Search Results (2,986)

The growing penetration of wind power has led to a continuous decline in system rotational inertia, posing serious challenges to the stability of next-generation power systems. Moreover, the strong dependence of wind generation on weather conditions, particularly the increasing frequency of extreme wind events, further exacerbates system vulnerability, making stability enhancement under adverse conditions an urgent research priority. To address this issue, this study proposes a virtual inertia-based control strategy for hybrid wind–storage systems, formulated through transfer function modeling of wind turbines, thermal generators, and energy storage units. By appropriately simplifying the dynamic characteristics of individual components, a comprehensive system-level transfer function model is developed to characterize the frequency response of the hybrid system. Virtual inertia support is provided by controlling the outputs of wind and storage units. A conventional wind–energy storage hybrid system without a virtual inertia control strategy was developed for comparison to evaluate the frequency regulation performance against the proposed system. Simulation studies under large load disturbance scenarios demonstrate that the hybrid wind–storage system achieves a smaller frequency nadir and faster steady-state recovery compared with standalone wind power system and a conventional wind–energy storage hybrid system without a virtual inertia control strategy. Notably, even under extreme wind conditions requiring complete curtailment of wind turbines, the energy storage unit continues to deliver virtual inertia, thereby maintaining system stability, superior to the conventional wind–energy storage hybrid system without virtual inertia control. These findings highlight the enhanced reliability and dynamic performance of wind–storage hybrid systems in mitigating frequency deviations within high-renewable environments, while also demonstrating the proposed control strategy’s robust adaptability to extreme weather conditions. The proposed approach offers valuable insights into strengthening the operational resilience of future low-carbon power systems. Full article

The role of distributed energy resources in distribution networks is evolving to support system operation, facilitated by their participation in local flexibility markets. Future scenarios envision a significant share of low-power resources providing ancillary services to efficiently manage network congestions, offering a competitive alternative to conventional grid reinforcement. Additionally, the interaction between distribution and transmission systems enables the provision of flexibility services at higher voltage levels for various applications. In such cases, the aggregated flexibility of low-power resources is typically represented as a capability envelope at the interface between the distribution and transmission network, constructed by accounting for distribution grid constraints and subsequently communicated to the transmission system operator. This paper revisits this concept and introduces a novel approach for envelope construction. The proposed method is based on a surrogate model composed of a limited set of standard power flow components—loads, generators, and storage units—enhancing the integration of distribution network flexibility into transmission-level optimization frameworks. Notably, this advantage can potentially be achieved without significant modifications to the optimization tools currently available to grid operators. The effectiveness of the approach is demonstrated through a case study in which the adoption of distribution network surrogate models within a coordinated framework between transmission and distribution operators enables the provision of ancillary services for transmission resilience support. This results in improved resilience indicators and lower control action costs compared to conventional shedding schemes. Full article

In line with EU decarbonization targets for the heavy-duty transport sector, this study proposes an analytical methodology to assess the impact of diesel performance additives on fuel consumption in Euro 6 heavy-duty vehicles, the prevailing standard in the circulating European road tractor fleet. A fleet of five N3-category road tractors equipped with tanker semi-trailers was monitored over two phases. During the first 10-month baseline phase, the vehicles operated with standard EN 590 diesel (containing 6–7% FAME); in the second phase, they used a commercially available premium diesel containing performance-enhancing additives. Fuel consumption and route data were collected using a GPS-based system interfaced with the engine control unit via the OBD port and integrated with the fleet tracking platform. After applying data filtering to exclude low-quality or non-representative trips, a 1% reduction in fuel consumption was observed with the use of fuel with additives. Route-level analysis revealed higher savings (up to 5.1%) in high-load operating conditions, while most trips showed improvements between −1.6% and −3.4%. Temporal analysis confirmed the general trend across varying vehicle usage patterns. Aggregated fleet-level data proved to be the most robust approach to mitigate statistical variability. To evaluate the potential impact at scale, a European scenario was developed: a 1% reduction in fuel consumption across the 6.75 million heavy-duty vehicles in the EU could yield annual savings of 2 billion liters of diesel and avoid approximately 6 million tons of CO₂ emissions. Even partial adoption could lead to meaningful environmental benefits. Alongside emissions reductions, fuel additives also offer economic value by lowering operating costs, improving engine efficiency, and reducing maintenance needs. Full article

