Search Results (1,891)

This paper presents a technical and economic feasibility analysis of a microgrid based on an existing traction substation supplying a 3 kV DC railway network. The study is based on real 15-min electricity consumption measurements and applies an engineering-oriented methodology to assess the integration of distributed energy resources, including wind turbines, photovoltaic generation, and a battery energy storage system. The analysis focuses on component sizing, land-use constraints, and investment efficiency under conservative and transparent assumptions. The results demonstrate that traction substation-based microgrids are technically feasible under realistic environmental and spatial conditions. The conducted variant analysis reveals a clear trade-off between the number of installed wind turbines and the required photovoltaic installation area, highlighting the importance of generation redundancy and source diversification for infrastructure-critical applications. The energy storage system is designed as a reliability-oriented backup component, ensuring continuity of supply during primary power outages rather than serving as an optimization or arbitrage asset. From an economic perspective, the obtained investment efficiency indicators indicate that the proposed microgrid configuration can achieve acceptable performance for capital-intensive infrastructure assets, particularly when supported by appropriate financing conditions and policy instruments. Overall, the study confirms that traction substation-based microgrids constitute a viable solution for enhancing energy supply diversification, resilience, and decarbonization of railway power systems, while providing a transparent framework for early-stage decision-making. Full article

The Hubei carbon emissions trading market presents significant price volatility driven by energy price fluctuations, macroeconomic conditions and policy changes. Accurate price risk measurement is critically important for market participants. This study adopts Value at Risk (VaR) and Expected Shortfall (ES) to quantify market risk, and constructs a set of DCS-type models by combining the dynamic conditional score framework with the skewed Student-t distribution. Model evaluation covers unconditional coverage test, conditional coverage test, dynamic quantile test, the Actual-to-Expected ratio, the mean and the maximum absolute deviation, quantile loss and FZ loss. Empirical analysis based on daily HBEA spot prices from 3 April 2014 to 4 December 2024 shows that: (1) The DCS-ST model provides better data fitting performance and can effectively measure the market risk of China’s carbon trading market. (2) The parameter updating frequency has little impact on the prediction accuracy of the model. The results enriches the quantitative methodology for carbon market risk measurement and provide a reliable technical scheme for tail risk management in China’s carbon emissions trading market. Full article

Battery-balancing circuits are essential for improving the performance, safety, and service life of lithium-ion battery packs in electric vehicles and energy storage systems. This paper proposes a modified multi-port half-bridge DC–DC circuit with a reconfigurable port network and its control method for battery balancing and multi-level DC voltage output. The circuit evolves from traditional inductor-based balancing units, while a new sequential turn-off switching strategy is introduced so that only one switch is turned off at any moment, achieving precise voltage distribution by adjusting the duty cycle. To improve control accuracy, a dual closed-loop voltage-current control strategy with adaptive gain scheduling and nonlinear compensation is employed. Furthermore, a predictive voltage control strategy based on Mamba-Multilayer Perceptron optimized by the Crested Porcupine Optimizer (CPO-Mamba-MLP-PVC) is proposed. This data-driven approach predicts a target voltage that considers battery and circuit losses, thereby optimizing the balancing path. Experimental results obtained from a hardware prototype verify both battery equalization and multi-level DC output functions. Compared with conventional methods, the proposed CPO-Mamba-MLP-PVC strategy reduces the balancing time by 18.03% and increases the energy utilization rate to 90.7%. Full article

Distributed energy systems open up a vast field of research in power electronics. Local solar power generation requires DC-DC converters that adapt the energy generated by the panels to on-site distribution buses. In addition, the control of the power converter to obtain the maximum possible energy from the solar source is crucial for the correct deployment of these distributed grids. In this work, system-level solutions are proposed for this application as follows: On the one hand, the use of novel resonant forward-flyback converters allows for a higher energy density than that of a conventional flyback and more relaxed withstand voltages on the switching elements. On the other hand, the implementation of maximum power point tracking algorithms for solar energy using Edge AI enables the deployment of algorithms that maximize the energy obtained locally. These improvements are shown by means of a prototype demonstrator, using cutting-edge microcontrollers and the implementation of a DC-DC power converter based on the proposed topology. Full article

