Search Results (24,550)

Modern power systems are becoming increasingly complex due to the rapid integration of renewable energy sources, the widespread use of nonlinear power-electronic devices, and the deployment of microgrids operating in parallel with conventional power grids. These evolving conditions intensify the occurrence of diverse and highly complex power quality disturbances (PQDs), demanding accurate and computationally efficient monitoring strategies. This paper presents a novel multi-stage hierarchical framework for PQD detection and classification, comprising an initial training stage with a dedicated 1D Convolutional Neural Network (1D-CNN), a transfer learning stage, and a subsequent fine-tuning stage. The proposed approach operates directly on raw voltage waveforms, eliminating the need for any signal preprocessing, as the CNN performs internal feature extraction. The framework is evaluated using a comprehensive dataset that includes synthetic signals, Matlab/Simulink (version R2022a) time-domain simulations, and real voltage sag events. Additionally, up to 29 types of disturbances, including complex multi-event combinations defined by the IEEE-1159 Standard, are generated using the PQ-SyDa toolbox. The proposed model achieves an F1-score of 97.8% using a three-cycle analysis window and further improves to 98.86% when five cycles are used. These results highlight the robustness and generalization capability of the proposed approach for the real-time PQD monitoring task in modern electrical networks. Full article

With the increasing integration of distributed energy sources, fault restoration in power distribution systems faces challenges in terms of real-time performance and adaptability. To effectively manage the uncertainty and volatility of distributed generation, this paper proposes a rapid self-healing strategy based on a dynamic operational grid. By enabling real-time topological reconfiguration and utilizing adaptive resource allocation, the proposed method accommodates the inherent fluctuations of distributed energy sources. First, a dynamic grid weighted graph theory model is constructed, and an emergency control strategy combining particle preprocessing and stepwise optimization is designed to achieve rapid fault response. Then, a “primary-secondary” two-tier restoration mechanism is established: the primary layer integrates the Floyd algorithm with optimized adaptive dynamic programming to achieve millisecond-level restoration of critical loads; the secondary layer employs an improved particle swarm algorithm incorporating Lévy flight perturbations and adaptive weighting to maximize the restoration of general loads. Simulations on a 56-node system demonstrate that this method achieves 100% restoration of critical loads under various fault scenarios. Even under extreme conditions, it can restore 90.88% of secondary loads and 44.63% of tertiary loads, forming a self-healing system characterized by “second-level detection and minute-level restoration,” thereby significantly enhancing system resilience. Full article

Hydrogen (H₂) is regarded as a promising option for sustainable energy systems; however, its large-scale use in electricity supply remains limited. This study develops a stochastic network optimization model to examine the applicability of H₂-based electricity generation. The proposed Hydrogen Supply Chain (HSC) model evaluates cost and emission performance under uncertainty by considering disaster conditions, transmission losses, depreciation, and the time value of money. The Marmara Region of Türkiye is divided into 24 grid nodes, and a single-period model for 2023 is solved using Mixed-Integer Linear Programming (MILP). The HSC is allowed to meet 10–40% of electricity demand and to replace collapsed grid lines by supplying critical public centers (CPCs) during disasters. The results show that the HSC can meet 24.82% of demand, although at costs approximately 3.9 times higher than power grid (PG) electricity, while producing 3.44 MtCO₂/year compared to 65.96 MtCO₂/year from the PG. The model is then extended to a multi-period structure (2023–2053) and solved by Variable Neighborhood Search (VNS). Over time, H₂ costs decline, and their share rises from 19% to 35%, while electricity costs decrease from 408 USD/MWh to 170 USD/MWh. These findings suggest that H₂-based electricity supply can support long-term sustainability and resilience objectives in regional energy planning. Full article

Wet friction components are critical to power transmission in petroleum drilling machinery, where their reliability directly affects system stability. Surface defects, such as scratches and plowing grooves, can significantly degrade transmission performance, highlighting the importance of interface morphology prediction for intelligent wear diagnosis. In this study, interface morphology data under different conditions are acquired using a UMT-Tribolab test platform and a white light interferometer. The Scale-Invariant Feature Transform (SIFT) algorithm is employed to achieve precise localization of microscopic regions before and after testing. Based on this, an NRBO-VMD-Transformer model is developed to predict the interface morphology of wet friction components under varying conditions. The results demonstrate that SIFT enables accurate localization of microscopic regions, while the proposed model achieves high-precision prediction of interface morphology evolution. These findings provide a reliable basis for interface morphology prediction and wear evolution analysis of wet friction components. Full article

