Most Down Articles

    Published in last 1 year | In last 2 years| In last 3 years| All| Most Downloaded in Recent Month | Most Downloaded in Recent Year|

    In last 3 years
    Please wait a minute...
    For Selected: Toggle Thumbnails
    Review of Research on Condition Assessment of Nuclear Power Plant Equipment Based on Data-Driven
    XU Yong, CAI Yunze, SONG Lin
    Journal of Shanghai Jiao Tong University    2022, 56 (3): 267-278.   DOI: 10.16183/j.cnki.jsjtu.2021.502
    Abstract3782)   HTML319)    PDF(pc) (1383KB)(1298)       Save

    The condition assessment of the entire life cycle of nuclear power equipment has a significant impact on improving the safety and economy of nuclear power plants. In the past, operation and maintenance of systems, equipment, and structures of domestic nuclear power plants, mostly relied on the alarm mechanism of equipments, the simple threshold judgments of parameters, or the empirical judgments of engineers. With the implementation of online monitoring system in nuclear power plants, a large number of equipment operation data have been accumulated, and the use of data-driven technology to assess the health of equipment has become the focus of attention in the industry. In this paper, the current situation of the online monitoring system of nuclear power equipment was introduced and the common malfunction of nuclear power equipment was analyzed. The condition assessment of nuclear power equipment were categorized into three major problems (i.e., anomaly detection, life prediction, and fault diagnosis), the situation of research and application were summarized respectively, and the application potential of deep learning technology in this field was emphasized. Based on this, the challenges and possible solutions to the condition assessment of nuclear power plant equipment were further analyzed.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Dynamics Modeling and Validation of Coaxial Lifting Rotors
    HU Jinshuo, HUANG Jianzhe
    Journal of Shanghai Jiao Tong University    2022, 56 (3): 395-402.   DOI: 10.16183/j.cnki.jsjtu.2021.044
    Abstract4075)   HTML107)    PDF(pc) (2567KB)(1243)       Save

    The dynamics model for coaxial lifting rotors can be used to study the controller design and flight simulation for coaxial-rotor aerial vehicles. However, both the computational efficiency and the accuracy should be considered. First, the computational model of the induced velocity of lifting rotor everywhere including the wake region is derived based on adjoint theorem. Then, the finite state dynamics model for coaxial lifting rotors with wake skew considered is developed by extending the finite state inflow model for single rotor. Finally, the equations for calculating the thrust of coaxial lifting rotors in the hover condition are given, and the test is conducted. The results show that the computational complexity of the proposed dynamics model for coaxial lifting rotors is acceptable, and the computational thrusts are almost close to the test results when the rotational speed is within a certain range, which can also reflect the trend of the thrust lost for coaxial lifting rotors.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    An Identification Method for DC-Link Capacitor Capacitance of Grid Connected Inverter
    ZHU Chenghao, WANG Han, SUN Guoqi, WEI Xiaobin, WANG Fuwen, CAI Xu
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 693-700.   DOI: 10.16183/j.cnki.jsjtu.2021.515
    Abstract1012)   HTML1284)    PDF(pc) (5050KB)(1200)       Save

    DC-link for the capacitor is one of the most vulnerable components of the grid connected converter, whose capacitance identification will help to improve the system reliability by finding and replacing the aging capacitor in time. An identification method for the DC-link capacitor capacitance of the grid connected inverter based on pre-charging circuit is proposed. By analyzing the relationship between the capacitance and the charging current, charging voltage during pre-charging process, and combining the historical operating data, the set of capacitance state feature vector is built. The support vector regression (SVR) model is trained and the regression prediction relationship between the state value and the capacitance is set. The model is optimized by using the particle swarm optimization (PSO) algorithm, which can be used for capacitance identification of the DC-link capacitor. Simulation and experiments results show that the proposed method can implement the accurate capacitance identification of the DC-link capacitor of the grid connected inverter, with an identification error of less than 0.95%. This method does not need to add hardware circuit and change the control algorithm, and has a certain practical value.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    A Review of Coupled Electricity and Hydrogen Energy System with Transportation System Under the Background of Large-Scale New Energy Vehicles Access
    LI Jiaqi, XU Xiaoyuan, Yan Zheng
    Journal of Shanghai Jiao Tong University    2022, 56 (3): 253-266.   DOI: 10.16183/j.cnki.jsjtu.2021.464
    Abstract4116)   HTML950)    PDF(pc) (2106KB)(1157)       Save

    The large-scale utilization of renewable energy is an important way to achieve the “double carbon targets”. The technology of coupled renewable energy with hydrogen system can improve the consumption rate of renewable energy and the penetration of new energy vehicles. The coupling between the electricity-hydrogen energy system and the transportation system will be even closer in the future. Based on the access of large-scale new energy vehicles, first, the development of the electricity and hydrogen energy system was summarized, and the three working modes of electricity-hydrogen coupling system including hydrogen production, output smoothing, and coordinated operation with electricity network were introduced. Then, the research status of the electricity-transportation coupling system on planning and optimal operation, and the problems of hydrogen-transportation coupling system on hydrogen refueling station optimization and hydrogen transportation were analyzed. Finally, in combination with the existing bottlenecks, the future feasible research directions such as dynamic model construction and the influence of uncertain factors were proposed.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Challenges of Distributed Green Energy Carbon Trading Mechanism and Carbon Data Management
    LI Xingzhi, HAN Bei, LI Guojie, WANG Keyou, XU Jin
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 977-993.   DOI: 10.16183/j.cnki.jsjtu.2021.450
    Abstract974)   HTML893)    PDF(pc) (2604KB)(1134)       Save

    To achieve the double carbon goal of “carbon peaking and carbon neutrality”, the construction of the power system which is based on the green energy needs to be accelerated. With the growth of the system scale, the distributed green energy carbon trading mechanism and the carbon data management technology based on the blockchain technology can effectively encourage the development of green energy and become effective means for the implementation of low-carbon electricity. The accurate and real-time carbon emission calculation will further provide data support for the accuracy and security of carbon trading information. First, the current research status of green certificate trading and carbon asset management is introduced. Next, the adaptability analysis of the key technologies of the blockchain technology in the four directions of green electricity traceability, green certificate trading, carbon trading, and joint market of green certificate and carbon assets is performed. Afterwords, the specific mathematical models of carbon emission calculation is studied, and the data availability of carbon source traceability methods applicable to the blockchain architecture are discussed. Finally, some suggestions for the future development of carbon emission flow analysis are proposed.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Multi-Objective Optimization Strategy of Trajectory Planning for Unmanned Aerial Vehicles Considering Constraints of Safe Flight Corridors
    HUANG Yuhao, HAN Chao, ZHAO Minghui, DU Qiankun, WANG Shigang
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 1024-1033.   DOI: 10.16183/j.cnki.jsjtu.2021.154
    Abstract747)   HTML41)    PDF(pc) (5684KB)(1024)       Save

