuss the concept of impedance and define it unequivocally for a class of electrical devices/components with rotational symmetry. Two application examples are presented and discussed. One simple example concerns the per-unit-length impedance of a homogeneous cylindrical wire subject to the skin effect. The other, which is more elaborate, concerns a heterogeneous structure that consists of a dielectric disk sandwiched between two metal plates. For the lossless situation, the high-frequency impedance of this device (circular parallel plate capacitor) reaches zero when the frequency reaches a certain critical frequency f_c; then, it becomes inductive and increases enormously when the frequency reaches another critical frequency at 1.6 f_c. The influence of losses on the impedance of the device is thoroughly investigated and evaluated. Impedance corrections due to dielectric losses are analyzed using a frequency-dependent Debye permittivity model. The impedance corrections due to plate losses are analyzed by considering radial current distributions on the outer and inner surfaces of the plates, the latter exhibiting significant variations near the critical frequencies of the device. Full article

To address the challenges of prolonged current isolation times and high dependency on varistors in traditional flexible short-circuit fault isolation schemes for DC systems, this paper proposes a rapid fault isolation circuit design based on an adaptive solid-state circuit breaker (SSCB). By introducing an adaptive current-limiting branch topology, the proposed solution reduces the risk of system oscillations induced by current-limiting inductors during normal operation and minimizes steady-state losses in the breaker. Upon fault occurrence, the current-limiting inductor is automatically activated to effectively suppress the transient current rise rate. An energy dissipation circuit (EDC) featuring a resistor as the primary energy absorber and an auxiliary varistor (MOV) for voltage clamping, alongside a snubber circuit, provides an independent path for inductor energy release after faults. This design significantly alleviates the impact of MOV capacity constraints on the fault isolation process compared to traditional schemes where the MOV is the primary energy sink. The proposed topology employs a symmetrical bridge structure compatible with both pole-to-pole and pole-to-ground fault scenarios. Parameter optimization ensures the IGBT voltage withstand capability and energy dissipation efficiency. Simulation and experimental results demonstrate that this scheme achieves fault isolation within 0.1 ms, reduces the maximum fault current-to-rated current ratio to 5.8, and exhibits significantly shorter isolation times compared to conventional approaches. This provides an effective solution for segment switches and tie switches in millisecond-level self-healing systems for both low-voltage (LVDC, e.g., 750 V/1500 V DC) and medium-voltage (MVDC, e.g., 10–35 kV DC) smart DC distribution grids, particularly in applications demanding ultra-fast fault isolation such as data centers, electric vehicle (EV) fast-charging parks, and shipboard power systems. Full article

Against the backdrop of the energy crisis and a rapidly advancing digital economy, electricity–computing synergy has become a strategic pathway to resolve energy constraints in computing power center and overcome renewable energy consumption challenges. This study breaks through the existing single-factor fragmented analysis method and systematically constructs a vertically progressive and horizontally coupled electricity–computing synergy planning model to deconstruct the core elements of computing power center construction and reconstruct the path of electricity–computing value co-creation. It proposes a multi-objective site selection decision-making method for computing power center based on linear weighting and the principle of reusability and universality, effectively avoiding the problem of overall system efficiency loss caused by single-objective optimization. Based on the empirical results from data from 31 provinces in China, this study classifies the endowments for computing power center construction, conducts targeted analyses of each province’s situation, and finds three major contradictions facing China’s computing power center: a spatial mismatch between green energy resources and service demand, a dynamic imbalance between electricity price advantages and comprehensive costs, and structural contradictions between talent reserves and sustainable development. Finally, a multi-dimensional integrated strategy was systematically constructed, encompassing demand-driven initiatives, electricity price adjustments, talent innovation, natural cold-source activation, and network upgrades, to provide guidance and policy toolkits for the government planning of computing power infrastructure development. Full article

Large steam turbine generators are increasingly vulnerable to damage from shaft voltages and bearing currents due to the widespread adoption of modern power electronic excitation systems and more flexible operating regimes. Earthing brushes provide a critical path for discharging these shaft currents and voltages, but their effectiveness depends on the timely detection of brush degradation or faults. Conventional monitoring of shaft voltage and current is often rudimentary, typically limited to peak readings, making it challenging to identify specific fault conditions before mechanical damage occurs. This study addresses this gap by systematically analyzing shaft voltage and current signals under various controlled earthing brush fault conditions (floating brushes, worn brushes, and oil/dust contamination) in several large turbine generators. Experimental site tests identified distinct electrical signatures associated with each fault type, demonstrating that online shaft voltage and current measurements can reliably detect and classify earthing brush faults. These include unique RMS, DC, and harmonic patterns in both voltage and current signals, enabling accurate fault classification. These findings highlight the potential for more proactive maintenance and condition-based monitoring, which can reduce unplanned outages and improve the reliability and safety of power generation systems. Full article