Understanding advanced pre-tertiary mathematics, particularly three-dimensional vectors, demands robust spatial reasoning skills that many students find challenging to develop through traditional pedagogical methods. This study proposes and evaluates an innovative educational tool that leverages large vision models to automate the conversion of handwritten vector equations into accurate 3D graphical representations. By interpreting students’ handwritten input using advanced computer vision, the system provides immediate, interactive visual feedback to bridge the cognitive gap between abstract symbolic notation and tangible geometric concepts. We evaluated the system using a dataset of 1000 handwritten vector equations typical of the Singapore-Cambridge GCE ‘A’ Level H2 Mathematics syllabus. Our findings demonstrate that while GPT-4o serves as a capable baseline, achieving 84.6% accuracy with multi-shot prompting, newer variants such as GPT-4.1-mini offer superior performance, reaching 91.4% accuracy with significantly higher computational efficiency. The results confirm that AI-powered visualisation tools can effectively interpret complex spatial mathematical layouts when guided by optimal prompt engineering. Implementing such technology in educational settings presents a viable, scalable, and cost-effective method to democratise learning support, fostering independent study and enhancing students’ conceptual comprehension of spatial mathematics. Full article

Commutation failure is likely to occur when an AC fault occurs at the receiving end of an LCC-HVDC system. This threatens transient stability. Conventional commutation failure prevention (CFPREV) control mainly responds to commutation-voltage magnitude variation. However, commutation-voltage phase variation is not fully considered. Its fixed start-up threshold also makes it difficult to adapt to different fault severities. To address these problems, this paper establishes a transient nonlinear large-signal model of the inverter. The model incorporates power angle variation and describes the coupled effects of DC current rise, commutation-voltage drop, and power angle deviation on the extinction angle. Phase-portrait analysis is then used to illustrate the transient evolution and critical characteristics of first commutation failure (FCF). The critical commutation voltage is predicted under different fault severities and further converted into a dynamic CFPREV start-up threshold. Simulations based on the CIGRE LCC-HVDC benchmark model verify the prediction accuracy. They also show that the improved CFPREV strategy suppresses FCF mainly by starting up at an appropriate instant rather than increased compensation strength. Full article

Nowadays, numerical simulation methods are advanced and widely used in industry, enabling the modeling of complex systems from printed circuit boards (PCBs) to full power converters. Among many isolated topologies, the phase-shift full-bridge (PSFB) topology is a well-established solution for isolated DC–DC conversion in electric vehicles. Therefore, this paper proposes a broadband electromagnetic compatibility (EMC) modeling methodology for a custom-designed 1 kW gallium nitride (GaN)-based PSFB converter intended for an electric vehicle (EV) DC powertrain. Moreover, the approach combines full-wave electromagnetic simulation with circuit-level simulation, including parasitic effects from PCB layout, power harnesses, and discrete components. Thus, the virtual prototype is assessed within a complete virtual test bench compliant with the standard Comité International Spécial des Perturbations Radioélectriques (CISPR) 25 over the 150 kHz–108 MHz range to capture common-mode (CM) and differential-mode (DM) conducted electromagnetic interference (EMI). Results show that the converter achieves efficiencies of 97.26% in standalone mode and 97.03% when integrated into the full DC powertrain. However, the conducted EMI assessment reveals that both CM and DM emissions exceed CISPR 25 Class 2 limits across the entire spectrum, with excess levels reaching up to 72 dBµV. Therefore, power harnesses significantly increase EMI levels at low frequencies due to the distributed inductance and stray capacitance. Finally, this study demonstrates the value of virtual prototyping for simulation-based EMI prediction in early-stage power converter design. Full article

Next-generation unmanned aerial vehicles require compact propulsion systems capable of providing efficient vertical lift, rapid thrust vectoring, and improved maneuverability. Cyclorotors represent a promising alternative to conventional propellers, but their aerodynamic behavior is governed by highly unsteady blade–wake interactions, making performance prediction challenging. This study investigates a four-bladed cyclorotor equipped with NACA 0012 airfoils using transient computational fluid dynamics simulations and a calibrated semi-analytical blade-element model. The numerical analysis was performed over a rotational-speed range of 368–2305 rpm and for several pitch-amplitude configurations, including 5°, 7.5°, 10°, 12.5° and 15°. The results showed that the favorable pitch amplitude decreases with increasing rotational speed, shifting from larger amplitudes at low RPM to approximately 5° at higher RPM values. The semi-analytical model reproduced the main CFD trends for lift, drag, moment, and power, providing a reduced-order tool for preliminary cyclorotor performance estimation. The comparison confirmed that pitch-amplitude selection strongly influences aerodynamic loading and efficiency and should therefore be adapted to the operating regime. The proposed CFD-based methodology, supported by semi-analytical modelling, provides a useful framework for the aerodynamic characterization and early-stage optimization of cyclorotor propulsion systems for UAV applications. Full article

