Search Results (615)

Multiphase electric drives (EDs) offer important advantages for high-demand applications. However, they require appropriate high-performance control strategies. In this context, finite-control-set model predictive control (FCS-MPC) emerges as a promising strategy, offering a notable flexibility to implement multiobjective regulation schemes. When applied to multiphase EDs, standard FCS-MPC exhibits degraded current quality at low and medium control frequencies. Multivector solutions address this issue by properly combining multiple voltage vectors within a single control period to create the so-called virtual voltage vectors (VVVs). In this way, this approach achieves flux and torque regulation while minimizing current injection into the secondary subspace. For this purpose, the VVV synthesis typically prioritizes active vectors with low contribution in secondary subspaces, avoiding the average deception phenomenon. VVV solutions commonly enable an open-loop regulation of secondary currents. Nevertheless, the absence of closed-loop control in the secondary subspace hinders the compensation of nonlinearities, machine asymmetries, and unbalanced conditions in the ED. Considering this scenario, this work implements a multivector FCS-MPC recovering closed-loop control for the secondary subspace. The capability of the proposal to mitigate secondary current injection and compensate for possible dissymmetries is experimentally evaluated in a six-phase ED. Its performance is compared against a benchmark technique in which secondary current regulation is handled in open-loop mode. The proposed control solution significantly improves in current quality, achieving a reduction in harmonic distortion of 54% at medium speed. Full article

The paper proposes a parallel transformerless (TL) static synchronous series compensator (SSSC) for the control of power flow along the power distribution lines under balanced or unbalanced voltages. This new SSSC configuration offers the advantages of a fast dynamic response, light weight, and high efficiency. By connecting multiple SSSCs in parallel, the current rating is increased, which improves the grid power transfer capabilities and flexibility. However, there may be circulating current flowing between the parallel-connected inverters, hence causing losses. A modified model predictive control scheme is thus developed, which ensures that the proposed SSSC accurately tracks the reference currents while effectively mitigating the circulating current. The model and cost function of the controller are derived and analyzed in the paper. A real-time simulation of a power line with the parallel TL SSSC controlled by a hardware-in-loop (HIL) DSP is developed to validate the performance of this device under both balanced and unbalanced line voltages. Full article

The rapid evolution of modern power systems, driven by the large-scale integration of renewable energy sources and the emergence of smart grids, presents new challenges in maintaining grid stability, power quality, and control reliability. As critical interfacing elements, three-phase pulse width modulation (PWM) converters must now ensure resilient and efficient operation under increasingly adverse and dynamic grid conditions. This paper proposes an adaptive neural network-based virtual flux (VF) estimator for sensorless predictive direct power control (PDPC) of PWM converters under nonideal grid voltage conditions. The proposed estimator is realized using an adaptive linear neuron (ADALINE) configured as a quadrature signal generator, offering robustness against grid voltage disturbances such as voltage unbalance, DC offset and harmonic distortion. In parallel, a PDPC scheme based on the extended pq theory is developed to reject active-power oscillations and to maintain near-sinusoidal grid currents under unbalanced conditions. The resulting VF-based PDPC (VF-PDPC) strategy is validated via real-time simulations on the OPAL-RT platform. Comparative analysis confirms that the ADALINE-based estimator surpasses conventional VF estimation techniques. Moreover, the VF-PDPC achieves superior performance over conventional PDPC and extended pq theory-based PDPC strategies, both of which rely on physical voltage sensors, confirming its robustness and effectiveness under non-ideal grid conditions. Full article

This paper proposes a nonlinear control strategy for a microgrid, comprising a PV generator, wind turbine, battery, solid oxide fuel cell (SOFC), electrolyzer, and a three-phase four-leg voltage source inverter (VSI) with an LC filter. The microgrid is designed to supply unbalanced AC loads while maintaining high power quality. To address chattering and enhance control precision, a super-twisting algorithm (STA) is integrated, outperforming traditional PI, IP, and classical SMC methods. The four-leg VSI enables independent control of each phase using a dual-loop strategy (inner voltage, outer current loop). Stability is ensured through Lyapunov-based analysis. Scalar PWM is used for inverter switching. The battery, SOFC, and electrolyzer are controlled using integral backstepping, while the SOFC and electrolyzer also use Lyapunov-based voltage control. A hybrid integral backstepping–STA strategy enhances PV performance; the wind turbine is managed via integral backstepping for power tracking. The system achieves voltage and current THD below 0.40%. An energy management algorithm maintains power balance under variable generation and load conditions. Simulation results confirm the control scheme’s robustness, stability, and dynamic performance. Full article