Bridges, as critical transportation infrastructure, are highly vulnerable to aerodynamic forces, particularly vortex-induced vibrations (VIV), which severely compromise their structural integrity and operational safety. These low-frequency, high-amplitude vibrations are a primary challenge to serviceability and fatigue life. Ensuring the resilience of these structures demands advanced understanding and robust mitigation strategies. This paper comprehensively addresses the multifaceted challenges of bridge aerodynamics, presenting an in-depth analysis of contemporary testing methodologies and innovative solutions. We critically examine traditional wind tunnel modeling, elucidating its advantages and inherent limitations, such as scale effects, Reynolds number dependence, and boundary interference, which can lead to inaccurate predictions of aerodynamic forces and vibration amplitudes. This scale discrepancy is critical, as demonstrated by peak pressure coefficients being underestimated by up to 64% in smaller-scale wind tunnel environments compared to high-Reynolds-number open-jet testing. To overcome these challenges, the paper details the efficacy of open-jet testing at facilities like the Windstorm Impact, Science, and Engineering (WISE) Laboratory, demonstrating its superior capability in replicating realistic atmospheric boundary layer flow conditions and enabling larger-scale, high-Reynolds-number testing for more accurate insights into bridge behavior under dynamic wind loads. Furthermore, we explore the design principles and applications of various aerodynamic mitigation devices, including handrails, windshields, guide vanes, and spoilers, which are essential for altering airflow patterns and suppressing vortex-induced vibrations. The paper critically investigates the innovative integration of green energy solutions, specifically solar panels, with bridge structures. This study presents the application of solar panel arrangements to provide both renewable energy production and verifiable aerodynamic mitigation. This strategic incorporation is shown not only to harness renewable energy but also to actively improve aerodynamic performance and mitigate wind-induced vibrations, thereby fostering both bridge safety and sustainable infrastructure development. Unlike previous studies focusing primarily on wind loads on PV arrays, this work demonstrates how the specific geometric integration of solar panels can serve as an active aerodynamic mitigation device for bridge decks. This dual functionality—harnessing renewable energy while simultaneously serving as a passive geometric countermeasure to vortex-induced vibrations—marks a novel advancement over single-purpose mitigation technologies. Through this interdisciplinary approach, the paper seeks to advance bridge engineering towards more resilient, efficient, and environmentally responsible solutions. Full article

Aiming at the speed chattering problem caused by high-frequency square wave injection in permanent magnet synchronous motors (PMSMs) during low-speed operation (200–500 r/min), this study intends to improve the rotor position estimation accuracy of sensorless control systems as well as the system’s ability to resist harmonic interference and sudden load changes. The goal is to enhance the control performance of traditional control schemes in this scenario and meet the requirement of stable low-speed operation of the motor. First, the study analyzes the harmonic error propagation mechanism of high-frequency square wave injection and finds that the traditional PI phase-locked loop (PI-PLL) is susceptible to high-order harmonic interference during demodulation, which in turn leads to position estimation errors and periodic speed fluctuations. Therefore, the extended state observer phase-locked loop (ESO-PLL) is adopted to replace the traditional PI-PLL. A third-order extended state observer (ESO) is used to uniformly regard the system’s unmodeled dynamics, external load disturbances, and harmonic interference as “total disturbances”, realizing real-time estimation and compensation of disturbances, and quickly suppressing the impacts of harmonic errors and sudden load changes. Meanwhile, a dynamic pole placement strategy for the speed loop is designed to adaptively adjust the controller’s damping ratio and bandwidth parameters according to the motor’s operating states (loaded/unloaded, steady-state/transient): large poles are used in the start-up phase to accelerate response, small poles are switched in the steady-state phase to reduce errors, and a smooth attenuation function is used in the transition phase to achieve stable parameter transition, balancing the system’s dynamic response and steady-state accuracy. In addition, high-frequency square wave voltage signals are injected into the dq axes of the rotating coordinate system, and effective rotor position information is extracted by combining signal demodulation with ESO-PLL to realize decoupling of high-frequency response currents. Verification through MATLAB/Simulink simulation experiments shows that the improved strategy exhibits significant advantages in the low-speed range of 200–300 r/min: in the scenario where the speed transitions from 200 r/min to 300 r/min with sudden load changes, the position estimation curve of ESO-PLL basically overlaps with the actual curve, while the PI-PLL shows obvious deviations; in the start-up and speed switching phases, dynamic pole placement enables the motor to respond quickly without overshoot and no obvious speed fluctuations, whereas the traditional fixed-pole PI control has problems of response lag or overshoot. In conclusion, the “ESO-PLL + dynamic pole placement” cooperative control strategy proposed in this study effectively solves the problems of harmonic interference and load disturbance caused by high-frequency square wave injection in the low-speed range and significantly improves the accuracy and robustness of PMSM sensorless control. This strategy requires no additional hardware cost and achieves performance improvement only through algorithm optimization. It can be directly applied to PMSM control systems that require stable low-speed operation, providing a reliable solution for the promotion of sensorless control technology in low-speed precision fields. Full article