Parallel grid-forming energy storage converters based on virtual synchronous generator (VSG) control are prone to active power oscillation and interphase circulating current under load disturbance, unit switching, and parameter mismatch conditions. To address these problems, this paper proposes a dual-layer damping control strategy that combines adaptive virtual damping in the power loop with capacitor current feedback damping in the current loop. First, the small-signal models of the LCL filter, VSG power loop, and parallel converter system are established, and the dominant oscillation modes are analyzed using eigenvalue and participation factor methods. Then, an adaptive damping coefficient is designed according to the active power deviation and frequency dynamic response to suppress low-frequency power oscillation, while a capacitor current feedback branch is introduced to reshape the LCL filter’s resonant poles and attenuate circulating current resonance. Compared with the conventional fixed-damping VSG control, the proposed method reduces active power overshoot and accelerates power redistribution under load step and unit switching conditions. In the traditional control case, the active power peaks of VSG1 and VSG2 reach approximately 30 kW and 40 kW, with an oscillation period of about 1.8 s, whereas the proposed strategy suppresses the oscillatory process and enables the output powers to rapidly reach the preset sharing ratio. In addition, the system frequency can recover to the rated value of 50 Hz without obvious steady-state deviation, and the high-frequency component of the grid-connected current and the interphase circulating current are significantly attenuated. MATLAB/Simulink simulation results verify that the proposed dual-layer damping strategy provides better power oscillation suppression, circulating current mitigation, and frequency dynamic performance than the conventional VSG control. Full article

To improve the sustainability of intelligent building operation and enhance grid adaptability in the presence of uncertainty, this paper presents a coordinated optimization method that jointly exploits virtual energy storage and waste heat recovery. A thermal modeling framework is developed to represent the coupling relationships among air conditioning operation, waste heat utilization, and indoor comfort requirements. On this basis, building thermal inertia is incorporated into an IDM-informed two-stage robust optimization framework, where distributional bounds derived from the Imprecise Dirichlet Model are transformed into data-driven interval uncertainty sets for wind–photovoltaic output and outdoor temperature. To make the model computationally tractable, the column-and-constraint generation method is employed for iterative solution. Numerical results verify that the proposed method can effectively unlock the flexibility of the cooling system and improve the utilization of recoverable heat resources while maintaining acceptable indoor comfort, even under adverse operating conditions. Overall, the proposed strategy strengthens system resilience, reduces carbon-related operational pressure, and provides more dependable demand-side support for secure power system operation. Full article

The rapid proliferation of low-altitude unmanned aerial vehicle (UAV) applications has made autonomous identification technology critical for flight safety and collaborative operations. In this paper, we propose and systematically analyze an autonomous identification scheme based on Bluetooth Low Energy (BLE) technology. We formulate a comprehensive system model that integrates link budget, packet collision, identification success probability, and power consumption. By incorporating safety interval constraints and a three-channel integrated reception probability, we employ an exhaustive search algorithm to optimize monitoring strategy parameters, thereby achieving an optimal trade-off between the Recognition Success Rate (RSR) and power consumption. Simulation results indicate that, at a PHY 1 Mbps rate, the optimal monitoring strategy theoretically approaches the Target Level of Safety (TLS) requirements for civil UAVs under the defined model assumptions, with a power consumption of 19.24 mW and an Average First Identification Delay (AFID) of 105 ms. Furthermore, simulation analysis verifies the scheme’s feasibility under dynamic topology, interference, and multi-UAV scenarios, providing a solid theoretical and technical reference for the practical implementation of autonomous UAV identification. Full article

Geometric monitoring of slender support structures, particularly steel lattice transmission towers, is a critical component of power infrastructure diagnostics. Such structures are susceptible to environmental influences and long-term deformation processes, which necessitates precise assessment of their geometric axis. The aim of this study was to evaluate the influence of the terrestrial laser scanning (TLS) scanner class and point cloud registration strategy on the determination of the geometric axis of a steel high-voltage lattice transmission tower (hereafter LTT). Unlike previous studies focused primarily on TLS-based axis reconstruction, this work introduces a comparative assessment of registration strategies, an error propagation model, and the proposed Axis Drift Index (ADI) as quantitative indicators of axis stability. The analysis was based on data obtained using a tachymetric method (reference), a compact scanner (Leica BLK360), and a survey-grade scanner (Riegl VZ-400i). The comparison included planimetric axis deviation, consistency of deformation direction, variation in results with height, and the influence of registration quality. The results show that TLS measurements performed using a survey-grade scanner and target-based registration exhibit high agreement with tachymetric results. In contrast, cloud-to-cloud registration without a stable reference framework leads to cumulative errors and instability of the reconstructed axis, particularly in the upper parts of the structure. The observed deviations in the BLK360 dataset were dominated by registration-related geometric instability rather than unequivocal structural deformation signals. The findings indicate that the accuracy of geometric axis determination in slender structures is governed more by the adopted point cloud registration strategy than by the scanner class itself. The proposed ADI parameter and linear error propagation model additionally enabled a quantitative assessment of geometric consistency with height. From an engineering perspective, this highlights the importance of stable reference systems and appropriate survey design in high-precision TLS applications. Although the study was conducted on a single lattice tower, the results provide practical insight into the reliability of TLS workflows for slender structures characterized by discontinuous geometry and high sensitivity to registration errors. Full article