    Aimed at the problem of generating a smooth, safe, and dynamically feasible continuous-time trajectory for unmanned aerial vehicles (UAV) in complex environments, a trajectory planning algorithm is proposed to minimize a multi-objective function based on safe flight corridors. The safe flight corridor represented by a collection of convex polyhedra is built based on the initial discrete waypoints generated by the improved rapidly-exploring random tree(RRT), namely the RRT* algorithm. The safety objective function is established according to the constraints of limiting the trajectory inside safe flight corridors. In combination with the flight smoothness, dynamic characteristics, and time performance, a multi-objective function is built. The gradient-based convex optimization algorithm is used to derive the continuous-time trajectory expressed as a piece-wise polynomial by optimizing the position, velocity, acceleration of waypoints, and time allocation. The effectiveness and performance of the proposed algorithm is tested and compared under complex environments such as the coal mine. The test results demonstrate that the proposed algorithm has a better comprehensive performance in comparison with existing algorithms.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Distributed Photovoltaic Net Load Forecasting in New Energy Power Systems
    LIAO Qishu, HU Weihao, CAO Di, HUANG Qi, CHEN Zhe
    Journal of Shanghai Jiao Tong University    2021, 55 (12): 1520-1531.   DOI: 10.16183/j.cnki.jsjtu.2021.244
    Abstract1496)   HTML235)    PDF(pc) (69168KB)(1022)       Save

    To respond to the demand of achieving carbon peaking and carbon neutrality goals, and to construct a complete “source-grid-load-storage” new energy power system, a distributed photovoltaic net load forecasting model based on Hamiltonian Monte Carlo inference for deep Gaussian processes (HMCDGP) is proposed. First, direct and indirect forecasting methods are used to examine the accuracy of the proposed model and to obtain spot forecasting results. Then, the proposed model is used to perform probability forecasting experiments and produce interval prediction results. Finally, the superiority of the proposed model is verified through the comparative experiments based on the net load data of 300 households recorded by Australia Grid. After obtaining the exact net load probabilistic forecasting results, the photovoltaic production can be fully utilized via power dispatch, which can reduce the use of fossil energy and further reduce the carbon emission.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Development Pathway of China’s Clean Electricity Under Carbon Peaking and Carbon Neutrality Goals
    HUANG Qiang, GUO Yi, JIANG Jianhua, MING Bo
    Journal of Shanghai Jiao Tong University    2021, 55 (12): 1499-1509.   DOI: 10.16183/j.cnki.jsjtu.2021.272
    Abstract1643)   HTML523)    PDF(pc) (1849KB)(965)       Save

    Nowadays, the third energy revolution has taken place. Many developed countries have formulated clean energy development strategies and announced the time for phasing out thermal and nuclear power to reduce carbon emissions. Meanwhile, China has made a commitment to the world that the carbon emissions of China will peak before 2030, and the carbon neutrality will be achieved before 2060. Therefore, it is of great significance to study the development pathway of clean electricity of China. The reserves and characteristics of clean energy such as hydro, wind, and solar in China are analyzed. The medium and long-term power demand of China is projected, and the power system structure in 2030 and 2050 are respectively estimated based on the electric power and energy balance equations. In addition, the trend of carbon emissions is also analyzed. Some suggestions are proposed to guide the development of China’s clean electricity. The results indicate that the “carbon peaking” of China’s power system would arrive in 2027, and the clean electricity of China is projected to exceed 50% of the total energy production in 2030. Thermal and nuclear power can be replaced by clean electricity such as hydro, wind, and solar energy in 2050, the power industry will achieve “zero CO2 emission”, and the transformation of the green power system will be achieved in response to carbon peaking and carbon neutrality goals.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Decision-Making Method of Intelligent Vehicles: A Survey
    HU Yikai, WANG Chunxiang, YANG Ming
    Journal of Shanghai Jiao Tong University    2021, 55 (8): 1035-1048.   DOI: 10.16183/j.cnki.jsjtu.2020.387
    Abstract953)   HTML30)    PDF(pc) (1687KB)(913)       Save

    Combined with the current research status of the intelligent vehicle decision-making methods at home and abroad, this paper classifies and summarizes decision-making methods from four aspects: decision input and output, environment interaction, and algorithm types. Besides, it analyzes their advantages and disadvantages, and evaluates applicable scenarios. Moreover, it surveyes the common data sets and current evaluation standards which are used for decision-making researches. Furthermore it discusses the technical difficulties faced by current decision-making methods and future development trends.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Circulation Control of Airfoil Aerodynamic Force Under Ground Effect of Wavy Wall
    LIU Hao, SUN Jianhong, SUN Zhi, TAO Yang, WANG Dechen, LIU Guangyuan
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 1101-1110.   DOI: 10.16183/j.cnki.jsjtu.2021.384
    Abstract577)   HTML34)    PDF(pc) (3280KB)(906)       Save

    The interaction of airflow and sea waves seriously affects the flight stability and cruising safety of ground effect vehicles. The influence of different sea states and different angles of attack were analyzed numerically on the aerodynamic characteristics of the airfoil under ground effect of wavy wall. The influence of the constant blowing and periodic blowing methods was further studied on the aerodynamic force of the airfoil under ground effect. The simulation results show that the lift coefficient of the airfoil changes periodically with the wave under the wavy ground wall. The amplitude of the lift coefficient fluctuation is larger with the increasing of wave height and angle of attack, or the decreasing of wavelength. Applying the circulation control method for periodic blowing in the same period as the relative motion of the waves can effectively weaken the fluctuation of the airfoil lift coefficient under wavy sea conditions and improve the flight stability and safety of ground effect vehicles.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Optimization of Active Distribution Network Operation Considering Decarbonization Endowment from 5G Base Stations
    ZENG Bo, MU Hongwei, DONG Houqi, ZENG Ming
    Journal of Shanghai Jiao Tong University    2022, 56 (3): 279-292.   DOI: 10.16183/j.cnki.jsjtu.2021.367
    Abstract4177)   HTML388)    PDF(pc) (3102KB)(901)       Save

