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Abstract The electrocatalytic reduction of nitrogenous waste offers a sustainable approach to producing nitrogen-containing chemicals. The selective synthesis of high-value hydroxylamine (NH2OH) is challenging due to the instability of NH2OH as an intermediate. Here, we present a rational electrocatalyst design strategy for promoting NH2OH electrosynthesis by suppressing the competing pathways of further reduction. We screen zinc phthalocyanines (ZnPc) with a high energy barrier for NH2OH reduction by regulating their intrinsic activity. Additionally, we discover that carbon nanotube substrates exhibit significant NH3-producing activity, which can be effectively inhibited by the high coverage of ZnPc molecules. In-situ characterizations reveal that NH2OH and HNO are generated as intermediates in nitrate reduction to NH3, and NH2OH can be enriched in the ZnPc electrode. In the H-cell, the optimized ZnPc catalyst demonstrates a Faradaic efficiency (FE) of 53 ± 1.7% for NH2OH with a partial current density exceeding 270 mA cm−2 and a turnover frequency of 7.5 ± 0.2 s−1. It also enables the rapid electrosynthesis of cyclohexanone oxime from nitrite with a FE of 64 ± 1.0%.

Abstract Background LACS (long-chain acyl-CoA synthetase) genes are widespread in organisms and have multiple functions in plants, especially in lipid metabolism. However, the origin and evolutionary dynamics of the LACS gene family remain largely unknown. Results Here, we identified 1785 LACS genes in the genomes of 166 diverse plant species and identified the clades (I, II, III, IV, V, VI) of six clades for the LACS gene family of green plants through phylogenetic analysis. Based on the evolutionary history of plant lineages, we found differences in the origins of different clades, with Clade IV originating from chlorophytes and representing the origin of LACS genes in green plants. The structural characteristics of different clades indicate that clade IV is relatively independent, while the relationships between clades (I, II, III) and clades (V, VI) are closer. Dispersed duplication (DSD) and transposed duplication (TRD) are the main forces driving the evolution of plant LACS genes. Network clustering analysis further grouped all LACS genes into six main clusters, with genes within each cluster showing significant co-linearity. Ka/Ks results suggest that LACS family genes underwent purifying selection during evolution. We analyzed the phylogenetic relationships and characteristics of six clades of the LACS gene family to explain the origin, evolutionary history, and phylogenetic relationships of different clades and proposed a hypothetical evolutionary model for the LACS family of genes in plants. Conclusions Our research provides genome-wide insights into the evolutionary history of the LACS gene family in green plants. These insights lay an important foundation for comprehensive functional characterization in future research.

In the event of a fault in the AC/DC distribution network with modular multilevel converter (MMC), the current will surge and have a large amplitude, which seriously threatens the secure and reliable operation of the distribution network. In order to handle the fault, this paper presents an integrated control and protection strategy for AC/DC distribution network, which is based on the active current limiting control (ACLC) and single-terminal fault identification and protection principle. Firstly, an ACLC technique utilizing virtual reactance is introduced to reduce the rising rate of fault current by real-time monitoring of fault current slope. Then, taking into account the impact of ACLC, the characteristics and dynamic deviation value of single terminal current are analyzed, and a fast fault area identification method is designed. Through the cooperation of circuit breakers, this method achieves the goal of fast fault isolation. Finally, the simulation model of AC/DC distribution network is built in PSCAD/EMTDC, where the ACLC described in this paper can reduce the average rising rate of fault current by 38.4%. Moreover, the efficacy of the suggested plan is verified under different fault situations.

The existing fault current analysis in distribution networks tend to ignore the impact of the control dynamics arising from AC/DC converters. In response to the abovementioned challenge, this paper introduces a novel fault current estimation calculation approach tailored for AC/DC distribution networks, specifically considering the control dynamics of Modular Multilevel Converters (MMC). The methodology commences with the simplified model of the AC/DC distribution networks. Subsequently, on the basis of the analysis for the control structure of MMC, the impact of various control dynamics on fault current is quantified. Then, the branch currents and node voltages are obtained through a set of voltage-current differential equations. To validate the proposed method, simulation verification is conducted using PSCAD/EMTDC. The calculation results of main branch currents demonstrate that the accuracy of the improved method is about 90%, which shows the effectiveness of the proposed method. Furthermore, the robustness of the presented method against the variations of voltage level, breaker delay, and transition resistance is validated, where its accuracy is over 80%.