In the field of modern optical communication, radar signal processing and optical sensors, true time delay technology, as a key means of signal processing, can achieve the accurate control of the time delay of optical signals. This study presents a novel design that integrates a 2 × 2 Multi-Mode Interference (MMI) structure with a Mach–Zehnder modulator on a silicon nitride–lithium niobate (SiN-LiNbO₃) heterogeneous integrated optical platform. This configuration enables the selective interruption of optical wave paths. The upper path passes through an ultralow-loss Archimedes’ spiral waveguide delay line made of silicon nitride, where the five spiral structures provide delays of 10 ps, 20 ps, 40 ps, 80 ps, and 160 ps, respectively. In contrast, the lower path is straight through, without introducing an additional delay. By applying an electrical voltage, the state of the SiN-LiNbO₃ switch can be altered, facilitating the switching and reconfiguration of optical paths and ultimately enabling the combination of various delay values. Simulation results demonstrate that the proposed optical true delay line achieves a discrete, adjustable delay ranging from 10 ps to 310 ps with a step size of 10 ps. The delay loss is less than 0.013 dB/ps, the response speed reaches the order of ns, and the 3 dB-EO bandwidth is broader than 67 GHz. In comparison to other optical switches optical true delay lines in terms of the parameters of delay range, minimum adjustable delay, and delay loss, the proposed optical waveguide digital adjustable true delay line, which is based on an optical switch and an Archimedes’ spiral structure, has outstanding advantages in response speed and delay loss. Full article

Microbial Fuel Cell (MFC) is a novel bioelectrochemical system that catalyzes the oxidation of chemical energy in organic waste and converts it directly into electrical energy through the attachment and growth of electroactive microorganisms on the electrode surface. This technology realizes the synergistic effect of waste treatment and renewable energy production. A CF-NiO-PANI capacitor composite anode was prepared by loading polyaniline on a CF-NiO electrode to improve the capacitance of a CF electrode. The electrochemical characteristics of the composite anode were evaluated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), and the electrode materials were analyzed comprehensively by scanning electron microscopy (SEM), energy diffusion spectrometer (EDS), and Fourier transform infrared spectroscopy (FTIR). MFC system based on CF-NiO-PANI composite anode showed excellent energy conversion efficiency in potato starch wastewater treatment, and its maximum power density increased to 0.4 W/m³, which was 300% higher than that of the traditional CF anode. In the standard charge–discharge test (C1000/D1000), the charge storage capacity of the composite anode reached 2607.06 C/m², which was higher than that of the CF anode (348.77 C/m²). Microbial community analysis revealed that the CF-NiO-PANI anode surface formed a highly efficient electroactive biofilm dominated by electrogenic bacteria (accounting for 47.01%), confirming its excellent electron transfer ability. The development of this innovative capacitance-catalytic dual-function anode material provides a new technical path for the synergistic optimization of wastewater treatment and energy recovery in MFC systems. Full article

Industrial parks are well-known as a critical intervention point for global carbon emission reductions due to the high carbon emissions emitted. Conducting carbon accounting research in these parks can provide more precise foundational data for carbon reduction initiatives, promoting low-carbon industrial park development. However, industrial parks, positioned as non-independent accounting units between provincial and industry levels, face severe challenges due to ambiguous boundaries, complex accounting entities, and data selection difficulties that significantly impact the carbon accounting accuracy. This study employed the IPCC emission factor method for industrial parks, taking its management structure as the accounting boundary. Additionally, we constructed a carbon accounting method and representation system by considering the carbon emission flow path and integrating the correlation between pollutant and carbon emissions. By categorizing carbon emissions into five groups, this study obtained emissions from fuel combustion (E1), industrial processes (E2), purchased/sold electricity (E3), purchased/sold heat (E4), and carbon-sequestering products (E5). Between 2016 and 2021, the industrial park’s carbon emissions fell from 15.0783 to 6.7152 million tons, while the intensity dropped from 4.86 to 1.91 tons of carbon dioxide (CO₂) per CNY 10,000. The park achieved dual control targets for the total carbon emissions and intensity, with E2 being the main reduction source (70% of total). Meanwhile, total atmospheric pollutants decreased from 9466.19 to 1736.70 tons, with C25 and C26 industries contributing over 99%. In particular, C26 achieved significant reductions in nitrogen oxides (NO_x) and sulfur dioxide (SO₂), aiding pollution mitigation. A strong positive correlation was found between pollutants and carbon emissions, especially in C26, SO₂ (0.77), and NO_x (0.89), suggesting NO_x as a more suitable carbon emission indicator during chemical production. These findings offer a theoretical framework for using pollutant monitoring to characterize carbon emissions and support decision-making for sustainable industrial development. Full article