The large-scale integration of distributed energy resources poses numerous challenges to distribution networks. At present, multi-terminal flexible interconnection has become a key development trend for active distribution networks integrated with high-penetration distributed energy resources. Conventional unified power flow controllers (UPFCs) are mainly designed for high-voltage transmission networks and lack distribution-adapted control strategies, making it difficult for them to meet the networking requirements for multi-terminal interconnection. Moreover, most existing studies still focus on two-terminal devices, soft open points and improved UPFC topologies for transmission networks. Existing multi-port schemes mostly adopt only shunt-side structures without series compensation branches, which fail to regulate voltage magnitude and phase difference, thus failing to suppress closing inrush currents and mitigate busbar voltage sags. Meanwhile, such schemes struggle with three-phase imbalance, feeder load imbalance and bidirectional power flow fluctuations in distribution networks, and lack adaptive power allocation capability among multiple ports. To solve the above problems, this paper proposes a VSC-based series–shunt hybrid multi-terminal flexible interconnection converter. The proposed topology consists of one series-side VSC and n − 1 shunt-side VSCs connected through a common DC capacitor; it removes the shunt-side transformer, and effectively reduces cost and volume, while achieving phase shifting, voltage regulation and power flow control. Meanwhile, dual closed-loop PI cross-decoupling control and a flexible closing strategy are adopted to independently regulate the active and reactive power of each feeder, adapt to three-phase imbalance and load imbalance conditions, suppress inrush currents, and realize flexible power mutual support among multiple ports, thereby significantly enhancing adaptability to distribution networks. Full article

Constrained multi-objective optimization (CMOP) is especially difficult when the feasible region is very narrow. In this study, we introduce Integrated-CMOEA, a clear and structured framework that uses structure-aware seeding, a projection-based repair operator, dual-population evolution, adaptive parameter control, and reference vector archiving. For the DC2-DTLZ1 problem, the repair step is handled as a continuous one-dimensional root-finding problem along a feasible search ray. This method provides clear rules for restoring feasibility when a valid bracket is found. Our results show that the method quickly finds and maintains strict feasibility and produces a well-distributed set of solutions near the constrained Pareto front. In tests with five independent runs, Integrated-CMOEA outperformed four other CMOEAs in both IGD and hypervolume. An ablation study shows that deterministic repair is the main reason for its strong performance on this narrow-band benchmark. Integrated-CMOEA is a reliable framework for analytically structured narrow-band CMOPs, though it has some limits when applied more broadly. Full article

When a line short-circuit fault occurs in a DC distribution network, the fault current rises quickly and affects a wide range, jeopardizing the safe operation of the system. In order to locate the fault quickly and accurately, this study proposes a fault localization method based on the Variational Mode Decomposition (VMD) and Bidirectional Long Short-Term Memory (Bi-LSTM) networks. First, the nonlinear relationship between the intrinsic principal frequency and fault distance is analyzed; then, the intrinsic principal frequency of the faulty traveling wave is extracted by using VMD, and the nonlinear relationship between the spectral energy of the principal frequency of the intrinsic frequency and the fault distance is fitted by training the Bi-LSTM network incorporating the attention mechanism. Finally, in response to the issue that a small amount of fault data in practical engineering is difficult to support the amount of data required for deep learning, a transfer learning method is used to locate the fault in the target domain. A small sample test of the target domain is carried out using the migration learning method. The experimental results show that the proposed method has high localization accuracy and good resistance to over-resistance and noise; compared with the traditional network training, the localization error based on migration learning is smaller, and the network convergence effect is better. Full article

Soil preferential flow plays a crucial role in governing hydrological cycles and soil moisture distribution in mountain forests. This makes it essential for understanding subsurface water movement and for guiding hillslope hydrological management. In this study, soil preferential flow, soil properties, and root characteristics across three slope positions on a Larix gmelinii var. principis-rupprechtii (Mayr) Pilger (larch) plantation hillslope in the Liupan Mountains were systematically observed to reveal the spatial patterns and formation mechanisms of hillslope soil preferential flow. The results showed that soil preferential flow development followed a distinct spatial pattern across the slope positions, with the mid-slope exhibiting the most developed preferential flow characteristics. The comprehensive preferential flow index further quantified this spatial variation, ranking the slope positions as mid-slope > upper slope > lower slope. Different soil structural properties exerted varying influences on preferential flow. Macropore-related properties (low bulk density and high porosity and saturated conductivity) promoted most preferential flow, whereas aggregate-related properties (high organic matter and water-stable aggregates) suppressed it. The influence of root characteristics on preferential flow was also dual. Root length density generally promoted preferential flow (e.g., DC, LI, and UniFr), whereas root surface area density primarily exerted an inhibitory effect (e.g., LI, UniFr, and total stained area TotStAr). This study clarifies how slope position modulates preferential flow through soil and root characteristics, offering insights for slope-specific hydrological understanding and targeted soil and water conservation practices. Full article