    The massive access of 5G base stations (5G BSs) provides new possibilities for the low-carbon development of future power systems. By incentivizing 5G BSs to participate in demand response and incorporating them into the existing active distribution network (ADN) operation framework, the cost of the electricity consumption of 5G BSs can be reduced while promoting the consumption and efficient use of renewable energy sources (RES). This paper proposes a multi-objective interval optimization model for ADN operation considering low-carbon empowerment of 5G BSs. Based on the interaction mode between 5G BSs and the distribution network, a 5G BSs operating flexibility description model is constructed, and the system dynamics method is used to reveal the mechanism of 5G BSs on carbon emission reduction on the distribution side. Taking the minimization of system operating cost and carbon emissions as the goals, and considering the constraints for both the distribution network and the communication network, a multi-objective optimization model for ADN operation with 5G BSs is established. The model cooptimizes the dispatch of RES and 5G equipment, and adopts an interval method to consider the uncertainty of RES output and communication loads, which can achieve simultaneous optimization of system economy and low-carbon benefits. Combining the equivalent transformation and the non-dominated sorting genetic algorithm to solve the problem, the results of numerical studies prove the effectiveness of the proposed method.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Design of Light Fireproof Enclosure Bulkheads Based on Topography Optimization for Cruise Ships
    ZHANG Fan, YANG Deqing, QIU Weiqiang
    Journal of Shanghai Jiao Tong University    2021, 55 (10): 1175-1187.   DOI: 10.16183/j.cnki.jsjtu.2020.201
    Abstract848)   HTML571)    PDF(pc) (19957KB)(848)       Save

    In order to develop a new lightweight enclosure structure with an excellent fireproof and bearing performance, and to replace the traditional stiffened fire enclosure bulkheads in the superstructure area, a design method of light fireproof enclosure bulkheads for cruise ship based on the topography optimization technology was proposed. The location and numbers of corrugated beads in lightweight wall designed by this method were generated according to the requirements of load bearing capacity and manufacturing process, and this method overcomes the disadvantages that the location and numbers of beads in the design of conventional corrugated wall have to be determined in advance. Aimed at the specified design regions, the lightweight of cruise fireproof enclosure bulkheads (CFEB) structure was taken as the objective function while the stress in the weld zone, the stress in the nonweld zone, and the first-order buckling factor of CFEB were taken as constraints. Then, the topography design models of CFEB were established and solved. Feasible configurations were obtained by topography optimization, and the final configurations of CFEB were formed by secondary design. The mechanical properties of the final configurations were compared with the traditional stiffened fireproof bulkheads. It is concluded that the new CFEB has advantages of lightweight and good strength compared with the traditional stiffened fireproof bulkheads.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    An Admittance Reshaping Strategy of Three-Phase LCL Grid-Connected Inverter Based on Modified Passive Control
    WANG Han, ZHANG Jianwen, SHI Gang, ZHU Miao, CAI Xu
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1105-1113.   DOI: 10.16183/j.cnki.jsjtu.2022.120
    Abstract267)   HTML32)    PDF(pc) (3313KB)(840)       Save

    The passivity-based control (PBC) based on energy function has been studied for grid-connected converters to achieve a better performance. However, traditional PBC method relies on the accurate mathematical model of grid-connected inverter. In previous studies on PBC, the effect of digital control delay is rarely considered and the stability under grid impedance uncertainties is not discussed, especially in the capacitive grid or complex weak grid. To address these issues, this paper proposes an improved PBC method to reshape the output admittance for LCL-filtered grid-connected inverters. The system passive region is expanded up to the Nyquist frequency by adding a capacitor current feedback loop which can achieve active damping control of LCL resonant frequency under the wide range of grid impedance changes. The parameter design method is also presented for the proposed PBC control. To verify the correctness of the theoretical analysis, both simulation and experiments are conducted on a 3 kW grid-connected inverter prototype.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Underwater Image Enhancement Based on Generative Adversarial Networks
    LI Yu, YANG Daoyong, LIU Lingya, WANG Yiyin
    Journal of Shanghai Jiao Tong University    2022, 56 (2): 134-142.   DOI: 10.16183/j.cnki.jsjtu.2021.075
    Abstract1969)   HTML59)    PDF(pc) (22386KB)(834)       Save

    This paper proposes an underwater image correction and enhancement algorithm based on generative adversarial networks. In this algorithm, the multi-scale kernel is applied to the improved residual module to construct a generator, which realizes the extraction and fusion of multiple receptive fields feature information. The discriminator design considers the relationship between global information and local details, and establishes a global-region dual discriminator structure, which can ensure the consistency of overall style and edge texture. An unsupervised loss function based on human visual sensory system is proposed. Reference image constraints are not required, and the confrontation loss and the content loss are jointly optimized to obtain better color and structure performance. Experimental evaluations on multiple data sets show that the proposed algorithm can better correct color deviation and contrast, protect details from loss, and is superior to typical algorithms in subjective and objective indexes.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Comparative Analysis of Technical Standards for Offshore Wind Power via VSC-HVDC
    YU Hao, ZHANG Zhemeng, PENG Sui, ZHANG Zhiqiang, REN Wanxin, LI Canbing
    Journal of Shanghai Jiao Tong University    2022, 56 (4): 403-412.   DOI: 10.16183/j.cnki.jsjtu.2021.465
    Abstract1782)   HTML1064)    PDF(pc) (1110KB)(813)       Save

    This paper introduces the current situation of domestic and foreign offshore wind power grid-connected via voltage source converter based high voltage direct current(VSC-HVDC) transmission standards, and selects representative standards of offshore wind power grid-connected via VSC-HVDC. It also compares the domestic and foreign offshore wind power grid in terms of power control, fault ride-through, power quality, stability, etc., and analyzes the development trend of offshore wind power grid-connected via VSC-HVDC standards. In order to promote the development of offshore wind power industry, it provides reasonable suggestions for the formulation and revision of Chinese offshore wind power grid-connected via VSC-HVDC standards.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Dynamic Knowledge Graph Modeling Method for Ship Block Manufacturing Process
    SONG Dengqiang, ZHOU Bin, SHEN Xingwang, BAO Jinsong, ZHOU Yaqin
    Journal of Shanghai Jiao Tong University    2021, 55 (5): 544-556.   DOI: 10.16183/j.cnki.jsjtu.2020.241
    Abstract899)   HTML28)    PDF(pc) (6895KB)(812)       Save