This paper analyzes the electromagnetic characteristics of an interior permanent magnet synchronous motor (IPMSM) for electric vehicle traction under various control imbalance conditions in a twin inverter system, assuming that one of the inverters fails to operate properly. The imbalance conditions are first investigated through dynamometer experiments and then applied to finite element method (FEM) simulations to evaluate their electromagnetic effects. Since the focus is on scenarios where a single inverter malfunctions, a stator winding configuration is first redefined to ensure stable operation in a single inverter system by preventing voltage and current imbalances within the circuit. When the stator winding is configured with eight parallel paths, the dynamometer test results show a phase voltage imbalance. However, when the number of parallel circuits is reduced to four, this voltage imbalance disappears. Using this configuration, a twin inverter system is constructed, and various imbalance conditions are applied to intuitively examine the electromagnetic characteristics when one inverter fails to accurately control current magnitude or phase angle. The simulation results showed that applying unbalanced conditions to the current and current phase angle led to a decrease in torque and an increase in torque ripple. In addition, when one of the inverters was completely disconnected, the motor performance analysis showed that it operated with approximately half of its original performance. Based on dynamometer experiments and finite element method (FEM) simulations, the electromagnetic characteristics under inverter fault conditions and appropriate stator winding configurations were analyzed. When an optimal number of parallel circuits is applied to the stator winding and a twin inverter system is employed, the load on each individual inverter is reduced, enabling accurate control. This makes the application to high-voltage and high-current systems feasible, allowing higher performance. Moreover, even if one inverter fails, the system can still operate at approximately half its capacity, ensuring high operational reliability. Full article

Multilevel inverters (MLIs) have become fundamental in contemporary power electronics, providing enhanced performance compared to conventional two-level inverters regarding their output voltage quality, efficiency, and scalability. This study comprehensively assesses multilevel inverter technologies, including their topologies, control systems, and various applications. The study starts with a comprehensive examination of the core concepts of MLIs, subsequently embarking on a detailed evaluation of both conventional and innovative topologies, such as diode-clamped, flying capacitor, cascaded H-bridge, and modular multilevel converters. The study further examines the control systems used in MLIs, including Pulse Width Modulation (PWM), space vector modulation (SVM), and Model Predictive Control (MPC), emphasizing their benefits and drawbacks. The applications of MLIs in renewable energy systems, electric cars, industrial drives, and grid integration are comprehensively examined. The study closes by examining growing trends, difficulties, and future research paths, emphasizing the ability of MLIs to transform power conversion systems. Full article

This study investigates a variant of the shortest path problem (SPP) tailored for plug-in hybrid electric vehicles (PHEVs), incorporating two practical features: hybrid energy mode switching and partial charging. A novel modeling framework is proposed that enables PHEVs to dynamically switch between electricity and fuel along each edge and to recharge partially at charging stations. Unlike most prior studies that rely on more complex modeling approaches, this paper introduces a compact mixed-integer linear programming (MILP) model that remains directly solvable using commercial solvers such as Gurobi. To address large-scale networks, a customized labeling algorithm is developed for an efficient solution. Numerical results on benchmark networks show that the hybrid mode and partial charging can reduce total cost by up to 29.76% and significantly affect route choices. The proposed algorithm demonstrates strong scalability, solving instances with up to 33,000 nodes while maintaining near-optimal performance, with less than 5% deviation in smaller cases. Full article