This paper presents adaptive sliding mode observers (A-SMOs) performing speed estimation for sensorless induction motor drives utilized in both industrial and electrical vehicle (EV) applications due to their computational simplicity. The fact that the constant switching gain (${\lambda }_0$) is used in conventional SMOs (C-SMOs) leads to the chattering problem, especially in low-speed regions. To tackle this issue, this paper proposes two different ${\lambda }_0$ adaptation mechanisms based on fuzzy and curve fitting methods. To estimate stator stationary axis components of stator currents and rotor fluxes together with the rotor speed, the proposed A-SMOs only utilize the measured stator currents and voltages of the IM. Here, the difference only between the estimated and measured stator currents is determined as the sliding surface in the proposed A-SMOs. To demonstrate the effectiveness of the proposed fuzzy-based A-SMO (FA-SMO) and curve fitting-based A-SMO (CFA-SMO), they are compared with C-SMO in real-time experiments for different scenarios including wide speed range operations of IM with/without load torque changes. Moreover, the stator and rotor resistances as well as the magnetizing inductance variations are also examined in real-time experiments of the proposed methods and the conventional one. The estimation results demonstrate how positively the ${\lambda }_0$ adaptations in FA-SMO and CFA-SMO affect the performance of C-SMO. Finally, two A-SMOs with improved performance are introduced and verified through real-time experiments. Full article

As the operating conditions of rolling bearings become increasingly demanding, traditional steel bearings can no longer fully meet the performance requirements of critical equipment. Silicon nitride full ceramic ball bearings, with intrinsic properties such as a low thermal expansion coefficient, low density, corrosion resistance, and wear resistance, offer significant advantages in extreme temperatures, high-speed operation, and harsh corrosive environments. As a result, they have become a key technical solution for the core transmission systems of high-end equipment. However, the dynamic evolution of their service performance under varying operating conditions—such as load and speed—remains insufficiently understood. This study systematically investigates the service performance evolution mechanism of silicon nitride full ceramic ball bearings under self-lubrication conditions. The key findings will provide a theoretical foundation for optimizing and regulating performance under extreme operating conditions. Full article

This study investigates the energy and environmental implications of replacing E10 gasoline with Liquefied Petroleum Gas (LPG) in a Euro 4 passenger car under real-world urban driving conditions. A comparative methodology robust to operating-state distribution was applied, combining portable exhaust gas analysis with on-board diagnostic data to calculate energy-specific emissions per crankshaft revolution and to reconstruct emission surfaces in the load–RPM domain using bilinear interpolation. The study revealed that LPG reduces carbon dioxide emissions by 8.35%, demonstrating a clear climate and energy benefit due to its lower carbon intensity. In comparison, carbon monoxide (+9.5%) and hydrocarbons (+8.3%) increased under low-load and idle conditions. Nitrogen oxides showed only minor differences between the fuels (+1.3%). LPG exhibited a more stable CO₂ emission profile, reflecting improved combustion efficiency from an energy perspective, although its performance in terms of incomplete combustion products requires further optimisation. The methodology highlights how linking energy efficiency with pollutant formation provides a comprehensive framework for evaluating alternative fuels in Real Driving Emissions (RDE) tests. The results confirm LPG’s potential to reduce greenhouse gas emissions in transport systems and identify calibration strategies needed to mitigate trade-offs in local pollutant emissions. Full article