    In the dynamic and discrete ship block manufacturing process, lack of effective process resource organization and transparency in product processing leads to the problem of high cost and low efficiency for managers to acquire knowledge. A method for dynamic generation and updating of knowledge graph based on processing beat data flow is proposed. The definition of the processing beat data information model is defined by analyzing the processing flow and the station data characteristics of the ship blocks. The graph mapping steps, models, and fusion connection algorithms are proposed for static resources and processing beat data to realize the semantic association of station dynamic time series data and knowledge graphs. Based on the relationship between station process and product structure, the generation of workshop-level dynamic knowledge graph is realized. Taking the production process of a ship block as an example, the knowledge graph visualization prototype system is designed, developed, and verified. The results show that the proposed method is beneficial to the organization, acquisition, and reuse of knowledge in the process of ship block manufacturing.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Research and Application of Key Technologies of Network Security Situation Awareness for Smart Grid Power Control Systems
    ZHANG Liang, QU Gang, LI Huixing, JIN Haochun
    Journal of Shanghai Jiao Tong University    2021, 55 (S2): 103-109.   DOI: 10.16183/j.cnki.jsjtu.2021.S2.017
    Abstract1142)   HTML21)    PDF(pc) (9257KB)(809)       Save

    The network security situational awareness (NSSA) technology, which can perceive the potential network security risks globally and dynamically, is receiving more and more attention.With the help of machine learning, artificial intelligence, big data, and the other technologies, the network security situation awareness solution of power control system can learn from the process of the long-term and massive network security situation data, gain insight into the internal logical relationship implied in the data, and realize the abnormal behavior identification, intrusion intention understanding, and impact assessment of various activities in the power business network. First, the basic concept and the logical block diagram of NSSA are introduced. Then, the current situation and the risk of network security of power control system are summarized. Next, aimed at these risks and deficiencies, the key technologies involved in the network security situation awareness platform from the perspective of practice are expounded, which include the multidimensional security event correlation analysis model,the abnormal traffic and abnormal behavior detection method based on “baseline learning”,the attack chain recognition model based on attack scenario,and the power remote control security technology based on “address self verification”. Finally, the situation awareness solution and its application in power monitoring systems are stated and prospected.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Experimental Study on Condensation of Steam Jet Injection in Submerged Condition
    ZHANG Wei, JIANG Chaofei, YE Ya’nan, WANG Xiaoyan, GONG Zili, HU Chen, XIAO Yao, GU Hanyang
    Journal of Shanghai Jiao Tong University    2022, 56 (1): 1-13.   DOI: 10.16183/j.cnki.jsjtu.2020.302
    Abstract893)   HTML464)    PDF(pc) (10296KB)(796)       Save

    An experimental study is conducted to find the characteristics of steam plume and pressure oscillation on direct contact condensation by a side-hole sparger. Synchronal measuring of transient pressure of the steam plume is gained from the high-speed camera and high-pressure sensor respectively. The influence of steam mass flux and water temperature on direct contact condensation characteristic are presented and its regime map is plotted. Then, the dynamic connections of transient pressure and steam plume in different condensation regimes are analyzed. It is found that high frequency pressure oscillation and the collapse of detached bubbles occur at the same time. Together with the condensing and disappearing process of the collapse of detached bubbles, the intensity of pressure oscillation decays exponentially in a vibration way. The changing trends of steam plume length in condensation oscillation regime and stable condensation regime are also obtained, which shows that the steam plume increases with the steam mass flux and the temperature in the condensation oscillation regime. When entering the stable condensation regime, the steam plume suddenly decreases and then increases with the temperature and the steam mass flux. The research results are useful for the engineering application of sparger in steam emission devices.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Ultra-Short-Term Load Forecasting of Electric Vehicle Charging Stations Based on Ensemble Learning
    LI Hengjie, ZHU Jianghao, FU Xiaofei, FANG Chen, LIANG Daming, ZHOU Yun
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 1004-1013.   DOI: 10.16183/j.cnki.jsjtu.2021.486
    Abstract988)   HTML394)    PDF(pc) (3182KB)(776)       Save

    Accurate electric vehicle load forecasting is the basis for maintaining the safe and economical operation of charging stations, and for supporting the planning and decision-making of new and expanded charging infrastructure. In order to improve the accuracy of the ultra-short-term load forecasting of charging stations, an ultra-short-term load forecasting method based on ensemble learning is proposed. First, aimed at the prediction accuracy and the response speed, the light gradient boosting machine (LightGBM) framework is utilized to build several basic regressors. Next, the basic regressors are integrated by using the adaptive boosting (Adaboost) method. Finally, by using hyperparameter adjustment and optimization, a dual-system for ultra-short-term load forecasting of charging stations named energy ensemble boosting-light gradient boosting machine (EEB-LGBM) is generated. The analysis of the numerical examples shows that the proposed model has a higher accuracy than the back propagation neural network (BPNN), convolutional neural networks-long short term memory (CNN-LSTM), autoregressive integrated moving average (ARIMA), and other load forecasting methods, which can greatly reduce the training time and the computing power requirements of the training platform.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    A Wind-Solar-Electric Vehicles Coordination Scheduling Method for High Proportion New Energy Grid-Connected Scenarios
    LI Linyan, HAN Shuang, QIAO Yanhui, LI Li, LIU Yongqian, YAN Jie, LIU Haidong
    Journal of Shanghai Jiao Tong University    2022, 56 (5): 554-563.   DOI: 10.16183/j.cnki.jsjtu.2022.040
    Abstract825)   HTML396)    PDF(pc) (1648KB)(771)       Save