Wire electrical discharge machining (WEDM), as a significant branch of non-traditional machining technologies, is widely applied in fields such as mold manufacturing and aerospace due to its high-precision machining capabilities for hard and complex materials. This paper systematically reviews the research progress in WEDM process optimization from two main perspectives: traditional optimization methods and artificial intelligence (AI) techniques. Firstly, it discusses in detail the applications and limitations of traditional optimization methods—such as statistical approaches (Taguchi method and response surface methodology), Adaptive Neuro-Fuzzy Inference Systems, and regression analysis—in parameter control, surface quality improvement, and material removal-rate optimization for cutting metal materials in WEDM. Subsequently, this paper reviews AI-based approaches, traditional machine-learning methods (e.g., neural networks, support vector machines, and random forests), and deep-learning models (e.g., convolutional neural networks and deep neural networks) in aspects such as state recognition, process prediction, multi-objective optimization, and intelligent control. The review systematically compares the advantages and disadvantages of traditional methods and AI models in terms of nonlinear modeling capabilities, adaptability, and generalization. It highlights that the integration of AI by optimization algorithms (such as Genetic Algorithms, particle swarm optimization, and manta ray foraging optimization) offers an effective path toward the intelligent evolution of WEDM processes. Finally, this investigation looks ahead to the key application scenarios and development trends of AI techniques in the WEDM field for cutting metal materials. Full article

Many communities in the Brazilian Amazon region remain without reliable access to electricity due to geographical barriers and the high cost of connecting to the national grid. This study aims to evaluate the techno-economic feasibility of implementing battery storage systems in an existing isolated solar–diesel microgrid located in Tunui-Cachoeira, in the district of São Gabriel da Cachoeira (AM). The analysis uses an energy balance methodology, implemented through the HOMER Pro simulation platform, to assess three scenarios: (i) without batteries, (ii) with lithium-ion batteries, and (iii) with lead–acid batteries. Technical and economic indicators such as net present cost (NPC), levelized cost of energy (LCOE), diesel consumption, and renewable fraction were compared. The results indicate that incorporating lead–acid batteries yields the lowest LCOE (1.99 R$/kWh) and the highest renewable fraction (96.8%). This demonstrates that adding energy storage systems significantly enhances the performance and cost-effectiveness of microgrids, offering a viable path to electrify remote and hard-to-reach communities in the Amazon. Full article

The failure of a porcelain insulator on a transmission line is a crucial cause of power supply interruptions, leading to poor reliability and revenue loss. The insulator’s performance is adversely affected by environmental contaminants, and wettability intensifies this adverse effect by developing a conductive path along the insulator’s surface, leading to premature flashover and insulator failure. This work aims to analyze the response of the electric field distribution and current density using the finite element method (FEM) under different wettability conditions. Discrete water droplets were placed along the surface, and the contact angle was varied to represent different levels of surface hydrophobicity. Abrupt rises and spikes were observed on the plots for the electric field and current density distribution, indicating distortion; however, the distortion kept on decreasing with the increase in the contact angle. Overall, the average stress followed a declining pattern, where the values of the electric field were reduced from 2.588 to 2.412 kV/cm, and current the density was reduced from 0.187 to 0.068 nA/cm² for an increase in the contact angle from 60° to 140°. Simulation results advocate for hydrophobic insulator surfaces. Therefore, a proper coating is necessary to enrich hydrophobicity and mitigate the adversity of wettability. Polyurethane, due to its excellent hydrophobic and insulating properties, offers a potential coating. Flashover voltage tests have been performed for the coated insulator under dry and wet conditions, where the flashover voltage improved from 79.14 kV to 82.04 kV and 48.4 kV to 53.8 kV, respectively, which supports the simulations’ outcomes. Full article

In this study, a novel silicon carbide (SiC) double-trench MOSFET (DT-MOS) combined Schottky barrier diode (SBD) and MOS-channel diode (MCD) is proposed and investigated using TCAD simulations. The integrated MCD helps inactivate the parasitic body diode when the device is utilized as a freewheeling diode, eliminating bipolar degradation. The adjustment of SBD position provides an alternative path for reverse conduction and mitigates the electric field distribution near the bottom source trench region. As a result of the Schottky contact adjustment, the reverse conduction characteristics are less influenced by the source oxide thickness, and the breakdown voltage (BV) is largely improved from 800 V to 1069 V. The gate-to-drain capacitance is much lower due to the removal of the bottom oxide, bringing an improvement to the turn-on switching rise time from 2.58 ns to 0.68 ns. These optimized performances indicate the proposed structure with both SBD and MCD has advantages in switching and breakdown characteristics. Full article