Search

Precisely predicting natural gas prices (NGPs) is important because it can provide the necessary decision-making basis for energy scheduling, planning and control. However, NGPs are affected by many factors and exhibit the characteristics of nonlinearity and randomness, which makes accurate predictions challenging. Therefore, in this paper, the information gain of multisource data and the global optimization ability of the gray wolf algorithm are used to build a multifactor-driven NGP hybrid forecasting model to improve the prediction performance. First, the emotional tendency and readability of news text are extracted and calculated by using VADER and textstat tools, respectively. Then the network search index is filtered and integrated by using the correlation coefficient method and the CRITIC method to form alternative variables of multisource data (news and search index). Second, the gray wolf optimization algorithm is used to find and determine the best key parameter group in long short-term memory model. Finally, the spot price of natural gas in Henry Hub from March 1, 2012 to February 28, 2022 is selected as the prediction object, and multi-scenario numerical experiments are carried out to verify the effectiveness of the proposed model. The ablation experiment results show that the information gain brought by multisource data can effectively improve the prediction effect of NGPs. Furthermore, the proposed model has the best prediction performance in different scenarios and can be regarded as a promising prediction tool.

Abstract Prostate cancer (PC) is one of the most common cancers in men and becoming the second leading cause of cancer fatalities. At present, the lack of effective strategies for prognosis of PC patients is still a problem to be solved. Therefore, it is significant to identify potential gene signatures for PC patients’ prognosis. Here, we summarized 71 different prognostic gene signatures for PC and concluded 3 strategies for signature construction after extensive investigation. In addition, 14 genes frequently appeared in 71 different gene signatures, which enriched in mitotic and cell cycle. This review provides extensive understanding and integrated analysis of current prognostic signatures of PC, which may help researchers to construct gene signatures of PC and guide future clinical treatment.

BackgroundTo evaluate the methodological quality, report quality, and evidence quality of meta-analysis (MA) and systematic review (SR) on the efficacy of probiotics in the treatment of rheumatoid arthritis (RA).MethodsDatabases were used to identify eligible SRs/MAs until February 12, 2024. The methodological quality of the studies was assessed using AMSTAR-2 tool, the quality of the literature reports was scored using PRISMA checklists, and the quality of the evidence was graded using GRADE system.ResultsSeven reviews including 21 outcomes were included. Methodological quality of the included reviews was of general low, and the entries with poor scores were 2, 4, and 7. By PRISMA checklists, there were some reporting deficiencies, and quality problems were mainly reflected in the reporting registration and protocol, comprehensive search strategy and additional analysis. GRADE results elevated the quality of evidence to be low or very low overall.ConclusionsProbiotics may have a therapeutic effect on RA, based on the evidence provided by the SRs/MAs in this overview. Nevertheless, there is still a lack of conclusive evidence due to methodological limitations in the included research. To make trustworthy judgments regarding the efficacy of probiotics in the treatment of RA, more large-scale, high-quality randomized controlled trials are still required.

This paper studies the distributed convex optimization of bipartite containment control problem for a class of higher order nonlinear multi-agent systems with uncertain states. For the optimization problem, the penalty function is constructed by summing the local objective function of each agent and combining the penalty term formed by the adjacency matrix. For the unknown nonlinear function and unpredictable states in the system, this paper construct radial basis function Neural-networks and state observer for approaching, respectively. In order to avoid “explosion of complexity,” under the framework of Lyapunov function theory, we propose the dynamic surface control (DSC) technology and design the distributed adaptive backstepping neural network controller to ensure all the signals remain semi-global uniformly ultimately bounded in the closed-loop system and all agents can converge to the convex hull containing each boundary trajectory as well as its opposite trajectory different in sign. Simulation results confirm the feasibility of the proposed control method.

Abstract Aim The current overview on published systematic reviews (SRs) and meta-analysis (MAs) aimed to systematically gather, evaluate, and synthesize solid evidence for using fecal microbiota transplantation (FMT) to treat ulcerative colitis (UC). Methods Relevant articles published before January 2023 were collected from Web of Science, Embase, PubMed, and Cochrane Library. Two authors used Assessment of Multiple Systematic Reviews 2 (AMSTAR-2) tool, PRISMA checklists, and Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system were applied by two authors to independently evaluate the methodological quality, reporting quality, and evidence quality, respectively. Re-meta-analysis on the primary RCTs was conducted after excluding overlapping randomized controlled trials (RCTs). Results Six SRs/MAs involving 12 primary RCTs and 544 participants were included. According to the AMSTAR-2 tool and PRISMA checklist, methodological quality and reporting quality of the included studies was overall satisfactory. The evidence quality of a great majority of outcomes was rated as moderate to high according to the GRADE system. Compared to placebo, the re-meta-analysis found a great advantage of use FMT in inducing combined clinical and endoscopic remission (OR 3.83 [2.31, 6.34]), clinical remission (3.31 [2.09, 5.25]), endoscopic remission (OR 3.75 [2.20, 6.39]), clinical response (OR 2.56 [1.64, 4.00]), and endoscopic response (OR 2.18 [1.12, 4.26]). Pooled data showed no significant difference in serious adverse events between patients receiving FMT and those receiving placebo (OR 1.53 [0.74, 3.19]). Evidence quality of the outcomes derived from re-meta-analysis was significantly higher after overcoming the limitations of previous SRs/MAs. Conclusion In conclusion, moderate- to high-quality evidence supported a promising use of FMT to safely induce remission in UC. However, further trials with larger sample size are still required to comprehensively analyze the delivery route, total dosage, frequency, and donor selection in FMT.