    Wind-solar-electric vehicles coordinated optimization scheduling can effectively reduce the adverse effects of multiple uncertainties of wind-solar output and disorderly charging of electric vehicles on the power system. Most of the existing optimization scheduling models take the minimum equivalent load fluctuation as the optimization objective, which, only considering the overall fluctuation of equivalent load, cannot measure the matching degree of output-load, and do not consider the difference of output in different output scenarios. Therefore, a wind-solar-electric vehicles coordination scheduling method for high proportion new energy grid-connected scenarios is proposed. First, the disordered charging model of electric vehicles by Monte Carlo simulation is constructed. Then, a wind-solar output typical day classification model using Gap statistical and K-means++ is constructed based on the forecasting data of wind and solar power. Finally, taking the minimum equivalent load variance and load tracking coefficient as the double optimization objectives, a wind-solar-electric vehicles coordination optimization scheduling model is established, and the NSGA-II algorithm is used to solve it. The results demonstrate that the proposed model can effectively improve the matching degree of wind-solar output and load, and reduce the fluctuation of equivalent load, so as to reduce the adverse effects of multiple uncertainties of wind-solar output and disorderly charging of electric vehicles on the power system.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Intelligent Global Sensitivity Analysis Based on Deep Learning
    WU Shuchen, QI Zongfeng, LI Jianxun
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 840-849.   DOI: 10.16183/j.cnki.jsjtu.2021.191
    Abstract935)   HTML47)    PDF(pc) (1418KB)(769)       Save

    This paper proposes an end-to-end method that combines deep learning and sensitivity analysis, which can perform gradient back propagation calculation sensitivity on the saved weight information while training the model. The structure and activation function of the depth model are specially designed to adapt to the subsequent sensitivity calculation. The experimental results conducted on a Boston house prices dataset, a track information fusion dataset, and the G function show that the proposed method is more accurate than classical methods such as Sobol’ method when the parameter distribution is uneven, and has a stronger robustness. Compared with the traditional neural network method, the accuracy of the proposed method is higher. The experiment proves that the sample parameter sensitivity obtained by the deep learning model can be used to optimize the model output.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Optimal Planning of Power Systems with Flexible Resources for High Penetrated Renewable Energy Accommodation
    GUO Yongtao, XIANG Yue, LIU Junyong
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1146-1155.   DOI: 10.16183/j.cnki.jsjtu.2022.269
    Abstract160)   HTML10)    PDF(pc) (2433KB)(766)       Save

    High penetrated renewable energy has brought great challenges to the flexibility of the power system due to its volatility and intermittency. To improve the capacity of renewable energy accommodation, the flexibility reformation of thermal power units, the construction of gas-fired units, and the electrical energy storage installation are considered as effective solutions. Thus, an optimization model for power system planning scheme considering multi-type flexible resources with their different output characteristics is established. The simulation results on a modified IEEE 24-bus power system and 12-node natural gas system demonstrate the effectiveness of the proposed model. In addition, the applicability of different flexible resource planning schemes is comprehensively evaluated from the perspectives of economy, accommodation capacity, and carbon reduction, so as to meet the different planning goals.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Numerical Simulation Strategy Optimization Analysis of Submarine Resistance and Flow Field
    LI Peng, WANG Chao, SUN Huawei, GUO Chunyu
    Journal of Shanghai Jiao Tong University    2022, 56 (4): 506-515.   DOI: 10.16183/j.cnki.jsjtu.2020.327
    Abstract2068)   HTML188)    PDF(pc) (13748KB)(765)       Save

    In order to explore the influence of different turbulence models on the resistance and flow field of an advancing submarine, based on the STAR-CCM+platform, and taking Sub-off as the geometric model, this paper adopts the finite volume method, combing 10 turbulence models to conduct numerical research on hydrodynamic and flow field characteristics of Sub-off. First, the LES-Smagorinsky turbulence model is used for the convergence of grids and time steps. Then, the appropriate grid and time step are selected to calculate 10 kinds of turbulence models in specific cases. Finally, the selected turbulence model is used to analyze the hydrodynamic characteristics and flow fields of Sub-off. The results show that there are great differences among the 10 turbulence models in the prediction of submarine hydrodynamic performance and flow field characteristics. LES-Smagorinsky can not only predict the hydrodynamic performance and the average flow field of submarine, but also accurately predict secondary variables of flow fields.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Low-Carbon Transformation of the Power System in the Guangdong-Hong Kong-Macao Greater Bay Area
    ZHANG Pengfei, XU Jingyi, GUO Wei, WU Wei, ZHONG Chen, WEI Wendong
    Journal of Shanghai Jiao Tong University    2022, 56 (3): 293-302.   DOI: 10.16183/j.cnki.jsjtu.2021.436
    Abstract4237)   HTML391)    PDF(pc) (2818KB)(748)       Save

    China’s “carbon peaking and carbon neutrality” goal relies greatly on the low-carbon transition of the power system, but the existing research rarely explores the low-carbon transition of the regional power system. By using the intergovernmental panel on climate change (IPCC) greenhouse gas inventory compilation method and the network model analysis, the carbon emissions caused by the power generation and the power consumption in Guangdong-Hong Kong-Macao Greater Bay Area (the Greater Bay Area) was quantified. The logarithmic mean Divisia index (LMDI) method was used to quantify the influence of socio-economic factors on the electricity-related carbon emissions in the Greater Bay Area. The results show that Hong Kong and Macao have made slow progress in the low-carbon transition of the power system, and Guangdong’s share of the low-carbon power continues to increase. The rapidly expanding economic scale and the power demand were the most important drivers of the emissions growth in the Greater Bay Area. The low-carbon electricity imported from outside regions and the improved efficiency in the sectoral electricity consumption offset part of the emission growth.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    A Dual-System Reinforcement Learning Method for Flexible Job Shop Dynamic Scheduling
    LIU Yahui, SHEN Xingwang, GU Xinghai, PENG Tao, BAO Jinsong, ZHANG Dan
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1262-1275.   DOI: 10.16183/j.cnki.jsjtu.2021.215
    Abstract808)   HTML69)    PDF(pc) (4009KB)(741)       Save

    In the production process of aerospace structural parts, there coexist batch production tasks and research and development (R&D) tasks. Personalized small-batch R&D and production tasks lead to frequent emergency insertion orders. In order to ensure that the task is completed on schedule and to solve the flexible job shop dynamic scheduling problem, this paper takes minimization of equipment average load and total completion time as optimization goals, and proposes a dual-loop deep Q network (DL-DQN) method driven by a perception-cognition dual system. Based on the knowledge graph, the perception system realizes the representation of workshop knowledge and the generation of multi-dimensional information matrix. The cognitive system abstracts the scheduling process into two stages: resource allocation agent and process sequencing agent, corresponding to two optimization goals respectively. The workshop status matrix is designed to describe the problems and constraints. In scheduling decision, action instructions are introduced step by step. Finally, the reward function is designed to realize the evaluation of resource allocation decision and process sequence decision. Application of the proposed method in the aerospace shell processing of an aerospace institute and comparative analysis of different algorithms verify the superiority of the proposed method.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Numerical Simulation and Analysis of Cylindrical Ice Impacting Problem
    WANG Chao, YANG Bo, ZHANG Yuan, GUO Chunyu, YE Liyu
    Journal of Shanghai Jiao Tong University    2022, 56 (3): 368-378.   DOI: 10.16183/j.cnki.jsjtu.2020.278
    Abstract3857)   HTML71)    PDF(pc) (4968KB)(738)       Save