Agriculture is fundamental to food security and environmental sustainability. Advancing its holistic ecological transformation can stimulate socioeconomic progress while fostering human–nature harmony. Utilizing provincial data from mainland China (2013–2022), this research establishes a multidimensional evaluation framework across four pillars: agricultural ecology, low-carbon practices, modernization, and productivity enhancement. Through comprehensive assessment, we quantify China’s low-carbon green agriculture (LGA) development trajectory and conduct comparative regional analysis across eastern, central, and western zones. As for methods, this study employs multiple econometric approaches: LGA was quantified using the TOPSIS entropy weight method at the first step. Moreover, multidimensional spatial–temporal patterns were characterized through ArcGIS spatial analysis, Dagum Gini coefficient decomposition, Kernel density estimation, and Markov chain techniques, revealing regional disparities, evolutionary trajectories, and state transition dynamics. Last but not least, Tobit regression modeling identified driving mechanisms, informing improvement strategies derived from empirical evidence. The key findings reveal the following: 1. From 2013 to 2022, LGA in China fluctuated significantly. However, the current growth rate is basically maintained between 0% and 10%. Meanwhile, LGA in the vast majority of provinces exceeds 0.3705, indicating that LGA in China is currently in a stable growth period. 2. After 2016, the growth momentum in the central and western regions continued. The growth rate peaked in 2020, with some provinces having a growth rate exceeding 20%. Then the growth rate slowed down, and the intra-regional differences in all regions remained stable at around 0.11. 3. Inter-regional differences are the main factor causing the differences in national LGA, with contribution rates ranging from 67.14% to 74.86%. 4. LGA has the characteristic of polarization. Some regions have developed rapidly, while others have lagged behind. At the end of our ten-year study period, LGA in Yunnan, Guizhou and Shanxi was still below 0.2430, remaining in the low-level range. 5. In the long term, the possibility of improvement in LGA in various regions of China is relatively high, but there is a possibility of maintaining the status quo or “deteriorating”. Even provinces with a high level of LGA may be downgraded, with possibilities ranging from 1.69% to 4.55%. 6. The analysis of driving factors indicates that the level of economic development has a significant positive impact on the level of urban development, while the influences of urbanization, agricultural scale operation, technological input, and industrialization level on the level of urban development show significant regional heterogeneity. In summary, during the period from 2013 to 2022, although China’s LGA showed polarization and experienced ups and downs, it generally entered a period of stable growth. Among them, the inter-regional differences were the main cause of the unbalanced development across the country, but there was also a risk of stagnation and decline. Economic development was the general driving force, while other driving factors showed significant regional heterogeneity. Finally, suggestions such as differentiated development strategies, regional cooperation and resource sharing, and coordinated policy allocation were put forward for the development of LGA. This research is conducive to providing references for future LGA, offering policy inspirations for LGA in other countries and regions, and also providing new empirical results for the academic community. Full article

Apologies can offer solace and compensate for intangible and emotional harm in social and legal contexts. In some areas of law, an apology offered by a defendant will be factored into the assessment of damages awarded to vindicate the plaintiff’s rights and compensate for loss. This is the case in Australia, the jurisdiction primarily considered in this article, and in many other jurisdictions. There is a danger, however, of assuming that because apologies are compensatory in some sense, they can be used as a basis to reduce damages in tort law more generally. Even though general damages for non-pecuniary loss in fault-based torts are incommensurate to a monetary amount, they are still intended to compensate for actual loss. Empowering defendants to reduce their damages exposure by apologizing might incentivize meaningful apologies which are valued by plaintiffs. It might also create perverse incentives for plaintiffs and defendants alike, further unbalancing a system in which plaintiffs are already at risk of under-compensation. And it raises uncomfortable questions of evidence, reciprocity, agency and expertise which are yet to be fully explored. We argue for these reasons that it is not currently defensible to reduce an award of general damages for negligence, especially for personal injuries, on the basis of an apology by the defendant. Full article

Background/Objectives: Optical genome mapping (OGM) has recently emerged as a new technology in the clinical cytogenomics laboratories. This methodology has the ability to detect balanced and unbalanced structural rearrangements using ultra-high molecular weight DNA. This article discusses the uses of this new technology in both constitutional and somatic settings, its advantages as well as opportunity for improvements. Methods: We reviewed the medical and scientific literature for methodology and current clinical uses of OGM. Results: OGM is a recent addition to the methods used in cytogenomics laboratories and can detect a wide range of structural and copy number variations across a plethora of diseases. Conclusions: Clinical cytogenomics is an important laboratory specialty for which various technologies have been validated over the last several decades to improve detection of copy number and structural variations and their association to human disease. OGM has proven to be a powerful tool in the arsenal of clinical laboratories and provides a unified workflow for the detection of chromosomal aberrations across a wide range of diseases. Full article