This article investigates a penalty-based distributed optimization algorithm of bipartite containment control for high-order nonlinear uncertain multi-agent systems with state constraints. The proposed method addresses the distributed optimization problem by designing a penalty function in the form of a quadratic function, which is the sum of the global objective function and the consensus constraint. Moreover, the observer is presented to address the unmeasurable state of each agent. Radial basis function neural networks (RBFNN) are employed to approximate the unknown nonlinear functions. Then, by integrating RBFNN and dynamic surface control (DSC) techniques, an adaptive backstepping controller based on the barrier Lyapunov function (BLF) is proposed. Finally, the effectiveness of the suggested control strategy is verified under the condition that the state constraints are not broken. Simulation results indicate that the output trajectories of all agents remain within the upper and lower boundaries, converging asymptotically to the global optimal signal.

In order to realize the automatic identification of typical defects in transmission lines, a typical defect identification method for transmission lines based on You Only Look Once (YOLO)v5 algorithm is proposed, which has the advantages of low missing detection rate and false detection rate. Firstly, a transmission line defect image dataset is constructed for three typical defects: bird’s nest defect, insulator defect and shakeproof hammer defect, and the corresponding image labeling strategy is formulated according to the defect characteristics. Secondly, this paper introduces the network structure of YOLOv5 in detail. For the sake of further improving the neural network’s ability to recognize the visual defects of transmission lines, the attention mechanism and small target detection layer are introduced into YOLOv5 neural network. Finally, this paper design transmission line defect recognition cases based on three kinds of typical defects, and the proposed method is compared with the recognition methods based on Faster Region based Convolutional Neural Network (RCNN) and Single Shot MultiBox Detector (SSD) in terms of the proposed performance indexes (missing detection rate and false detection rate). The results show that the missing detection rate and false detection rate of the YOLOv5-based identification method are much lower than those of the Faster RCNN and SSD-based identification methods, and the improved YOLOv5 network recognition rate is higher, which is significant for reducing the workload of transmission line inspection personnel.

High-speed railway, as one of the most important forms of transportation, have been developed rapidly throughout the world. As the people’s living condition improves, the energy demand in China’s transport sector has grown dramatically and will keep increasing in the short term. In order to support the realization of ’ energy conservation ’ vision, it is urgent to adopt energy technology to change the structure of traditional high-speed railway system and realize the green, high efficiency and high elasticity transformation of high-speed railway system. High-speed railway will cause voltage fluctuation of the traction network during driving, which may affect the safety and reliability of high-speed railway in severe cases. In order to improve the voltage fluctuation of traction network caused by high-speed railway, this paper proposes a comprehensive voltage compensation system (VCCS) and its control strategy for high-speed railway traction network. Firstly, the causes of voltage fluctuation in traction network are analyzed, and the existing compensation methods at home and abroad are introduced. Then, the topology and compensation principle of high-speed railway traction network voltage compensation system are introduced, and the corresponding control strategy is proposed. Finally, the correctness of the theoretical analysis is verified by simulation experiments. The experimental results show that the VCCS proposed in this paper can ensure that the high-speed train can maintain full power operation under various typical working conditions, and effectively improve the voltage fluctuation of the traction network.

Voltage source converter based high voltage direct current transmission (VSC-HVDC) is widely adopted in the power system with new energy sources, but with the problem of fast rise of fault current. Magnetic saturation fault current limiter (MSFCL) suppresses the rise of short-circuit current by increasing the inductance value, which has the advantages of high speed and no additional control. However, the change of inductance will affect the detection of VSC-HVDC system fault, may leading to missed or incorrect removal of the fault and causing harm. Based on this problem, this paper proposes a fault detection method used in VSC-HVDC system considering MSFCL, which has fast detection speed, high sensitivity and reliability. The proposed method is robust to short-circuit resistance variation and can locate faults external and internal. Firstly, we establish the short-circuit equivalent circuit of VSC-HVDC system. Then we establish the differential equation and solve it, to obtain the analytical expression of voltage across MSFCL. Furthermore, we proposed a short circuit fault detection method based on the rise rate of the voltage across MSFCL. Finally we establish a four port VSC-HVDC system simulation model to prove that the method is effective. The results show that compared with traditional methods, the proposed method has faster detection speed. The proposed method is independent of the power flow direction, can identify the short circuit fault with large short-circuit resistance of 500 Ω and can discriminate the faulty branch from the healthy ones accurately.

With the development of society, the demand for electric energy is growing day by day. However, the energy centers and load centers are geographically distributed in a reverse direction, so the power supply and demand are unbalanced. High voltage transmission lines are characterized by long distance and large capacity, and the power flow problems are increasingly prominent. In order to flexibly adjust the line power flow, improve the comprehensive utilization of grid assets, and improve the transmission capacity of the system, this paper analyzes the principle of double core symmetrical phase-shift transformer (DS-PST) and the application of power flow regulation. Firstly, the basic principle of phase shifting transformer is analyzed in detail, and the equivalent mathematical model of DS-PST and the calculation of main parameters are derived. Impedance coefficient and excitation coefficient are introduced to modify the parameter design of DS-PST. Then, an electromagnetic simulation model is established to verify the effectiveness of the design method. Finally, a system simulation model is built to verify the power flow regulation effect of DS-PST by taking 500 kV UHV power grid and IEEE standard multi-node system as examples. DS-PST can transfer the active power transmitted by the lines with high load rate to the lines with low load rate, which makes the power flow distribution of the system more balanced and effectively improves the transmission capacity of the power system.

In the field of high-precision physical field detection, measurements based on magnetic signals are crucial due to their exceptional accuracy, sensitivity, and stability. Superconducting Quantum Interference Devices (SQUIDs), with their ultra-high sensitivity, have become key in detecting minute changes in magnetic flux. However, with increasing demands for higher precision, further enhancing device performance under quantum constraints remains a significant challenge. This study improved the precision of SQUID sensors by optimizing the geometry of microscale washers using the physical response of superconducting films under micromachining technologies and quantum constraints. Our research extensively examined the effects of square, octagonal, and circular washers on the magnetic field response, shielding currents, and inductance. Experimental results showed that, compared to traditional square washers, octagonal washers significantly enhanced sensor sensitivity and efficiency by minimizing edge magnetic flux and optimizing current distribution. Notably, all observed inductance values exceeded predictions based on traditional empirical formulas, with square washers showing the highest average relative error of 80.8%, while circular and octagonal washers had errors of 65.31% and 66.43%, respectively. This breakthrough not only lays a new theoretical foundation for the design of SQUID sensors but also provides robust evidence for enhancing magnetic field detection through microscale technological innovation.