This paper presents a distributed V2G-enabled multiport DC charging system with a hierarchical charging management strategy. Unlike conventional architectures based on centralized power converter cabinets, the proposed system distributes bidirectional power converters within individual multiport dispensers, each equipped with a local charging power management device. This architecture improves system scalability, fault tolerance, and operational flexibility while enabling vehicle-level charging and V2G services. A hierarchical control framework is introduced, consisting of high-level optimal charging scheduling, mid-level power coordination among distributed dispensers, and low-level converter control. Key elements include modular power units that can be dynamically configured and expanded, providing a cost-effective and adaptable solution for growing EV markets. Experimental results obtained from a 45 kW modular DC charging prototype demonstrate an efficiency improvement of up to 2% at rated power compared to a non-modular charger. In contrast, the optimized charging strategy achieves an overall charging cost reduction of approximately 11% and a peak load demand reduction of up to 31%. Furthermore, stable bidirectional power flow, effective power sharing, and total harmonic distortion within regulatory limits are experimentally validated during both charging and V2G operation. The prototype is implemented to validate the proposed charging system in the laboratory environment. Full article

Objectives: This study aimed to investigated the role of Giardia extracellular vesicles (EVs) in intercellular communication and to evaluated their potential as vaccine candidates. Methods: The immunomodulatory effects of Giardia EVs were assessed in mouse macrophages and human monocyte-derived dendritic cells (Mo-DCs), with a particular focus on key inflammatory signaling pathways. In vivo immunogenicity was evaluated following EV administration, and the antigenic composition of EV cargo was characterized by proteomic analysis. Results: Giardia EVs activated pro-inflammatory signaling pathways in mouse macrphages, including SAPK/JNK, ERK1/2, and NF-κB. This activation was associated with IκB-α degradation and nuclear translocation of p65. Furthermore, EV stimulation significantly upregulated the expression of pro-inflammatory genes, including Il1β, Il6, Il4, Ptgs2, Nos2, and Tnf, with log₂ fold changes ranging from 3.9 to 15.8. Consistently, EVs increased iNOS protein expression (28–45%) and nitrite production (9.6–12.3-fold). In human Mo-DCs, Giardia EVs promoted cellular maturation, as evidenced by increased expression of MHC-II, CD80, and CD86, and enhanced T-cell proliferation with a Th1-skewed profile. In vivo immunization induced antigen-specific antibody responses, with IgG subclass distribution indicative of a balanced Th1/Th2 response. Proteomic analysis identified immunoreactive EV-associated proteins, including elongation factor 1-alpha, α-7.3 giardin, tubulin, and variant surface proteins (VSPs), which are well-established antigens in Giardia infection, with prominent bands observed at approximately 22 kDa and 50 kDa. Conclusions: Collectively, these findings demonstrate that Giardia EVs modulate innate immune responses in vitro, elicit antigen-specific humoral immunity in vivo, and contain conserved immunogenic proteins. These properties support their potential as a promising cell-free vaccine platform against giardiasis. Full article

Within the framework of consistent couple stress theory (CCST) and employing Hamilton’s principle, we derive a Galerkin weak formulation to analyze the three-dimensional (3D) size-dependent free vibration characteristics of a simply supported, functionally graded (FG) magneto-electro-elastic (MEE) doubly curved (DC) microscale shell subjected to a uniform temperature change. Incorporating the differential reproducing kernel (DRK) interpolants into the weak formulation, we further develop an element-free Galerkin (EFG) method. The microscale shell of interest is composed of two-phase MEE materials, and its material properties are assumed to vary through its thickness according to a power-law distribution of the volume fractions of the constituents. The results show that the natural frequency solutions obtained using the EFG method are in excellent agreement with the reported 3D solutions for laminated composite and FG-MEE macroscale plates, with the material length-scale parameter and the inverse of the curvature radii set to zero. The effects of the material length-scale parameter, temperature change, inhomogeneity index, and mid-surface radius and length-to-thickness ratios on the FG-MEE microscale shell’s free vibration characteristics in a thermal environment are examined and appear to be significant. Full article

The capacitance of the DC link is an important variable for the prediction of remaining useful life and failures in frequency inverters. The direct measurement of the DC-link capacitance in inverters operating under load is technically challenging and generally impractical. Recently, a great focus has been given to data-based soft sensors for estimating this variable. These methods, however, are evaluated based only on the estimate errors, and do not take into account the metrological aspects of these estimators. This paper proposes an uncertainty analysis method based on Monte Carlo simulations and bootstrapping that can be applied to all recently published methods for end-of-life (EOL) estimation based on data-driven regression and neural networks. A state-of-the-art model of EOL monitoring based on capacitance estimation was evaluated using the proposed framework, and an experimental study with a frequency converter drive for a brushless DC motor was performed, considering multiple output frequencies, loads and DC-link capacitance conditions. The output distributions are not symmetrical and show that the variable with the most significant impact in the propagated uncertainty is the DC link voltage. The results show confidence interval widths ranging from 12 μF to 61 μF, with wider confidence intervals obtained at higher power setpoints. Full article