To improve the flexibility and carbon reduction performance of coal-fired power plants, a solar-aided power generation (SAPG) system integrated with parabolic trough collectors and thermal energy storage (TES) was proposed and investigated using a combined Aspen Plus and System Advisor Model (SAM) framework. Two different integration schemes, namely SAPG-1 and SAPG-2, were evaluated under 100%, 75%, and 50% load conditions with a solar multiple of 2 and a TES duration of 6 h. The thermodynamic, economic, and environmental performances of the systems were comprehensively analyzed. The results show that TES significantly improves solar energy utilization, annual solar contribution, and system dispatchability. Compared with SAPG-2, SAPG-1 demonstrates superior thermodynamic and economic performance due to its lower boiler heat demand and more effective feedwater integration. At full load, the solar contribution of SAPG-1 with TES reaches 16.04%, while the annual solar energy production increases to 190.35 GWh with a capacity factor of 21.75%. In addition, TES integration effectively reduces the levelized cost of electricity and shortens the payback period under both CO₂ pricing and non-CO₂ pricing scenarios. The proposed SAPG framework demonstrates considerable potential for enhancing renewable energy utilization, operational flexibility, and economic feasibility in large-scale solar–coal hybrid power generation systems. Full article

Power systems worldwide are evolving toward interconnection and long-distance transmission, resulting in issues of uneven power flow distribution. Single-core independent phase shifting transformers (SCIPSTs) can regulate voltage magnitude and phase angle, serving as an effective solution to this problem. To provide guidance on the parameter design for practical applications, this paper conducted a study on the topological structure, regulation characteristics, and parameter design of SCIPSTs. First, the topological composition and working principle of SCIPSTs are elaborated. Regulation of voltage magnitude and phase shift angle is achieved by controlling the magnitude and phase of the compensation voltage. Second, the voltage regulation characteristics of SCIPSTs are analyzed, and the constraint mechanisms of the source-side winding transformation ratio and load-side winding transformation ratio on the compensation voltage range are revealed. Third, the influence of symmetric and asymmetric parameter designs on the regulation range is discussed, illustrating the key parameter design methods. Finally, a system simulation model is built to verify the voltage regulation and power flow control effects of SCIPSTs. Simulation results show that SCIPSTs can realize independent regulation of active power and reactive power within a certain range, with significantly improved regulation precision and performance. Full article

Background/Objectives: Despite advances in the TNM staging system, prognostic heterogeneity persists in early-stage non-small cell lung cancer (NSCLC). Lymphatic invasion (LI) is a known marker of aggression, but its independent significance in the critical, low-risk Stage I, N0 subgroup—typically ineligible for adjuvant therapy—remains poorly defined. We hypothesized that LI acts as a powerful, yet hidden, risk factor in this highly favourable cohort. Methods: This retrospective cohort study included 988 consecutive patients who underwent curative anatomical resection for NSCLC. All patients underwent complete resection with pathologically confirmed negative surgical margins (R0 resection). Cases were staged according to the 9th Edition of the TNM Classification of Malignant Tumours (TNM-9) and grouped as LI-positive or LI-negative. A critical subgroup analysis focused on 347 truly low-risk patients (TNM Stage I, N0, no vascular or pleural invasion). Overall survival (OS) was evaluated using the Kaplan–Meier method and multivariable Cox proportional hazards models. Results: In the entire cohort (n = 988), LI was present in 40.9% of cases. LI positivity was an independent predictor of worse OS in multivariable analysis (HR: 1.520, 95% CI: 1.004–2.301, p = 0.048). In the low-risk subgroup (n = 347), the presence of LI resulted in a drastic survival divergence, with 5-year OS declining from 96.1% (LI-negative) to 83.8% (LI-positive). Multivariable analysis confirmed LI as an independent adverse prognostic factor in this subgroup (HR: 4.002, 95% CI: 1.567–10.221, p = 0.004). Conclusions: Lymphatic invasion is a robust, independent adverse prognostic factor in resected NSCLC. LI may identify a subset of early-stage N0 NSCLC patients who warrant closer postoperative surveillance and prospective evaluation for adjuvant treatment strategies. Validation in prospective cohorts is required before LI can be formally integrated into staging algorithms or treatment guidelines. Full article