Valve reactors (VR) with multiple magnetic cores are important electrical components in ultra-high voltage direct current systems. The impact current and high-order harmonics during their operation can lead to additional losses and temperature rise in the valve reactors, posing a threat to insulation aging, and even causing serious incidents such as combustion and explosions. Therefore, it is necessary to accurately quantify and analyze the loss characteristics of valve reactors under different magnetic materials. This article first theoretically analyzes the electromagnetic and temperature characteristics during the actual operation of VR; then, it analyzes and calculates the magnetic field distribution and electromagnetic losses of a single magnetic core. Finally, it establishes a three-dimensional equivalent model of VR and conducts transient electromagnetic-thermal coupled finite element simulation to reveal the magnitude and spatial distribution of VR temperature changes.

Installing a three-phase saturated core fault current limiter (TSFCL) is an effective method to limit the increasing short-circuit current in high-voltage alternating current (HVAC) systems. However, the traditional TSFCL uses silicon steels as its working material for the iron core, resulting in poor current-limiting effects, requiring a large DC excitation current, and having a slow response speed. Nanocrystalline alloys have advantages such as a lower saturation point, higher permeability in the unsaturated zone, and a steep B–H curve, making them highly suitable for TSFCL’s applications. However, their poor capability which withstands fault hindered their large-scale commercialization. Therefore, this paper proposes a novel hybrid magnetic material based on TSFCL (HMTFCL), where the materials of the working limbs are replaced by nanocrystalline alloys. Compared to TSFCL, the DC excitation current of HMTFCL decreases by 60.5%. And, the HMTFCL reduces the peak short-circuit current by 23%. Last, the magnetic flux intensity inside the working limb of HMTFCL is reduced to zero more quickly.

Based on an adaptive neural control scheme, this paper investigates the consensus problem of random Markov jump multi-agent systems with full state constraints. Each agent is described by the fractional-order random nonlinear uncertain system driven by random differential equations, where the random noise is the second-order stationary stochastic process. First, in order to deal with the unknown functions with Markov jump parameters, a radial basis function neural network (RBFNN) structure is introduced to achieve approximation. Second, for the purpose of keeping the agents’ states from violating the constraint boundary, the tan-type barrier Lyapunov function is employed. By using the stochastic stability theory and adopting the backstepping technique, a novel adaptive neural control design method is presented. Furthermore, to cope with the differential explosion problem in the design course, the extended state observer (ESO) is developed instead of neural network (NN) approximation or command filtering techniques. Finally, the exponentially noise-to-state stability in the mean square is analyzed rigorously by the Lyapunov method, which guarantees the consensus of the considered multi-agent systems and all the agents’ outputs are bounded in probability. Two simulation examples are provided to verify the effectiveness of the suggested control strategy.

In the context of carbon peaking and carbon neutrality goals, the integration of a large number of renewable energy sources may trigger significant tidal changes, leading to transmission congestion, wind and light abandonment, power oscillation, voltage and frequency fluctuations, etc. A phase-shifting transformer is a cost-effective and reliable power flow control equipment, but its key parameters lack systematic design methods. Based on the equivalent model of phase-shifting transformers, detailed design principles and methods have been proposed, and the configuration method of winding turns has been improved to facilitate calculation and control strategy formulation. The regulation effect of the phase-shifting transformer designed through simulation of power flow regulation in a typical 500 kV network is simulated. By adjusting the phase-shifting transformer, the power flow of heavy load lines can be transferred to light load lines, optimizing the power flow distribution and improving the transmission capacity of the cross-section.

Abstract High‐voltage withstand tests are essential for electric equipment like power transformers, electric cable lines, gas insulated switchgears etc. The partial discharge (PD) measurement for such equipment under applied high voltage is also required at the same time. Pulse Width Modulation (PWM)‐based variable frequency power supply (VFPS) finds wide applications in the series resonance high‐voltage testing circuits. However, the steep rising and falling voltage edges in the PWM process will produce large amount of partial discharge interference in a wide spectrum range, which will confuse the real partial discharge signal of the device and lead to the wrong estimation of the insulation status. This paper proposes a new VFPS based on the high‐efficiency linear power amplifier without PD interference. The topology and principle of the VFPS are given and discussed. A prototype rated at 232 V/35 A was designed and constructed to verify the feasibility of the proposed VFPS. Physical experiments were carried out on the prototype.

Abstract Mitochondrial dysfunction of neurons is the core pathogenesis of incurable Parkinson's disease (PD). It is crucial to ameliorate the mitochondrial dysfunction of neurons for boosting the therapy of PD. Herein, the remarkable promotion of mitochondrial biogenesis to ameliorate mitochondrial dysfunction of neurons and improve the treatment of PD by using mitochondria‐targeted biomimetic nanoparticles, which are Cu2‐xSe‐based nanoparticles functionalized with curcumin and wrapped with DSPE‐PEG2000‐TPP‐modified macrophage membrane (denoted as CSCCT NPs), is reported. These nanoparticles can efficiently target mitochondria of damaged neurons in an inflammatory environment, and mediate the signaling pathway of NAD+/SIRT1/PGC‐1α/PPARγ/NRF1/TFAM to alleviate 1‐methyl‐4‐phenylpyridinium (MPP+)‐induced neuronal toxicity. They can reduce the mitochondrial reactive oxygen species, restore mitochondrial membrane potential (MMP), protect the integrity of mitochondrial respiratory chain, and ameliorate mitochondrial dysfunction via promoting mitochondrial biogenesis, which synergistically improve the motor disorders and anxiety behavior of 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)‐induced PD mice. This study demonstrates that targeting mitochondrial biogenesis to ameliorate mitochondrial dysfunction has a great potential in the treatment of PD and mitochondria‐related diseases.