In complex 3D maneuvering tasks (e.g., post-disaster rescue, urban operations, and infrastructure inspection), the trajectories that quadrotors need to track are often complex—containing both gentle flight phases and highly maneuverable trajectory segments. Under such trajectory tracking tasks with the composite characteristics of “gentle-high maneuvering”, quadrotors face challenges of limited onboard computing resources and short endurance, requiring a balance between trajectory tracking accuracy, computational efficiency, and energy consumption. To address this problem, this paper proposes a lightweight trajectory tracking control method based on hierarchical decision-making and dual-threshold adaptive switching. Inspired by the biological “prediction–reflection” mechanism, this method designs a dual-threshold collaborative early warning switching architecture of “prediction layer–confirmation layer”: The prediction layer dynamically assesses potential risks based on trajectory curvature and jerk, while the confirmation layer confirms in real time the stability risks through an attitude-angular velocity composite index. Only when both exceed the thresholds, it switches from low-energy-consuming Euler angle control to high-precision geometric control. Simulation experiments show that in four typical trajectories (straight-line rapid turn, high-speed S-shaped, anti-interference composite, and narrow space figure-eight), compared with pure geometric control, this method reduces position error by 19.5%, decreases energy consumption by 45.9%, and shortens CPU time by 28%. This study not only optimizes device performance by improving trajectory tracking accuracy while reducing onboard computational load, but also reduces energy consumption to extend UAV endurance, and simultaneously enhances anti-disturbance capability, thereby improving its operational capability to respond to emergencies in complex environments. Overall, this study provides a feasible solution for the efficient and safe flight of resource-constrained onboard platforms in multi-scenario complex environments in the future and has broad application and expansion potential. Full article

This study addresses structural distortions in the IMO Carbon Intensity Indicator (CII) for short-voyage training vessels and proposes corrective strategies combining denominator adjustments with controllable pitch propeller (CPP) mode optimization. Using 2024 operational data from a training ship, we computed monthly and annual CII values, identifying significant inflation when time-at-sea fractions are low due to extensive port stays. Two correction methods were evaluated: a hybrid denominator approach converting port-stay CO₂ to equivalent distance, and a Braidotti functional correction. The CPP operating maps for combination and fixed modes revealed a crossover point at approximately 12 kn (~50% engine load), where the combination mode shows superior efficiency at low speeds and the fixed mode at higher speeds. The hybrid correction effectively stabilized CII values across varying operational conditions, while the speed-band CPP optimization provided additional reductions. Results demonstrate that combining optimized CPP mode selection with hybrid CII correction achieves compliance with required standards, attaining a B rating. The integrated framework offers practical solutions for CII management in short-voyage operations, addressing regulatory fairness while improving operational efficiency for training vessels and similar ship types. Full article

Small hydropower-dominated microgrids enable power exchange with the main grid during grid-connected operation but face frequency stability challenges during sudden islanding (e.g., line faults), requiring prompt generation curtailment or load shedding. In communication-constrained mountainous regions, conventional methods such as high-frequency tripping or low-frequency load shedding often struggle to achieve precise frequency regulation A hierarchical strategy integrating master station centralized decision making and substation local control is proposed. This study theoretically analyzes the post-islanding frequency dynamics of small hydropower microgrids. The master station formulates optimal shedding decisions using regional power flow data, while substations execute decisions via local measurements to mitigate communication issues. A constrained mathematical model is established, solved using a heuristic algorithm, validated through electromagnetic transient simulations, and compared with traditional schemes. The proposed scheme achieves precise surplus capacity shedding, enhancing frequency stability during abrupt islanding with reduced over-/under-tripping compared to that of conventional methods. This hierarchical strategy enhances frequency regulation capability under communication constraints, ensuring reliable operation of small hydropower microgrids during sudden islanding and providing a practical solution for remote regions with limited communication infrastructure. Full article

Bio-waste from potato shell agro-waste-based photocatalyst is introduced using potato shell integrated with Fe₃O₄ nanoparticles as a novel photocatalyst for photo-Fenton oxidation reaction. The catalyst was prepared via thermal activation of biochar, followed by co-precipitation of magnetite nanoparticles, resulting in a stable and reusable material. X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques augmented with the energy dispersive X-ray spectroscopy (EDX) analysis with elemental mapping were used to assess the prepared sample. The prepared material, PtS200–Fe₃O₄, is then applied for oxidizing Procion Blue dye using biochar-supported magnetite catalyst. The oxidation process was evaluated under varying operational parameters, including pH, temperature, catalyst loading, oxidant dosage, and dye concentration. Results revealed that the system achieved complete dye removal within 20 min at 60 °C and pH 3, demonstrating the strong catalytic activity of the composite. Furthermore, the kinetic modeling is evaluated and the data confirmed that the degradation followed first-order kinetics. Also, the thermodynamic parameters indicated low activation energy with PtS200–Fe₃O₄ composite in advanced oxidation processes. The system sustainability is also assessed, and the reusability test verified that the catalyst retained over 70% efficiency after six consecutive cycles, highlighting its durability. The study confirms the feasibility of using biochar-supported magnetite as a cost-effective, eco-friendly, and efficient catalyst for the treatment of textile effluents and other dye-contaminated wastewater. Full article