The distribution network with high penetration of renewable energy such as wind and photovoltaic power has higher flexibility and power supply efficiency, but it also faces more faults and uncertainties. Traditional dynamic reconfiguration under fault conditions are still limited by problems such as low load recovery rate and strong decision conservatism. To overcome these challenges, this article proposes a dynamic reconstruction strategy for distribution network under fault conditions that takes into account multivariate uncertainty. Firstly, in response to the uncertainty of distributed power generation output and load demand in the distribution network, an interval prediction method is adopted to construct a uncertainty model for source and load side. Then, the Latin hypercube sampling method is used to generate multiple operation scenarios, and computational efficiency is improved by reducing scenario samples using Cholesky sorting principle and synchronous backpropagation reduction method. Finally, a robust dynamic reconstruction model based on mixed-integer second-order cone programming (MISOCP) is constructed, and the feasibility and robustness of the proposed dynamic strategy are verified using the improved IEEE-33 node system. Through analysis, the proposed method effectively addresses the risk factors in the operation, thus improving the safety and reliability of the distribution network.

In order to cope with the failure of existing fault analysis schemes for AC/DC distribution networks with a high proportion of distributed generations, this paper proposes a fault characteristic analysis method for AC/DC distribution networks that considers the influence of distributed generation control strategies. Firstly, a transient model for the AC/DC distribution network connected to distributed generations is built. Then, the fault characteristics of the AC/DC distribution network in different stages, such as the capacitor discharge stage, inductive renewal stage, and steady state stage, is analyzed. Finally, detailed simulation analysis is conducted using PSCAD/EMTDC to validate the effectiveness of the developed scheme by the superior approximation performance between simulated curves and calculated curves.

In the development of new-type power system, the flexible interconnected distribution network becomes a better inclination. With the continuous increase of wind power generation in the flexible interconnected distribution network, the frequency stability issue caused by the high randomness of wind power generation has become increasingly prominent. This paper suggests an advanced active power strategy of double-fed induction generators (DFIGs) based on modifying power tracking curves in the interconnected distribution network for smoothing out the fluctuations of the system frequency. To this end, the various power tracking operation is used to participate in power smoothing instead of maximum power tracking operation so as to fully utilize the large rotor inertia of the double-fed induction generators for smoothing out the fluctuations of the power output of double-fed induction generators and system frequency. The control gain for the various power tracking operation is determined by the instantaneous system frequency deviation and rotor speed of the DFIG. Based on the modified IEEE 14 power system, simulation results successfully proved that the suggested advanced active power strategy is benefit for reducing the fluctuations of the output power of the DFIG and suppressing the maximum system frequency deviations with the scenario of continuously varying wind speed conditions.

With the explosive growth of distributed renewable energy connected to the power system, the application of AC–DC hybrid distribution network with power electronic transformer (PET) becomes more and more extensive. An equivalent loss model is formulated from the perspective of the internal topology of PET. Then, a novel PET power flow model is established to obtain the relationship between the three ports. On this basis, reactive power of PV nodes connecting PET and distributed renewable generation is modified by establishing an equivalent impedance matrix, thus the forward–backward sweep load flow calculation method is improved for power flow calculation and volt/var control of distribution network. Different from traditional reactive optimization methods, a multi-objective reactive power optimization model considering the PET and two types of photovoltaic converters is established in this paper, with the targets of minimizing voltage deviation and power loss simultaneously. Finally, the numerical simulation shows the accuracy, rationality, and feasibility of the proposed method.

The scales of the power distribution networks in real-world power grids expand quickly while the network structures are becoming more and more complex. The power grid companies analyze the power distribution networks in different business scenarios with different topology models. In this work, we propose a hierarchical graph model to describe the medium-voltage distribution network (which is a typical power distribution network in power grids) based on homeomorphic transformation. The hierarchical graph model preserves the basic network topology described by the traditional Common Information Model (CIM). Firstly, the nodes in the distribution network topology are classified according to graph theory. Secondly, three typical business scenarios of distribution network topology analysis are summarized, and the original model is simplified by progressive dimensionality reduction method to meet the analysis requirements of different scenarios, the simplified method consists of three abstract levels: critical path, core path and minimal path, and can effectively reduce the space complexity of the model while maintaining the topological properties. Thirdly, a multi-level distribution network topology construction and mapping method based on the graph database is proposed. It is used to realize the rapid conversion and traceability between different levels of topology. Finally, a practical distribution network in a county is used as an example to verify the effectiveness of the proposed method in the aspects such as topology rendering and path searching. The evaluation indicates that the proposed model can visualize the distribution network intuitively. The model can also speed up the visualization and path searching significantly.