High-speed railway power system consists of traction power system and station power system. High-speed railway locomotives generate electrical energy that is fed back to the grid during regenerative braking, and the grid company adopts the policy of ignoring the reverse transmission, which wastes energy on the railway system. In this paper, based on the interconnection of 10kV station power system and 27.5 kV traction power system, a hybrid energy storage system (HESS) composed of supercapacitors (SCs) and batteries is added to recover the regenerative braking energy, and roof photovoltaic (PV) is installed in railway station to reduce the power consumption of the system, and an energy management strategy with grid peak shaving characteristics is proposed. Then, the optimal dispatching model of high-speed railway power system is established, and the daily operation cost of the system is reduced by using the mixed integer linear programming method. Finally, according to the actual data of a domestic railway station, the proposed optimization method is verified. The results show that the strategy not only reduces the total daily operation cost, but also effectively reduces the peak power purchase of the peak load. The scheme proposed in this paper saves 11.86% of the daily operation cost.

As the key equipment to protect the thyristor of HVDC converter valve, the vibration problem of anode saturable reactor (ASR) is very prominent. Its long-term vibration will even cause the failure of the whole converter valve system. From the perspective of multi-physical field coupling, this paper establishes the solid model of ASR, considers the influence of Maxwell electro-magnetic field and magnetostrictive effect, numerically calculates the magnetic field and vibration of iron core, analyzes the contribution of two forces to vibration, and expounds the vibration phenomenon of iron core at different positions. In order to evaluate the effectiveness of the simulation, a single iron core vibration experiment is designed and compared with the single iron core simulation. This study can predict the vibration level of ASR core and provide theoretical basis and calculation method for vibration reduction in ASR design stage.

With the development of new energy, the proportion of wind power in the global power production structure is increasing year by year, and it has broad development prospects. This article discusses a new type of wind-powered permanent magnet eddy current heating device, which converts excess wind energy into heat energy and stores it in a heat storage medium, so as to achieve the function of storing heat energy. Thermal energy can be directly supplied to users and can also be used for thermal power generation when the power supply is insufficient, which is of practical significance to alleviating the problems of energy shortage and large amount of wind curtailment. Based on the law of electromagnetic induction and eddy current phenomenon, this paper establishes a model of permanent magnet eddy current heating device, and then simulates and analyzes the permanent magnet eddy current heating device to improve the heating power and material utilization of the device. The focus is on the influence of stator groove type, the number of stator slots and the thickness of the stator on the heating power. Finally, the simulation analysis of the permanent magnet eddy current heating device before and after the optimization is carried out in MATLAB. The simulation results prove the effectiveness of the optimization.

This paper investigates the distributed optimization problem (DOP) for fractional high-order nonstrict-feedback multiagent systems (MASs) where each agent is multiple-input–multiple-output (MIMO) dynamic and contains uncertain dynamics. Based on the penalty-function method, the consensus constraint is eliminated and the global objective function is reconstructed. Different from the existing literatures, where the DOPs are addressed for linear MASs, this paper deals with the DOP through using radial basis function neural networks (RBFNNs) to approximate the unknown nonlinear functions for high-order MASs. To reduce transmitting and computational costs, event-triggered scheme and quantized control technology are combined to propose an adaptive backstepping neural network (NN) control protocol. By applying the Lyapunov stability theory, the optimal consensus error is proved to be bounded and all signals remain semi-global uniformly ultimately bounded. Simulation shows that all agents reach consensus and errors between agents’ outputs and the optimal solution is close to zero with low computational costs.

In response to the limitations of traditional double rice cropping models, this study constructed five typical rice planting models in the middle reaches of the Yangtze River, namely “Chinese milk vetch-early rice-late rice (CK/CRR), Chinese milk vetch—early rice—sweet potato || late soybean (CRI), rapeseed—early rice—late rice (RRR), rapeseed—early rice—sweet potato || late soybean (RRI) and potato—early rice—late rice (PRR)” to study the annual emission characteristics of greenhouse gases under different planting models. The results showed the following: (1) From the perspective of total yield in two years, the CRI treatment reached its maximum, which was significantly higher than that of other treatments by 9.30~20.29% in 2019 (p < 0.05); in 2020, except for the treatment of RRI, it was significantly higher than other treatments by 20.46~30.23% (p < 0.05). (2) The cumulative emission of CH4 in the double rice treatment is generally higher than that in paddy-upland rotation treatment, while the cumulative emission of N2O in the paddy-upland rotation treatment is higher than that in the double rice treatment, but the total amount is much lower than the cumulative emission of CH4. Therefore, CH4 emissions from rice fields still occupy most of the GHGs. (3) The global warming potential (GWP) and greenhouse gas emission intensity (GHGI) of different planting patterns in rice fields in 2020 were higher than those in 2019, and the GWP and GHGI of double rice cropping treatment is higher than that of paddy-upland rotation treatments. During the two years, the GWP of CRR treatment reached its maximum and was significantly higher than that of other treatments by 48.28~448.90% and 34.43~278.33% (p < 0.05). The GHGI of CRR was significantly higher than that of CRI and RRI by 3.57~5.4 and 1.4~3.5 times (p < 0.05). Based on the comprehensive performance of greenhouse gas emissions over the two experimental years, RRI and CRI have shown good emission reduction effects, which can significantly reduce greenhouse gas emissions from paddy fields, are conducive to reducing global warming potential and greenhouse gas emission intensity and conform to the development trend of “carbon neutrality”. Therefore, considering high-yield, low-temperature chamber gas emissions, the Chinese milk vetch—early rice—sweet potato || late soybean model performs well and has the best comprehensive benefits. It is of great significance for optimizing the rice field planting mode in the middle reaches of the Yangtze River.