With the continuous increase in the penetration of single-phase microgrids in low-voltage distribution networks (LVDNs), the phase asymmetry of source–load distribution has made the problem of three-phase imbalance increasingly prominent. To address this issue, this paper proposes an active–reactive power coordinated optimization model for distribution network–microgrid clusters considering three-phase imbalance mitigation. The model is formulated within a master–slave game framework: in the upper level, the distribution network acts as the leader, formulating time-of-use prices for active and reactive power based on day-ahead forecast data with the objective of minimizing operating costs. These price signals guide the flexible loads and photovoltaic (PV) inverters of the lower-level microgrids to participate in mitigating three-phase imbalance. In the lower level, each microgrid responds as the follower, minimizing its own operating cost by determining internal scheduling strategies and power exchange schemes with the distribution network. Finally, the resulting leader–follower game problem is transformed into a unified constrained model through strong duality theory and formulated as a mixed-integer second-order cone programming (MISOCP) problem, which is efficiently solved using the commercial solver Gurobi. Simulation results demonstrate that the proposed model fully exploits the reactive power compensation potential of PV inverters, significantly reducing the degree of three-phase imbalance. The maximum three-phase voltage unbalance factor decreases from 3.98% to 1.43%, corresponding to an overall reduction of 25.87%. The proposed coordinated optimization model achieves three-phase imbalance mitigation by leveraging existing resources without the need for additional control equipment, thereby enhancing power quality in the distribution network while ensuring economic efficiency of system operation. Full article

Cementation using Ordinary Portland Cement (OPC) remains the standard method for conditioning low- and intermediate-level radioactive waste, including Spent Ion Exchange Resins (SIERs). This work presents an integrated strategy involving thermal pretreatment to minimize waste volume and eliminate organic constituents, followed by encapsulation within three distinct binders: CEM I, CEM III, and a novel one-part geopolymer. The one-part geopolymer system represents a significant operational innovation, enabling safe and simple “just-add-water” processing and avoiding the need to handle alkaline solutions. The proposed geopolymer, synthesized from metakaolin, blast furnace slag, and solid sodium silicate, was systematically benchmarked against conventional OPC matrices (CEM I, CEM III) by assessing their capacity to immobilize thermally treated SIER ashes under accelerated leaching conditions. For benchmarking, leaching indices for Cs and Sr were determined following the ANSI/ANS 16.9 standard protocol in three representative environments simulating operational and long-term repository scenarios, providing a quantitative evaluation of radionuclide retention and matrix durability. Results indicate that the one-part geopolymer improved leaching indices for Cs and Sr compared to both cementitious binders and complied with regulatory waste acceptance criteria. The comparative results highlight the potential of geopolymer technology to increase waste loading efficiencies and improve long-term safety, establishing a robust framework for future radioactive waste management approaches. Full article

Francis turbines are widely used due to their large capacity and broad head adaptability, placing higher demands on the internal flow characteristics and runner performance of the units. In this paper, numerical simulations of a Francis turbine model were conducted using ANSYS CFX 2022 R1. The SST turbulence model, ZGB cavitation model, and VOF multiphase flow model were selected for the calculations. The internal flow characteristics and pressure pulsations in the runner and draft tube under different operating conditions were analyzed, and the variations in normal and tangential forces acting on the runner blades during operation were investigated. The results indicate significant differences in the internal flow within the runner and draft tube under various guide vane opening conditions. The pressure pulsation in the unit is influenced by both the internal flow in the draft tube and the rotation of the runner. The mechanical load on the runner blades is affected by multiple factors, including the wake from upstream fixed guide vanes, rotor–stator interaction, and downstream vortex ropes. Under low-flow conditions, the variation in forces acting on the runner blades is relatively small, whereas under high-flow conditions, the runner blades are prone to abrupt force fluctuations at 0.6–0.8 times the rotational frequency. This is manifested as periodic abrupt force changes in both the X and Y directions of the runner blades under high-flow conditions. The normal force in the Z-direction of the runner blades increases instantaneously and then decreases immediately, while the tangential force decreases instantaneously and then increases promptly. Full article