Abstract By integrating the increasing number of electric vehicles (EVs) in the existing multi‐terminal DC system, the new power lines construct can be reduced and the investment in distribution power equipment can be saved. The integration of EVs will affect the power transfer boundary of the system to a certain extent. It is necessary to ensure the normal performance of the system and the power supply for the EVs through the optimal configuration of system integration. The paper proposes the state‐space model of the low‐voltage multi‐terminal DC system, after which the influence of EV integration on the system power transfer boundary and the sensitivity of the power transfer boundary under the change of integration parameters are analysed. Furthermore, an optimization method of EV integration configuration considering the investment cost is proposed, which considers minimizing the system integration cost as the optimization goal and adopts the genetic algorithm for optimization solving. Finally, through the case verification and simulation analysis, the effectiveness of the method is verified, which can minimize the system integration cost and ensure power supply for EVs, without affecting the system power transfer boundary.

Short video hot spot classification is a fundamental method to grasp the focus of consumers and improve the effectiveness of video marketing. The limitations of traditional short text classification are sparse content as well as inconspicuous feature extraction. To solve the problems above, this paper proposes a short video hot spot classification model combining latent dirichlet allocation (LDA) feature fusion and improved bi-directional long short-term memory (BiLSTM), namely the LDA-BiLSTM-self-attention (LBSA) model, to carry out the study of hot spot classification that targets Carya cathayensis walnut short video review data under the TikTok platform. Firstly, the LDA topic model was used to expand the topic features of the Word2Vec word vector, which was then fused and input into the BiLSTM model to learn the text features. Afterwards, the self-attention mechanism was employed to endow different weights to the output information of BiLSTM in accordance with the importance, to enhance the precision of feature extraction and complete the hot spot classification of review data. Experimental results show that the precision of the proposed LBSA model reached 91.52%, which is significantly improved compared with the traditional model in terms of precision and F1 value.

There may be a commutation failure during a fault or start-up of the UHVDC inverter side. The law of commutation failure process in UHVDC converter is studied here. First, the cause of inverter commutation failures is briefly introduced. Then, the general law for the bridge arm conduction of the inverter in the process of the commutation failure is revealed. Finally, the system debugging recorded data of some commutation failures of Taizhou UHVDC inverter in China is used to verify the law. Research shows that the commutation failure will go through three stages which has obvious features: (i) the commutation failure stage, (ii) the bypass circuit formation stage, and (iii) the commutation failure recovery stage. In the last stage, the AC currents of two conducted phases increase instantly in opposite directions, which are easy to recognise. In the second stage, only the DC current increases, and the AC currents equal 0 approximately. Because of the three stages, the commutation failure valve number is easily recognised. The study on the law of commutation failure process lay the foundation for commutation failure process analysis and identification for relay protection.

With the continuous expansion of power grid capacity and growth of voltage levels, the transient ground potential rise (GPR) caused by the switchgear operation has become great threaten to the safety of the grid. In the startup operation of 500 kV part of Taizhou 1000 kV ultra-high voltage (UHV) substation, the electromagnetic lock installed in the switchgear filed was broken by the GPR in case of switchgear operation. There are two possible transmission paths of the GPR, one is the ground copper bar connecting the ground and the other is the control cable connecting the control cabinet and electromagnetic lock. In order to find out the transmission path of the electromagnetic disturbance, the experiment is carried out to distinguish the two possible paths. The waveform of the GPR in case of switchgear operation from different measuring points are recorded and compared, the results are analysed by comparing the signal characteristics and the transmission path is eventually diagnosed. Finally, the protective measures are proposed by wrapping the control wires with the conductive metal cube to reduce the influences of GPR. The outcomes in the study provide beneficial methods to analyse the GPR disturbance and positive guidance for the protection of locally installed equipment.

On the basis of briefly analysing the construction background, systemic function, and practice situation of large-scale source-grid load friendly interactive system and introducing real load shedding verification of the system, this paper proposed an effective strategy validation technique based on preset instruction release mode, a time test method of real load shedding control command transmission according to global GPS clock synchronisation technology, and a frequency measurement method according to zero-crossing detection and digital filter technology. These methods can accurately measure the system's control time and dynamic frequency on real load shedding. The real experimental results verified that quick load shedding time and frequency control effect when DC-blocking fault happens meet system expectations. It effectively verified the function design of large-scale source-grid-load friendly interactive system.

The unified power flow controller (UPFC) based on modular multilevel converter (MMC) is the most creative flexible ac transmission system (FACTS) device. In theory, the output voltage of the series MMC in MMC-UPFC can be regulated from 0 to the rated value. However, there would be relatively large harmonics in the output voltage if the voltage modulation ratio is small. In order to analyze the influence of MMC-UPFC on the harmonics of the power grid, the theoretical calculation method and spectra of the output voltage harmonics of MMC are presented. Subsequently, the calculation formulas of the harmonics in the power grid with UPFC are proposed. Based on it, the influence of UPFC on the grid voltage harmonics is evaluated, when MMC-UPFC is operated with different submodular numbers and voltage modular ratios. Eventually, the proposed analysis method is validated using digital simulation. The study results would provide guideline for the design and operation of MMC-UPFC project.