Investigating the spatiotemporal variation characteristics of aerosol optical depth (AOD) and its driving factors is essential for assessing atmospheric environmental quality and alleviating air pollution. Based on a 22-year high-resolution AOD dataset, the spatiotemporal variations of AOD in mainland China and ten national urban agglomerations were explored based on the Mann–Kendall trend test and Theil–Sen median method. Random forest (RF) and multiscale geographically weighted regression (MGWR) were combined to identify the main driving factors of AOD in urban agglomerations and to reveal the spatial heterogeneity of influencing factors. The results showed that areas with high annual average AOD concentrations were mainly concentrated in the Chengdu–Chongqing, Central Plains, Shandong Peninsula, and Middle Yangtze River urban agglomerations. Southern Beijing–Tianjin–Hebei and its surrounding areas revealed the highest AOD pollution during summer, whereas the worst pollution during the remaining three seasons occurred in the Chengdu–Chongqing urban agglomeration. Temporally, except for the Ha-Chang and Mid-Southern Liaoning urban agglomerations, where the average annual AOD increased, the other urban agglomerations showed a decreasing trend. Among them, the Central Plains, Middle Yangtze River, Guanzhong Plain, and Yangtze River Delta urban agglomerations all exhibited a decline greater than 20%. According to the spatial trends, most urban agglomerations encompassed much larger areas of decreasing AOD values than areas of increasing AOD values, indicating that the air quality in most areas has recently improved. RF analysis revealed that PM2.5 was the dominant factor in most urban clusters, followed by meteorological factors. MGWR results show that the influencing factors have different spatial scale effects on AOD in urban agglomerations. The socioeconomic factors and PM2.5 showed strong spatial non-stationarity with regard to the spatial distribution of AOD. This study can provide a comprehensive understanding of AOD differences among urban agglomerations, and it has important theoretical and practical implications for improving the ecological environment and promoting sustainable development.

Abstract The regenerative braking energy generated during the braking of high‐speed trains affects the power quality of the power grid. Recovery of regenerative braking energy is problem that needs to be solved urgently. The regenerative braking energy of high‐speed railway features high power and high energy. It is difficult to recover it only by using high power density supercapacitors or high energy density batteries. In this paper, a hybrid energy storage system (HESS) composed of supercapacitors and lithium‐ion batteries and its optimal configuration method are proposed for the purpose of obtaining maximum economic benefits for railroad systems. Then the economic benefits when using the HESS and the single energy storage system are compared from the perspective of whether the regenerative braking energy is fully recycled or not. Finally, a simulation analysis with actual load of a high‐speed railway station is performed. The highest benefit is achieved when the regenerative braking energy is partially recovered by the HESS, which can save 3% of the total cost per day and pay back the cost in eight years.

Developing high-performing oxygen evolution reaction (OER) electrocatalysts under high-current operation conditions is critical for future commercial applications of alkaline water electrolysis for clean energy generation. Herein, we prepared a three-dimensional (3D) bimetallic oxyhydroxide hybrid grown on a Ni foam (NiFeOOH/NF) prepared by immersing Ni foam (NF) into Fe(NO3)3 solution. In this unique 3D structure, the NiFeOOH/NF hybrid was composed of crystalline Ni(OH)2 and amorphous FeOOH evenly grown on the NF surface. As a bimetallic oxyhydroxide electrocatalyst, the NiFeOOH/NF hybrid exhibited excellent catalytic activity, surpassing not only the other reported Ni–Fe based electrocatalysts, but also the commercial Ir/C catalyst. In situ electrochemical Raman spectroscopy demonstrated the active FeOOH and NiOOH phases involved in the OER process. Profiting from the synergy of Fe and Ni catalytic sites, the NiFeOOH/NF hybrid delivered an outstanding OER performance under challenging industrial conditions in a 10.0 mol∙L−1 KOH electrolyte at 80 °C, requiring potentials as small as 1.47 and 1.51 V to achieve the super-high catalytic current densities of 100 and 500 mA∙cm−2, respectively.

This paper investigates the fractional order chaotic systems synchronization with input delay. To reduce the utilization of communication resources and achieve system synchronization, an adaptive neural network backstepping sliding mode controller is proposed based on event-triggered scheme without Zeno behavior. To avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously, the fractional order dynamic surface control (DSC) technology is introduced into the controller. The sliding term is introduced to enhance robustness. The Pade delay approximation method is used to handle the input delay, which can reduce the analysis complexity of fractional order chaotic systems with input delay. The unknown nonlinear functions and uncertain disturbances are approximated by the RBF neural network. An observer is used for state estimation of the fractional order system. By applying the Lyapunov stability theory, we can prove that the all closed-loop signals are bounded. Examples and simulations prove the feasibility of the proposed control method.

This paper proposes an adaptive neural network (NN) output-feedback synchronization controller for the nonlinear stochastic systems driven by Lévy processes, which consist of Wiener and compensated Poisson process. By employing the generalized It&ohat;’s formula combined with Lyapunov function method, it is proved that the proposed controller can ensure that all signals of closed system are bounded in probability. Under the backstepping control framework of stochastic process including Lévy noises, the event-triggered control technology is used to reduce the utilization of communication resources. Moreover, the command filtered control technology is introduced into the controller to avoid “explosion of complexity” and obtain the derivatives for virtual control functions continuously. Simulation proves the feasibility of the proposed control method.