    In order to study the application characteristics of the peridynamics (PD) method in the field of ice mechanical behavior and the sensitivity analysis of parameter changes in the numerical prediction of ice failure, the ordinary state-based peridynamic method is employed to systematically analyze the impact failure process of cylindrical ice in the present work. The results show that the simulated ice impact process by the proposed method is basically consistent with the test results, and the calculation results converge under the selected time step and particle spacing. The impact velocity, Poisson’s ratio, and the elastic modulus of the ice have remarkable effects on the impact process of ice cylinder, while the size and fracture toughness of the ice only have little influence. The innovation of this paper lies in the fact that the state-based PD method is applied to study the ice impact problem, which compensate for the shortcomings of the bond-based PD method that limits the Poisson’s ratio of the ice.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Differentiated Allocation Model of Renewable Energy Green Certificates for New-Type Power System
    ZHANG Shuo, LI Wei, LI Yingzi, LIU Qiang, ZENG Ming
    Journal of Shanghai Jiao Tong University    2022, 56 (12): 1561-1571.   DOI: 10.16183/j.cnki.jsjtu.2022.150
    Abstract1283)   HTML816)    PDF(pc) (1436KB)(734)       Save

    In order to achieve China’s “30·60” decarbonization goal, the green and low-carbon transformation of the energy system is the fundamental support; the construction of new-type power system is the key step, and the green certificate is the important voucher to reflect the green value of renewable energy. Currently, the distribution mechanism of green certificates in China is oversimplified, which neither effectively measures the variability of green values generated by different types of renewable energy, nor balances the coordinated development of renewable energy. Therefore, to differentiate the exchange mechanism of green certificates by different types of renewable energy power in this paper, an evaluation index system is established, which describes the difference between green certificates, considering the comprehensive value of renewable energy, and an evaluation model is built with the criteria importance by using the intercriteria correlation (CRITIC) method, the entropy weight method, and the technique for order preference by similarity to an ideal solution (TOPSIS) method. Under the development scenario of peaking carbon emissions before 2030, the impact of the differentiated distribution model on the green incomes of centralized photovoltaic distributed photovoltaic power, onshore wind power, and offshore wind power is analyzed. Moreover, the development plan of renewable energy is modified in consideration of the effect of the differentiated distribution model, and policy suggestions on green certificates are proposed accordingly. The results show that the differentiated distribution model of green certificates is practical to provide corresponding decision-making support to the construction and improvement of green certificates trading mechanism in China.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Voltage and Frequency Suppression of Intentional Islanding Restoration Process for Distribution System with Multi-Generations
    CHEN Chun, GAO Jing, CAO Yijia, WANG Weiyu, ZHAO Long
    Journal of Shanghai Jiao Tong University    2022, 56 (5): 543-553.   DOI: 10.16183/j.cnki.jsjtu.2021.418
    Abstract804)   HTML1031)    PDF(pc) (4975KB)(724)       Save

    Intentional islanding restoration of distribution systems with multi-generations is of great importance to ensure the power supply of critical loads under extreme conditions, which is beneficial to improve the reliability of distribution systems. There are transient voltage and frequency fluctuations in the process of intentional islanding restoration, when the loads and distributed generations are gradually connected to the grid. The safety and stability of the intentional islanding are affected by the fluctuations, and networking process may fail in serious cases. Hence, the rapid power response of the energy storage system is utilized to suppress voltage and frequency fluctuations. A fluctuation suppression model based on energy storage system control is established, where a voltage and current double-loop feed-forward disturbance compensation control system is designed. A vector control method for energy storage system with improved dual-loop control is proposed, which solves the problems of traditional V/f control voltage offset and excessive voltage fluctuation. MATLAB/Simulink is used to build simulation models in different control modes in accordance with the black-start principle. The simulation results show that the improved double-loop control based on the vector method has a stronger anti-interference ability and significantly improved the islanding black-start self-organizing networking process. Voltage and frequency fluctuations are reduced, and the dynamic response performance of the system is improved.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Control Strategies for Suppressing Frequency Oscillation of Doubly-Fed Wind Farms Connected to Grid
    LIU Xinyu, LU Xinyan, ZENG Long, HAO Zhenghang, ZHAO Qifang, LI Xianwei, HAO Tongmeng
    Journal of Shanghai Jiao Tong University    2022, 56 (3): 303-311.   DOI: 10.16183/j.cnki.jsjtu.2021.437
    Abstract4161)   HTML247)    PDF(pc) (1481KB)(712)       Save

    Aimed at the problem of low-frequency oscillations caused by cross-region power transmissioin of large-scale wind farms, a single neuron adaptive proportion integration differentiation (PID) additional damping control strategy for low-frequency oscillations of the damping system is proposed in this paper. By analyzing the dynamic frequency response characteristics of doubly-fed wind turbines, a wind farm damping system oscillation controller is constructed by introducing quadratic performance indicators into the single neuron adaptive PID control algorithm. By adaptively adjusting the excitation frequency converter, the wind farm can quickly generate active power and the maximum positive damping, and suppress the low-frequency oscillation of the damping system. MATLAB is used to build a four-machine two-region power system simulation model with a wind farm. The comparison verifies that the method proposed in this paper can effectively suppress the swing of the power angle of the synchronous generator when low-frequency oscillation occurs in the system, improve the inertial response of the system, and reduce the risk of low-frequency oscillation in the power grid.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Adaptive Transferring Method of Digital Twin Model for Machining Domain
    SHEN Hui, LIU Shimin, XU Minjun, HUANG Delin, BAO Jingsong, ZHENG Xiaohu
    Journal of Shanghai Jiao Tong University    2022, 56 (1): 70-80.   DOI: 10.16183/j.cnki.jsjtu.2021.167
    Abstract995)   HTML44)    PDF(pc) (6512KB)(712)       Save