This research paper presents Volvo SmartCell, an AC battery technology that integrates modular multilevel converters and battery cells to form a unified system for electric vehicle propulsion and power supply. The research work addresses the broader challenge of reducing driveline cost and complexity by replacing traditional components such as inverters, onboard chargers, centralized DC/DC converters, vehicle control units and many more. SmartCell uses distributed Cluster Boards comprised of H-bridges which are controlled via wireless communication to generate AC voltage, deliver redundant low voltage power, and support cell level protection mechanisms. The prototype testing demonstrates that the system can supply traction power by engaging clusters according to the required voltage depending on motor speed, achieve AC grid charging by synthesizing sinusoidal voltages without a dedicated charger, and provide autonomous DC/DC operation through cluster level voltage regulation. Simulations further indicate that multilevel voltage generation can reduce switching losses and improve electric machine efficiency compared to conventional systems. Additional benefits include active cell balancing, support for mixed cell chemistries, and high redundancy through multiple independent power branches. Challenges remain in wireless bandwidth limitations and cost optimization of Cluster Boards. Ongoing development aims to enhance communication robustness and validate safety for non-isolated grid charging. Full article

Background: Spare parts distribution networks (DNs) play a strategic role in retailers’ profitability. Among DN configuration decisions, selecting the optimal stock deployment policy—centralised, decentralised, or hybrid inventory allocation across distribution centres (DCs)—critically affects service levels and logistics costs. This decision becomes more complex with additive manufacturing (AM) as an alternative to conventional manufacturing (CM). While AM enables production with shorter lead times, its higher costs alter stock deployment cost-effectiveness. Given the complexity of joint stock deployment and manufacturing decisions, retailers require decision support systems (DSSs). Methods: To address this need, we develop a DSS through a three-step methodology: (i) a mathematical model evaluates logistics costs across different stock deployment policies and manufacturing technologies; (ii) parametric analysis tests the model across 2000 realistic scenarios; (iii) Random Forest trained on this dataset predicts optimal solutions, with SHapley Additive exPlanations (SHAP) interpreting post hoc recommendations. Results: The DSS achieves 93.4% prediction accuracy—outperforming (+16.4%) the only comparable literature DSS (77%)—while explaining recommendations. SHAP reveals that AM and CM unit costs dominate decision-making, followed by backorder costs. Conclusions: Beyond individual spare parts recommendations, the DSS provides guidelines enabling retailers to maintain cost-effective DNs aligned with evolving customer needs and to plan valuable investments in AM. Full article

In light of the global issue of “Carbon Neutrality”, a high proportion of renewable energy integrated into modern power systems has become the key to energy strategic transformation, which has escalated the demand for high-gain, high-power converters for DC energy conversion. In this paper, a non-isolated double-layer multi-port parallel-connected high-gain DC–DC conversion system has been proposed. The system consists of two energy layers: the upper layer is designed as a non-isolated high-gain three-port DC conversion topology, which includes two energy inputs and one output port, and the bottom layer is a three-port constant current output module. The output ports of these layers are connected in parallel, while the input ports are independent. Thus, both high output voltage gain and power capacity were fulfilled for the renewable power application condition. The system is capable of operating in both input-parallel–output-parallel (IPOP) and multi-input–independent-output-parallel (MIIOP) modes, thereby enabling multi-port high-gain DC power conversion. Detailed analysis of the operation strategies under a switching cycle for both energy layers is presented. A small signal was introduced to establish the mathematical model of both energy topologies. In order to simultaneously regulate the output voltage and achieve dynamic current sharing between the layers, an adaptive current-sharing control strategy was developed based on the established system models. The proposed control strategy can control the output voltage through the upper-layer topology and dynamically allocates output current between the layers based on the output power level, which will effectively enhance the system’s power rating. The simulation mode was built in the PSIM environment, open-loop simulations were carried out for obtaining system characteristics, and closed-loop simulations were conducted for control efficiency validation. Finally, a 2000-W experimental prototype was developed based on the digital control center dsPIC33FJ64GS606. Open-loop and closed-loop experiments were carried out for system performance evaluation. Both simulation and experimental results successfully evaluated the power transfer performance and control system performance of the proposed system, and a peak efficiency of 95.7% under 10 times voltage gain was achieved. Full article