EDI is a hot topic in the research of multimodal transportation informatization, which determines the exchange level of intermodal transportation information. However, its high cost, large system coupling degree and low performance threshold cannot adapt to mass data exchange in high concurrent environment. Therefore, a decentralized, scalable, distributed and efficient data exchange system is formed. It plays a key role in realizing the comprehensive sharing of interdepartmental intermodal information in the cloud environment. In order to solve the problem of mismatching between application load and computing resource capacity and realize on-demand resource allocation and low carbon emission, this paper proposes to build an Extensible EDI system (XEDI) based on MSA and studies the scaling mechanism in container environment. Based on the resource scheduling characteristics of container cloud and considering the distribution and heterogeneity of intermodal cloud computing platform from the perspective of resource allocation, the automatic scaling mechanism of XEDI is established, the scaling model is established, and the automatic scaling algorithm is proposed. For Dominant Resource Fairness for XEDI (XDRF) resource allocation algorithm and Dominant Resource Fairness for XEDI (CXDRF) based on carbon considering energy consumption, the CXDRF algorithm is proved by quantitative experiments to achieve system performance optimization on the basis of ensuring system reliability and effectively reducing energy consumption. XEDI can not only meet the demand of dynamic load and improve service quality, but also reduce resource occupation and save energy by releasing virtual resources when resource utilization rate is low. It has great research significance and practical value for mass data application under low energy consumption conditions.

Abstract Cost-effective and stable electrocatalysts with ultra-high current densities for electrochemical oxygen evolution reaction (OER) are critical to the energy crisis and environmental pollution. Herein, we report a superaerophobic three dimensional (3D) heterostructured nanowrinkles of bimetallic selenides consisting of crystalline NiSe2 and NiFe2Se4 grown on NiFe alloy (NiSe2/NiFe2Se4@NiFe) prepared by a thermal selenization procedure. In this unique 3D heterostructure, numerous nanowrinkles of NiSe2/NiFe2Se4 hybrid with a thickness of ~ 100 nm are grown on NiFe alloy in a uniform manner. Profiting by the large active surface area and high electronic conductivity, the superaerophobic NiSe2/NiFe2Se4@NiFe heterostructure exhibits excellent electrocatalytic activity and durability towards OER in alkaline media, outputting the low potentials of 1.53 and 1.54 V to achieve ultra-high current densities of 500 and 1000 mA cm−2, respectively, which is among the most active Ni/Fe-based selenides, and even superior to the benchmark Ir/C catalyst. The in-situ derived FeOOH and NiOOH species from NiSe2/NiFe2Se4@NiFe are deemed to be efficient active sites for OER.

Fast emerging fault current levels in high voltage direct current (HVDC) systems has always been a significant obstacle to building a safer and more reliable grid. Inductive fault current limiters (FCLs), compared with its resistive counterpart, are very effective in restricting the fault rising speed that causes major damage during the whole fault process. In this study, a comprehensive review of the methods used for building inductive type FCLs in HVDC systems is presented. The fault current characteristics of the modern HVDC system is discussed to obtain the basic requirements for the FCL. On the basis of different technological domains, various inductive-type FCL topologies and devices are well categorized and analyzed. After the overall discussion and comparison, representative works, as well as new progress and future prospects, are conveyed in detail. One may find the content of this study helpful as a detailed literature review or a practical technical guidance of this field.

The large current generated by starting directly of super large capacity and high voltage induction motor would have a huge impact on the grid as well as the motor itself. The variation of the power factor and electromagnetic torque during direct start of motors with different capacity and voltage levels are obtained. Aiming at the problem that the secondary impact of auto-transformer starter is too large and the cost of magnetic control starter is too high, the auto-transformer and magnetic control soft start method of super large capacity and high voltage motor is proposed and the basic working principle is analyzed. The calculation formula of cost for magnetic control soft starter and auto-transformer and magnetic control soft starter is deduced, and specific examples are analyzed and compared. It is concluded that the choice of auto-transformer with appropriate tapping ratio can greatly reduce the cost of auto-transformer and magnetic control soft starter compared with the other one. Finally, the simulation and experiment results show that the start method can effectively avoid secondary current impact and constrain the motor starting current to less than 2.5 times the rated current.

This paper proposes an observer-based adaptive neural network backstepping sliding mode controller to ensure the stability of switched fractional order strict-feedback nonlinear systems in the presence of arbitrary switchings and unmeasured states. To avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously, the fractional order dynamic surface control (DSC) technology is introduced into the controller. An observer is used for states estimation of the fractional order systems. The sliding mode control technology is introduced to enhance robustness. The unknown nonlinear functions and uncertain disturbances are approximated by the radial basis function neural networks (RBFNNs). The stability of system is ensured by the constructed Lyapunov functions. The fractional adaptive laws are proposed to update uncertain parameters. The proposed controller can ensure convergence of the tracking error and all the states remain bounded in the closed-loop systems. Lastly, the feasibility of the proposed control method is proved by giving two examples.

In this article, the distributed optimization problem is studied for a class of fractional-order nonlinear uncertain multi-agent systems (MASs) with unmeasured states. Each agent is represented through a system with unknown nonlinearities, unmeasurable states and a local objective function described by a quadratic polynomial function. A penalty function is constructed by a sum of local objective functions and integrating consensus conditions of the MASs. Radial basis function Neural-networks (RBFNNs) and Neural networks (NN) state observer are applied to approximate the unknown nonlinear dynamics and estimate unmeasured states, respectively. By combining the NN state observer and the penalty function, and the stability theory of the Lyapunov function, the distributed observer-based adaptive optimized backstepping dynamic surface control protocol is proposed to ensure the outputs of all agents asymptotically reach consensus to the optimal solution of the global objective function. Simulations demonstrate the effectiveness of the proposed control scheme.

In this study, an observer based sliding mode control (SMC) scheme is proposed for vibration suppression of subsonic piezo-composite plate in the presence of time varying measurement delay by using the piezoelectric patch (PZT) actuator. Firstly, the state space form of the subsonic piezo-composite plate model is derived by Hamilton’s principle with the assumed mode method. Then an state observer involving time varying delay is constructed and the sufficient condition of the asymptotic stability is derived by using the Lyapunov-Krasovskii function, descriptor method and linear matrix inequalities (LMIs) for the state estimation error dynamical system. Subsequently, a sliding manifold is constructed on the estimation space. Then an observer-based controller is synthesized by using the SMC theory. The proposed SMC strategy ensures the reachability of the sliding manifold in the state estimate space. Finally, the simulation results are presented to demonstrate that the proposed observer-based controller strategy is effective in active aeroelastic control of subsonic piezo-composite plate involving time varying measurement delay.