    In the multi-variety and small batch manufacturing workshop, digital twin model is mostly established for specific scenarios. Due to its lack of adaptive ability under working conditions, the prediction accuracy of machining quality is insufficient. To solve this problem, an adaptive transferring method of the digital twin model is proposed. By building the transferable digital twin model, the online prediction of machining quality based on the fusion of mechanism and algorithm model is realized. The transferring process and strategy of the digital twin model are proposed. Based on the analysis and calculation of characteristic data, the source model to be transferred is selected. At the same time, in combination with the transfer learning theory, the transfer of digital twin models is realized under simple and complex changing conditions. Taking drilling as an example, the drilling experiment platform is built and the feasibility of digital twin model transfer is verified. The results show that the model can keep the mean absolute error of prediction less than 1.5% under changing working conditions. This method provides a new idea to improve the adaptive ability of digital twin models.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Radar Signal Recognition Based on Dual Channel Convolutional Neural Network
    QUAN Daying, CHEN Yun, TANG Zeyu, LI Shitong, WANG Xiaofeng, JIN Xiaoping
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 877-885.   DOI: 10.16183/j.cnki.jsjtu.2021.209
    Abstract837)   HTML26)    PDF(pc) (4098KB)(709)       Save

    In order to solve the problems of difficult feature extraction and low recognition rate of radar signal at low signal-to-noise ratios, a dual channel convolutional neural network model based on Choi-Williams distribution (CWD) and multisynchrosqueezing transform (MSST) is proposed, which obtains two-dimensional time-frequency images by CWD and MSST time-frequency analyses on radar signals. Respectively, the time-frequency images are preprocessed and sequencely fed to a dual channel convolutional neural network for deep feature extraction. Finally, the features acquired by the two channels are fused, and the radar signal is classified and recognized through the convolutional neural network classifier. The simulation results show that when the signal-to-noise ratio is -10 dB, the overall recognition accuracy can reach above 96%, which is excellent at low signal-to-noise ratios.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Real-Time Calculation of Carbon Emissions in County-Level Administrative Regions Based on ‘Energy Brain’
    CHEN Yun, SHEN Hao, WANG Jiayu, ZHAO Wenkai, PAN Zhijun, WANG Xiaohui, XIAO Yinjing
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1111-1117.   DOI: 10.16183/j.cnki.jsjtu.2021.364
    Abstract959)   HTML782)    PDF(pc) (851KB)(709)       Save

    Existing calculation methods of carbon emission cannot well meet the needs of gradual refinement and real-time of carbon emission regions. In order to ensure the real-time and accuracy of carbon emissions responsibility allocation, a real-time calculation method of carbon emissions in urban regions is proposed. The improved K-means clustering algorithm is used to cluster and combine the operating periods and operating scenarios of the urban area energy load,so as to obtain the typical carbon emission characteristics. The regional unit electricity carbon emission is proposed as a carbon emission indicator, the operating period and scenario are classified, and the unit electricity carbon emission and the total carbon emission of urban regions for each cluster are calculated. The proposed algorithm is verified based on part of the historical data of energy consumption in the energy brain of a certain region in eastern China. The results show that the clustering method and carbon emission indicators can effectively calculate the total carbon emission of urban regions in real-time.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Mechanism of Forced Subsynchronous Oscillation of Large-Scale Photovoltaic Power Generation Grid-Connected System with Series Compensation Tranmmission Lines
    LIN Yong, KANG Jiale, YU Hao, CHEN Honglin, YANG Yanji, CHEN Wuhui
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1118-1127.   DOI: 10.16183/j.cnki.jsjtu.2021.415
    Abstract654)   HTML132)    PDF(pc) (1463KB)(703)       Save

    There exists the subsynchronous oscillation (SSO) instability risk in large-scale photovoltaic(PV) grid-connected systems with series compensation, which is generally explained by the negative damped oscillation theory. In this paper, the inter-photovoltaic harmonics due to maximum power point tracking (MPPT) control are used as the disturbance source and the large-scale PV grid-connected system with series compensation as the forced system. The forced oscillation theory is used to reveal the SSO mechanism of PV power generation based on the interaction between the perturbed MPPT and the series compensation grid-connected system, and verified in the PSCAD/EMTDC simulation platform. The results show that the perturbed MPPT-based PV inverter outputs interharmonic currents to the system due to the modulation coupling on the AC-DC side, which may lead to serious forced SSO problems when the interharmonic frequency is close to the frequency of inherent weakly damped mode of the system, causing a shock to the system stability. The simulation results verify the correctness of the proposed theory.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    An LC Inverter Based on Novel Dual-Loop Control
    LI Shuang, SHI Jianqiang
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1139-1147.   DOI: 10.16183/j.cnki.jsjtu.2021.275
    Abstract846)   HTML128)    PDF(pc) (1553KB)(697)       Save

    To improve the voltage tracking and anti-disturbance performance of the LC inverter, a novel voltage-current dual-loop control strategy is proposed. First, the voltage loop is tuned to first-order inertia link by zero-pole cancellation based on virtual resistance, which restrains the overshoot during voltage tracking. Next, the hypo-time-optimal current-loop is adopted to enhance the response speed of the current loop, which suppresses the sudden change of transient voltage. Finally, the cause of overshoot during the voltage recovery period is analyzed and the overshoot is eliminated by the adaptive integrator initial value, which modifies the voltage waveform distortion under loading disturbance. Based on the traditional double-loop control, the voltage loop and the current loop are improved respectively by the proposed novel control strategy, which overcomes the shortcomings of step response and anti-load disturbance performance. The feasibility and effectiveness of this method are validated through simulations on MATLAB/Simulink.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Numerical Simulation and Experimental Research of Sheet Hemming Forming Based on Adhesive Filling
    TANG Genglin, LI Jianjun, LI Yuanhui, ZHANG Longyao, ZHU Wenfeng
    Journal of Shanghai Jiao Tong University    2022, 56 (4): 523-531.   DOI: 10.16183/j.cnki.jsjtu.2020.429
    Abstract1974)   HTML139)    PDF(pc) (11461KB)(696)       Save