The multi-terminal AC/DC system will become one of the important forms of the future power grid. The negative impedance characteristic caused by the constant power load in the DC network will reduce the power transfer capacity between the terminals, especially when a grid fault occurs in AC system at any terminal. Energy storage has played an important role in improving the stability of AC and DC systems. This paper proposes an additional control method based on an energy storage system to improve system power transfer capacity with low cost. The state space model of two-terminal AC/DC system is established, and the feedback laws for additional control are further designed by Lyapunov theory. Furthermore, the additional control strategies based on the energy storage system is built, without changing the existing control system of each control object. Finally, the corresponding system simulation model is established by Matlab/Simulink for analysis and verification. The research results show that the proposed additional control method is effective. The power transfer limitation can be overcome by only adding small damping energy with the stable DC voltages under large disturbances, and the power transfer capacity between the terminals can be significantly improved with low control cost.

Network reconfiguration is of theoretical and practical significance to guarantee safe and economical operation of distribution system. In this paper, based on all spanning trees of undirected graph, a novel genetic algorithm for electric distribution network reconfiguration is proposed. Above all, all spanning trees of simplified graph of distribution network are found. Tie branches are obtained with spanning tree subtracted from simplified graph. There is one and only one switch open on each tie branch. Decimal identity number of open switch on each tie branch is taken as the optimization variable. Therefore, the length of chromosome is very short. Each spanning tree corresponds to one subpopulation. Gene operations of each subpopulation are implemented with parallel computing method. Individuals of offspring after gene operation automatically meet with radial and connected constraints for distribution network operation. Disadvantages of conventional genetic algorithm for network reconfiguration that a large amount of unfeasible solutions are created after crossover and mutation, which result in very low searching efficiency, are completely overcome. High calculation speed and superior capability of the proposed method are validated by two test cases.

In order to solve the large scale linear systems, backward and Jacobi iteration algorithms are employed. The convergence is the most important issue. In this paper, a unified backward iterative matrix is proposed. It shows that some well-known iterative algorithms can be deduced with it. The most important result is that the convergence results have been proved. Firstly, the spectral radius of the Jacobi iterative matrix is positive and the one of backward iterative matrix is strongly positive (lager than a positive constant). Secondly, the mentioned two iterations have the same convergence results (convergence or divergence simultaneously). Finally, some numerical experiments show that the proposed algorithms are correct and have the merit of backward methods.

A novel algorithm for automatic foreground extraction based on difference of Gaussian (DoG) is presented. In our algorithm, DoG is employed to find the candidate keypoints of an input image in different color layers. Then, a keypoints filter algorithm is proposed to get the keypoints by removing the pseudo-keypoints and rebuilding the important keypoints. Finally, Normalized cut (Ncut) is used to segment an image into several regions and locate the foreground with the number of keypoints in each region. Experiments on the given image data set demonstrate the effectiveness of our algorithm.

This paper presents a novel gender classification method based on geometry features of palm image which is simple, fast, and easy to handle. This gender classification method based on geometry features comprises two main attributes. The first one is feature extraction by image processing. The other one is classification system with polynomial smooth support vector machine (PSSVM). A total of 180 palm images were collected from 30 persons to verify the validity of the proposed gender classification approach and the results are satisfactory with classification rate over 85%. Experimental results demonstrate that our proposed approach is feasible and effective in gender recognition.

Due to the semantic gap between visual features and semantic concepts, automatic image annotation has become a difficult issue in computer vision recently. We propose a new image multilabel annotation method based on double-layer probabilistic latent semantic analysis (PLSA) in this paper. The new double-layer PLSA model is constructed to bridge the low-level visual features and high-level semantic concepts of images for effective image understanding. The low-level features of images are represented as visual words by Bag-of-Words model; latent semantic topics are obtained by the first layer PLSA from two aspects of visual and texture, respectively. Furthermore, we adopt the second layer PLSA to fuse the visual and texture latent semantic topics and achieve a top-layer latent semantic topic. By the double-layer PLSA, the relationships between visual features and semantic concepts of images are established, and we can predict the labels of new images by their low-level features. Experimental results demonstrate that our automatic image annotation model based on double-layer PLSA can achieve promising performance for labeling and outperform previous methods on standard Corel dataset.