With the development of power systems, the power flow problem of transmission line is becoming more and more prominent. This paper presents a power flow regulation method based on phase shifting transformer (PST). Firstly, the working principle and performance of PST are analyzed. Then, the simulation model of BPA multi node system is established. PST access reduces the line imbalance to less than 8%. On this basis, considering the influence of saturation effect and leakage reactance, a PST suitable for 220 kV power grid is designed. Three different working conditions are simulated by PSCAD software. Under normal working conditions and N-1 conditions, PST can increase the transmission limit of the ring network section by more than 20%. When a short-circuit fault occurs, PST can also suppress the fault current. For 220 kV practical projects, unified power flow controller (UPFC) has faster response speed and stronger performance, but PST is more economical and reliable, and the equipment cost is 49.86% lower than that of UPFC. The power flow regulation method based on PST has good steady-state effect. It can improve the utilization efficiency of power grid assets and optimize the power flow distribution in a short time and at low cost.

In recent years, major large ports in China have realized the business informatization of rail-water intermodal transportation. However, the overall development level of intermodal transportation informatization has been restricted to a great extent due to the unbalanced development of intermodal transportation informatization in different regions, the rigid system architecture, the low degree of information sharing, and the lack of data management and analysis methods. Combined with the structure and business characteristics of intermodal transportation information systems, adopting cloud computing and Big Data technology, we propose an intermodal transportation information process with waybill as the information carrier and FPMS as the service fulcrum in this paper. Illustrated by the example of China’s container export process, this paper explores a series of key technical issues in the cloud environment, such as application management, business information sharing, and Big Data processing, at different levels of the construction of the rail water transport cloud platform, combined with its business characteristics, and makes experimental analysis on the relevant models to verify the feasibility of the reconstruction of the rail water transport cloud platform. It can provide theoretical and practical support for the development of rail water intermodal informatization in China.

In this study, the microstructure of TC1/1060/6061 composites manufactured by explosive welding was investigated using experiments and numerical simulations. The results showed that the two interfaces of the TC1/1060/6061 composites exhibited an overall linear bonding interface without defects such as macroscopic cracks or pores. A melting layer caused by the adiabatic compression of air was observed, and the overall welding quality of the composites was good. There were no intermetallic compounds observed at the TC1/1060 interface, and the diffusion area was short, which formed a metallurgical bond. After heat treatment, the grains on the base plate and interlayer side of the composites formed a cubic recrystallized texture, while the grains on the flyer plate side developed a fine-grained structure. The microhardness of the base plate and flyer plate was higher closer to the interface due to the process hardening effect, while the microhardness of the interlayer remained stable. The formation process of these two interfaces was analyzed by numerical simulations, and jetting was observed at the 1060/6061 interface. The TC1/1060 interface in the numerical simulations showed a linear morphology, and the 1060/6061 interface showed a microwave morphology.

This paper studies the containment control problem for a class of fractional order nonlinear multiagent systems in the presence of arbitrary switchings, unmeasured states, and quantized input signals by a hysteresis quantizer. Under the framework of the Lyapunov function theory, this paper proposes an event-triggered adaptive neural network dynamic surface quantized controller, in which dynamic surface control technology can avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously. Radial basis function neural networks (RBFNNs) are used to approximate the unknown nonlinear functions, and an observer is designed to obtain the unmeasured states. The proposed distributed protocol can ensure all the signals remain semi-global uniformly ultimately bounded in the closed-loop system, and all followers can converge to the convex hull spanned by the leaders’ trajectory. Utilizing the combination of an event-triggered scheme and quantized control technology, the controller is updated aperiodically only at the event-sampled instants such that transmitting and computational costs are greatly reduced. Simulations compare the event-triggered scheme without quantization control technology with the control method proposed in this paper, and the results show that the event-triggered scheme combined with the quantization mechanism reduces the number of control inputs by 7% to 20%.

This paper presents a multi-objective Pareto optimal method for allocation of fault current limiters based on an immune algorithm, which takes into account two objectives of the cost and fault current mitigation effect. A sensitivity factor calculation method based on the rate of fault current mitigation is proposed to reduce the search space and improve the efficiency of the algorithm. In this approach, the objective functions related to the cost and fault current mitigation effect are established. A modified inversion operator based on equal cost is proposed to converge to global optimal solutions more effectively. The proposed algorithm is tested on the IEEE 39-bus system, and obtains the Pareto optimal solutions, from which the user can select the most suitable solutions according to the preferences and relative importance of the objective functions. Simulation results are used to verify the proposed method.

With the continuous expansion of power grid capacity, the problem of short-circuit current exceeding the standard is becoming increasingly serious. Fault current limiter is a promising solution and is gradually becoming a research hotspot. In this study, fault current limiters are classified into four categories. And saturated-core fault current limiters are emphatically introduced, including its working principle and comparison with the other three categories. Saturated core fault current limiters are divided into four branches according to the ways leading the core saturated. A comprehensive review of the research activities and emerging technologies of saturated-core fault current limiters for AC power systems is presented in this study. The working principle and typical structure of DC-biased-, permanent-magnet-, superconducting- and hybrid-type saturated-core fault current limiters are introduced. The advantages and disadvantages of four types of saturated core fault current limiters are compared in detail from the aspects of current-limiting performance, iron core size and DC magnetomotive force. Real grid application examples of some types of devices are presented, as well as new progress in the techniques, are covered and discussed in detail. One may find the content of this study helpful as a detailed literature review or as practical technical guidance.