This study investigates the development of silver (Ag)-doped zirconia (ZrO₂) coatings deposited on 316LVM stainless steel via the unbalanced magnetron sputtering technique. The oxygen content in the Ar/O₂ gas mixture was systematically varied (12.5%, 25%, 37.5%, and 50%) to assess its influence on the resulting coating properties. In response to the growing demand for biomedical implants with improved durability and biocompatibility, the objective was to develop coatings that enhance both wear and corrosion resistance in physiological environments. The effects of silver incorporation and oxygen concentration on the structural, tribological, and electrochemical behavior of the coatings were systematically analyzed. X-ray diffraction (XRD) was employed to identify crystalline phases, while atomic force microscopy (AFM) was used to characterize surface topography prior to wear testing. Wear resistance was evaluated using a ball-on-plane tribometer under simulated prosthetic motion, applying a 5 N load with a bone pin as the counter body. Corrosion resistance was assessed through electrochemical impedance spectroscopy (EIS) in a physiological solution. Additionally, tribocorrosive performance was investigated by coupling tribological and electrochemical tests in Ringer’s lactate solution, simulating dynamic in vivo contact conditions. The results demonstrate that Ag doping, combined with increased oxygen content in the sputtering atmosphere, significantly improves both wear and corrosion resistance. Notably, the ZrO₂-Ag coating deposited with 50% O₂ exhibited the lowest wear volume (0.086 mm³) and a minimum coefficient of friction (0.0043) under a 5 N load. This same coating also displayed superior electrochemical performance, with the highest charge transfer resistance (38.83 kΩ·cm²) and the lowest corrosion current density (3.32 × 10⁻⁸ A/cm²). These findings confirm the high structural integrity and outstanding tribocorrosive behavior of the coating, highlighting its potential for application in biomedical implant technology. Full article

In recent years, with the development of science and technology and the transformation of economic structures, rubidium and cesium have gradually become indispensable rare metal resources as important materials for high-tech industries. However, the relationship between supply and demand of resources is unbalanced, industrial demand is much higher than production, and the rubidium and cesium resources in hard rock minerals such as traditional pegmatite minerals are no longer enough to support global scientific and technological upgrading. There is therefore an urgent need to expand sources of resource extraction and recovery to meet market demand. This paper summarizes the current feasible technologies for extracting rubidium and cesium from pegmatite minerals, silicate minerals, salt lake brines and other potential resources. Full article

With the increasing penetration of distributed generation and the diversification of electrical equipment, distribution networks face issues like three-phase unbalance and harmonic currents, while the voltage stability and inertia of the grid-connected system also decrease. A certain amount of energy storage is needed in a Distribution Static Synchronous Compensator (DSTATCOM) to manage power quality and actively support voltage and inertia in the network. This paper first addresses the limitations of traditional $dq0$ compensation algorithms in effectively filtering out negative-sequence twice-frequency components. An improved $dq0$ compensation algorithm is proposed to reduce errors in detecting positive-sequence fundamental current under unbalanced three-phase conditions. Second, considering the impedance ratio characteristics of the distribution network, while reactive power voltage regulation is common, active power regulation is more effective in high-resistance distribution networks. A grid-forming model-based active and reactive power coordinated voltage regulation method is proposed. This method uses synchronous control to establish a virtual three-phase voltage internal electromotive force, forming a comprehensive compensation strategy that combines power quality improvement and active voltage support, exploring the potential of energy storage DSTATCOM applications in distribution networks. Finally, simulation and experimental results demonstrate the effectiveness of the proposed control method. Full article