    The filling rate of adhesive is defined based on the geometric dimensions of the hemming model, and the numerical simulation model of the hemming process with adhesive is established by using the finite element method-smoothed particle hydrodynamics (FEM-SPH) method. By comparing and verifying with the hemming experiment with adhesive, the quantitative study of the influences of the hemming adhesive diameter, the edge distance, and the hemming thickness on the filling rate is realized. The research results show that the flow state and the final filling state of the adhesive layer obtained in the experiment are similar to the numerical simulation results, and the filling rate of the adhesive layer obtained in the experiment is highly consistent with the numerical simulation result, which verifies the feasibility and accuracy of the numerical simulation model. Further analysis shows that the influences of the hemming adhesive diameter, the edge distance, and the hemming thickness on the filling rate decrease in order, and the relationship formulas between the filling rate and process parameters, such as the hemming adhesive diameter, the edge distance, and the hemming thickness, are obtained by fitting, which provides a basis for the optimization design of the hemming process with adhesive of the automobile body sheet.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Inertial Control Strategy for Wind Farm with Distributed Energy Storage System Based on Model Predictive Control
    SHEN Yangwu, SONG Xingrong, LUO Ziren, SHEN Feifan, HUANG Sheng
    Journal of Shanghai Jiao Tong University    2022, 56 (10): 1285-1293.   DOI: 10.16183/j.cnki.jsjtu.2022.134
    Abstract862)   HTML1097)    PDF(pc) (1641KB)(694)       Save

    Distributed energy storage (DES) wind turbine is an effective means to solve the problem of system frequency stability caused by large-scale wind power connection. In this paper, an inertial control method for DES wind farms based on model predictive control (MPC) is proposed.First, the linearized prediction model of the DES wind farm is established. Then, on this basis, in combination with the control framework of MPC, an optimization model and strategy of MPC inertial control are proposed considering the cost of energy storage loss and the balanced change of wind turbine rotor speed,in order to achieve the balanced change of wind turbine rotor speed during inertia control. The simulation results show that the proposed control strategy can effectively coordinate the active power output of the wind power generation unit and the energy storage system unit in the DES wind turbine, reduce the cost of charging and discharging loss of the energy storage system, and ensure that the rotational speed of all wind turbines in the wind farm tends to be average during the inertial control period, avoiding the problem of wind turbines exiting frequency regulation due to excessive reduction of the rotational speed of wind turbines. The inertial control strategy of the DES wind farm is beneficial to improve the frequency stability of the power grid, which is of great significance to ensure the safe operation of the power grid.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Effect of Nanosecond Pulse Discharge Parameters on Ignition Performance
    LIU Jingyuan, WANG Ning, ZHAO Qingwu, XIONG Yong, CHENG Yong
    Journal of Shanghai Jiao Tong University    2022, 56 (1): 28-34.   DOI: 10.16183/j.cnki.jsjtu.2021.033
    Abstract705)   HTML13)    PDF(pc) (1129KB)(693)       Save

    The discharge characteristics of nanosecond pulse discharge at different pulse voltages and different pulse intervals are investigated based on constant volume bomb. The effects of different discharge parameters on the flame success rate and ignition delay of methane/air mixture are compared. The results show that the coupling between pulses can be reasonably utilized and the utilization rate of discharge energy can be improved by decreasing the pulse interval.The ignition limit of methane/air mixture can be enlarged by increasing the pulse voltage, the pulse number, and decreasing the pulse interval. The ignition delay can be reduced by increasing the pulse voltage and decreasing the pulse interval.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    A Novel Weather Classification Method and Its Application in Photovoltaic Power Prediction
    LI Fen, ZHOU Erchang, SUN Gaiping, BAI Yongqing, TONG Li, LIU Bangyin, ZHAO Jinbin
    Journal of Shanghai Jiao Tong University    2021, 55 (12): 1510-1519.   DOI: 10.16183/j.cnki.jsjtu.2021.264
    Abstract1061)   HTML142)    PDF(pc) (1327KB)(693)       Save

    To improve the accuracy of photovoltaic (PV) power prediction, this paper proposes a novel weather classification method. First, it distinguishs the clear days and cloudy days according to the total cloud cover. Then, it further classifies the cloudy days into three subtypes to investigate whether the sun is obscured by clouds. This method can effectively identify the characteristics of key meteorological environmental factors that affect PV output and form a new classification index sky condition factor (SCF) by weighted summation. This method has clear physical meanings, good discrimination, and easy quantification. The reasonable classification of weather types can eliminate the coupling relationship between many meteorological environmental factors and reduce the dimension of input variables, which makes it easy for statistical modeling. Based on the theoretical and the statistical approachs respectively, the modeling and verification are conducted and the results show that the method can effectively improve the accuracy of PV power prediction.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Journal of Shanghai Jiao Tong University    2021, 55 (S2): 7-14.   DOI: 10.16183/j.cnki.jsjtu.2021.S2.002
    Abstract944)      PDF(pc) (376KB)(687)       Save
    Table and Figures | Related Articles | Metrics | Comments0
    Application of Plane Elements and Shell Elements in Imitating Ribs of Members in Compound Strip Method
    HOU Yanguo, LI Zhanjie, GONG Jinghai
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 710-721.   DOI: 10.16183/j.cnki.jsjtu.2021.071
    Abstract807)   HTML448)    PDF(pc) (10465KB)(685)       Save

    Finite strip method (FSM) is a classical method to analyze the buckling of thin-walled members. The traditional FSM adopting trigonometric functions longitudinally can hardly analyze the members with spaced ribs along the longitudinal direction, while the compound strip method (CSM) can compensate for this shortcoming. Based on the CSM, the influence of utilizing plane elements and shell elements to respectively imitate stiffeners on buckling is investigated. Compared with the shell-element ribs, the plane-element ribs are prone to assembling the stiffener matrices with fewer degrees of freedom. But the shell-element ribs are more comprehensive as the out-plane displacement of ribs are taken into consideration. It is found that plane element ribs and shell element ribs have little difference on the buckling capacity of members. The buckling capacity has a small difference of mean absolute error (MAE) underneath 0.75% between the two types of CSMs, and the buckling capacity and modes are in good agreement with the finite element results. The buckling loads of the two types of CSMs are close to the FEM with a MEA less than 5%. The accuracy of the plane elements satisfies the predicted requirements, which helps to reduce the program computation and simplify the analysis complexity. The efficiency of analysis can be dramatically improved for fine meshing elements.

    Table and Figures | Reference | Related Articles | Metrics | Comments0