The large current generated by a direct start of the super-large-capacity high-voltage induction motor would have a huge impact on the power grid as well as the motor itself. Traditional soft starters have the shortcomings of discontinuous adjustment, voltage sags, sudden torque mutation, secondary current impact and high cost. To resolve this issue, the authors propose a novel coupled autotransformer and magnetic-control (CATMC) soft-start method. The structure of the new CATMC soft starter combines the functions of the autotransformer and magnetic control reactor via an innovative electric and magnetic circuit design. In this study, the authors analyse the magnetic circuit structure and working principles of the CATMC soft starter. Then, to validate its principle and performance, the authors conduct a simulation study using ANSYS software and design and test an 18 MW/10 kV CATMC soft starter prototype. The simulation results demonstrate that the CATMC soft starter effectively avoids secondary current impact and constrains the motor starting current to

In the magnetic field analysis of magnetic devices using a ferrite core, such as a pulse transformer, the frequency-domain analysis is often carried out using the measured complex permeability under different frequency range. However, the nonlinear magnetic characteristics cannot be considered in the frequency-domain analysis because of the harmonics caused by it cannot be represented. The nonlinear magnetic characteristics can be considered in the time-domain analysis, but suitable constant conductivity and permittivity taking account of the microstructure of ferrite core, which can represent the measured complex permeability under different frequencies, needs to be investigated for the time-domain analysis. In this paper, the effective permeability of a toroidal ferrite core is tried to be demonstrated by using the linear ac steady state magnetic field analysis taking account eddy currents and displacement currents. It is shown that the measured permeability can be realized roughly by using the modified constant conductivity and permittivity. The nonlinear time-domain magnetic field analysis can be carried out using the modified constant conductivity and permittivity obtained from this paper.

To achieve economical compensation for the huge-capacity negative sequence currents generated by high-speed railway load, an electromagnetic hybrid compensation system (EHCS) and control strategy is proposed. The EHCS is made up of a small-capacity railway static power conditioner (RPC) and a large-capacity magnetic static var compensator (MSVC). Compared with traditional compensation methods, the EHCS makes full use of the SVC's advantages of economy and reliability and of RPC's advantages of technical capability and flexibility. Based on the idea of injecting a negative sequence, the compensation principle of the EHCS is analyzed in detail. Then the minimum installation capacity of an EHCS is theoretically deduced. Furthermore, a constraint optimization compensation strategy that meets national standards, which reduces compensation capacity further, is proposed. An experimental platform based on a digital signal processor (DSP) and a programmable logic controller (PLC) is built to verify the analysis. Simulated and experimental results are given to demonstrate the effectiveness and feasibility of the proposed method.

The South China Block (SCB) is a globally important metallogenic district containing numerous W-Sn deposits. Extensive studies of W-polymetallic deposits in this region have greatly improved our understanding of the petrogenesis, geochronology and metallogenesis of these systems. However, studies on the mobilization of ore-forming elements between mineralization- and alteration-related minerals using in situ analyses are rare. Using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), we analyzed W, Pb, Mo and Bi concentrations in silicate minerals and scheelite from granites and skarns associated with the Shizhuyuan W-polymetallic deposit in the Nanling Range in the SCB. Data show that muscovitized biotite in granites contains high W contents. Pb mainly occurs in K-feldspar and plagioclase in granites and epidote and scheelite in skarns. Bi mainly occurs in epidote in skarns. Scheelite in skarns contains high W and Mo contents. Pb isomorphously substitutes K or Ca in silicate minerals and scheelite. W isomorphously substitutes Ti in biotite. Mo isomorphously substitutes W in scheelite and occurs as W-bearing submicroscopic inclusions in minerals with low contents. Bi isomorphously substitutes Pb when the Pb content is relatively high and occurs as Bi-bearing micro or submicroscopic inclusions in minerals when the Pb content is low. Biotite and feldspar are altered in a magmatic-hydrothermal process, W enriched in biotite, Pb enriched in feldspar and the W-, Pb-, Mo- and Bi-bearing submicroscopic inclusions are excluded from minerals and released to the magmatic-hydrothermal fluids. Large amounts of W are precipitated in scheelite when the fluids come in contact with carbonate rocks to form skarn, while a few contents of Pb, Mo and Bi are distributed in skarn minerals. Thus, large amounts of Pb, Mo, Bi and residual W remain in the fluids, which results in the formation of a W-Sn-Mo-Bi massive skarn ore.

In order to protect high voltage direct current (HVDC) system from destructive consequences caused by fault current, a novel concept of HVDC system fault current limiter (DCSFCL) was proposed previously. Since DCSFCL is based on saturable core reactor theory, iron core becomes the key to the final performance of it. Therefore, three typical kinds of soft magnetic materials were chosen to find out their impact on performances of DCSFCL. Different characteristics of materials were compared and their theoretical deductions were carried out, too. In the meanwhile, 3D models applying those three materials were built separately and finite element analysis simulations were performed to compare these results and further verify the assumptions. It turns out that materials with large saturation flux density value Bs like silicon steel and short demagnetization time like ferrite might be the best choice for DCSFCL, which can be a future research direction of magnetic materials.

To develop mechanical circuit breaker in high voltage direct current (HVDC) system, a fault current limiter is required. Traditional method to limit DC fault current is to use superconducting technology or power electronic devices, which is quite difficult to be brought to practical use under high voltage circumstances. In this paper, a novel concept of high voltage DC transmission system fault current limiter (DCSFCL) based on saturable core was proposed. In the DCSFCL, the permanent magnets (PM) are added on both up and down side of the core to generate reverse magnetic flux that offset the magnetic flux generated by DC current and make the DC winding present a variable inductance to the DC system. In normal state, DCSFCL works as a smoothing reactor and its inductance is within the scope of the design requirements. When a fault occurs, the inductance of DCSFCL rises immediately and limits the steepness of the fault current. Magnetic field simulations were carried out, showing that compared with conventional smoothing reactor, DCSFCL can decrease the high steepness of DC fault current by 17% in less than 10ms, which verifies the feasibility and effectiveness of this method.