With the current acceleration of climate change, there is a global demand for sustainable development and carbon emission reduction. As a major link in the global supply chain, the logistics industry’s green and low-carbon transformation has become a critical breakthrough in achieving the objective of reducing carbon emissions. This study develops a multidimensional assessment index method for the green logistics level. The study selects 51 major economies worldwide from 2000 to 2022 as research subjects. The cloud model–entropy value–TOPSIS method is applied to measure the green logistics level. The results of the green logistics level are analyzed from the perspectives of developed and developing countries, and their spatiotemporal evolution characteristics are explored. The study shows that (1) the green logistics level in developed countries is relatively high, mainly due to policy-driven, core technology advantages. However, they continue to encounter issues, such as regional imbalance and excessive green costs. (2) The green logistics level in developing countries is in the middle to lower level, limited by technological dependence, outdated infrastructure, and so on. They are generally caught in a “high-carbon lock-in” situation. (3) From the perspective of time, the global level of green logistics shows a rising trend year by year. The peak of the kernel density curve of the green logistics level is characterized by an “I” shape. There is a significant disparity in each country’s green logistics level, although it is narrowing every year. (4) From the spatial perspective, the green logistics level in each country shows a rising trend year by year vertically, while the horizontal disparity between countries is enormous. The development of the green logistics level between continents is unbalanced. The study presents several recommendations, including boosting technology transfer, giving financial support, strengthening international cooperation, and developing green infrastructure, to promote the global logistics industry’s green and low-carbon transformation to accomplish sustainable development goals. Full article

The widespread integration of power electronic devices and renewable energy sources into power systems has significantly exacerbated voltage and current waveform distortion issues, where asymmetric loads—including single-phase nonlinear equipment and unbalanced three-phase power electronic installations—serve as critical harmonic sources whose inherent nonlinear and asymmetric characteristics increasingly compromise power quality. To enhance power quality management, this paper proposes a universal harmonic source modeling and operational state identification methodology integrating physical mechanisms with data-driven algorithms. The approach establishes an RL-series equivalent impedance model as its physical foundation, employing singular value decomposition and Z-score criteria to accurately characterize asymmetric load dynamics; subsequently applies Variational Mode Decomposition (VMD) to extract time-frequency features from equivalent impedance parameters while utilizing Density-Based Spatial Clustering (DBSCAN) for the high-precision identification of operational states in asymmetric loads; and ultimately constructs state-specific harmonic source models by partitioning historical datasets into subsets, substantially improving model generalizability. Simulation and experimental validations demonstrate that the synergistic integration of physical impedance modeling and machine learning methods precisely captures dynamic harmonic characteristics of asymmetric loads, significantly enhancing modeling accuracy, dynamic robustness, and engineering practicality to provide an effective assessment framework for power quality issues caused by harmonic source integration in distribution networks. Full article

State estimation in distribution power systems is increasingly challenged by the proliferation of distributed energy resources (DERs), bidirectional power flows, and the growing complexity of unbalanced network topologies. Physics-Informed Neural Networks (PINNs) offer a compelling solution by integrating machine learning with the physical laws that govern power system behavior. This paper introduces a PINN-based framework for state estimation in unbalanced distribution systems, leveraging available data and embedded physical knowledge to improve accuracy, computational efficiency, and robustness across diverse operating scenarios. The proposed method is evaluated on four IEEE test feeders—IEEE 13, 34, 37, and 123—using synthetic datasets generated via OpenDSS to emulate realistic operating scenarios, and demonstrates significant improvements over baseline models. Notably, the PINN achieves up to a 97% reduction in current estimation errors while maintaining high voltage prediction accuracy. Extensive simulations further assess model performance under noisy inputs and partial observability, where the PINN consistently outperforms conventional data-driven approaches. These results highlight the method’s ability to generalize under uncertainty, accelerate convergence, and preserve physical consistency in simulated real-world conditions without requiring large volumes of labeled training data. Full article

Land degradation neutrality is crucial for sustainable mining, necessitating a comprehensive assessment of mining and land restoration performance. Current assessments of mining development and land degradation neutrality are isolated. Therefore, this study formulated a comprehensive framework for economic development and land governance, integrating a Dynamic Network Directional Distance Function (DDF) model with structural equation modeling (SEM), using China’s mining development and land restoration governance as a case study, to evaluate the efficiency and its determinants of mining and land restoration systems. The findings are as follows: there are significant regional differences in mining efficiency; the overall land restoration efficiency is higher than mining efficiency; the development of the two stages is unbalanced, and there is no obvious linear correlation between efficiencies; policy and economic factors negatively impact both mining and land restoration efficiency; technological innovation strongly boosts mining efficiency but has a weaker effect on land restoration efficiency; and climate factors slightly hinder land restoration and mildly enhance mining. Therefore, comprehensively analyzing the mining-land restoration system and considering exogenous factors to internalize externalities are crucial for promoting ecological protection, achieving the LDN target in mining areas, and realizing harmonious human-nature development in China. 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