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    Multi-Energy Flow Modeling and Optimization of Electric-Gas-Thermal Integrated Energy System
    LI Bingjie, YUAN Xiaoyun, SHI Jing, XU Huachi, LUO Zixuan
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1297-1308.   DOI: 10.16183/j.cnki.jsjtu.2022.494
    Abstract3767)   HTML44)    PDF(pc) (8902KB)(872)       Save

    In view of the fact that the conversion of various energy forms such as electricity, gas, and heat in the regional integrated energy system (RIES) seriously affects the economy of the system operation, a mathematical model and an optimization model of RIES energy flow are established to improve the economy of the system and the absorption of renewable energy. First, the mathematical models of all kinds of energy conversion equipment in the system are established to determine the constraints of three kinds of energy transmission networks, namely electricity, natural gas, and heat. Then, taking economic operation as the primary objective, and taking into account the objective function of low carbon emissions and increasing the uptake rate of renewable energy, the RIES multi-energy flow optimization model is constructed. Finally, based on the large-scale integrated energy system, the load side demand response is introduced and the simulation model is established. The simulation results show that the introduction of demand response improves the flexibility of system scheduling, reduces the dependence of the system on energy storage equipment, and effectively reduces the energy consumption cost of users.

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    Optimal Allocation of Electric-Thermal Hybrid Energy Storage for Seaport Integrated Energy System Considering Carbon Trading Mechanism
    LIN Sen, WEN Shuli, ZHU Miao, DAI Qun, YAN Lun, ZHAO Yao, YE Huili
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1344-1356.   DOI: 10.16183/j.cnki.jsjtu.2022.428
    Abstract2994)   HTML9)    PDF(pc) (5125KB)(488)       Save

    With the continuous increase of electrification in seaports, the single energy supply mode of seaport microgrid is evolving towards multi-energy integration. Aimed to achieve the goals of peak carbon and carbon neutrality, an optimal carbon trading mechanism-based allocation scheme of hybrid electric and thermal storage system is proposed to further maximize the economic and environmental benefits. First, the integrated energy system model of a seaport is established, incorporating a scheme within the carbon trading market. Then, a bi-level optimization framework is proposed, in which the upper layer is utilized to optimize the allocation of the hybrid energy storage system and the lower layer is employed to optimize the operation. Afterwards, a combination algorithm of the mesh adaptive direct search and the adaptive chaotic particle swarm optimization is developed to solve the proposed problem. Finally, the real-world data of Tianjing port is utilized to verify the method. The numerical results demonstrate that with the help of the proposed method, both the cost and carbon emissions are dramatically reduced.

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    Two-Stage Day-Ahead and Intra-Day Rolling Optimization Scheduling of Container Integrated Port Energy System
    ZHOU Siyi, YANG Huanhong, HUANG Wentao, ZHOU Ze, JIAO Wei, YANG Zhenyu
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1357-1369.   DOI: 10.16183/j.cnki.jsjtu.2023.016
    Abstract2646)   HTML10)    PDF(pc) (7518KB)(550)       Save

    In view of the fact that the current integrated port energy system (IPES) considers neither the time scale difference of refrigerated containers in port scheduling nor the impact of renewable energy and load uncertainty, this paper proposes a day-ahead and intra-day two-stage rolling optimization scheduling method for a container IPES. In day-ahead scheduling, based on the temperature rise process of refrigerated containers, a port cold chain energy demand model is established, which is combined with the logistics process after the arrival of refrigerated containers. Then, the day-ahead output values of each unit in the system are obtained with the goal of the lowest operating cost. In intra-day scheduling, a two-layer rolling model is proposed to obtain the adjusted output of the port energy equipment, which considers the prediction error of shore power load and renewable energy as well as the different response speeds of cooling, heating and power. The calculation results show that the collaborative optimization scheduling of refrigerated containers and the container IPES can effectively reduce the port operation cost and carbon emissions. The two-stage day-ahead and intra-day rolling optimization scheduling can improve the economy and stability of the system.

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    Improved Transformer-PSO Short-Term Electricity Price Prediction Method Considering Multidimensional Influencing Factors
    SUN Xin, WANG Simin, XIE Jingdong, JIANG Hailin, WANG Sen
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1420-1431.   DOI: 10.16183/j.cnki.jsjtu.2023.065
    Abstract2639)   HTML18)    PDF(pc) (3027KB)(527)       Save

    With the construction of a diversified electricity market, the factors affecting electricity prices are gradually increasing, and the market environment has undergone more drastic changes. In order to improve the accuracy of short-term electricity price prediction, an improved Transformer-particle swarm optimization (PSO) short-term electricity price prediction method considering multiple factors affecting electricity prices is proposed. First, based on the consideration of historical electricity prices and historical loads, the relevant factors of electricity price formation are further analyzed. The autocorrelation function is used to analyze the multi-cycle characteristics of electricity price and adjust input sequence, which overcomes the problem of limited prediction accuracy caused by using historical data only and adjusting the input sequence by experience. Then, by combining long short-term memory (LSTM), self-attention mechanism, multi-layer attention mechanism, and adopting a multi-input structure, an improved Transformer model is established to further enhance the ability of the LSTM model to capture long short-term dependencies between different time step information, to overcome the information utilization bottleneck of LSTM, and to adapt to complex multiple sequence inputs including historical electricity prices and various electricity price causes. In addition, the PSO intelligent algorithm is utilized to search for the optimal learning rate of the model at different learning stages, overcoming the limitations of manually adjusting the learning rate. Finally, the PJM market electricity price is used for example analysis. The results show that the proposed short-term electricity price prediction model can be applied to the market environment where electricity prices are affected by various factors and drastic changes, and effectively improve the accuracy of short-term electricity price prediction.

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    Dispatching Method of Combined Wind-Storage System for Multi-Time Scale Scenarios Application in Electricity Markets
    YIN Gaowen, SHEN Feifan, HUANG Sheng, WEI Juan, QU Yinpeng, WANG Pengda
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1410-1419.   DOI: 10.16183/j.cnki.jsjtu.2022.493
    Abstract2530)   HTML13)    PDF(pc) (2736KB)(352)       Save

    Aimed at the coupling problem of the combined wind-storage system participating in different call time scale scenarios in electricity markets, an optimal dispatching method of the combined wind-storage system oriented to the application of multi-time scale scenarios in electricity markets is proposed to guide the combined wind-storage system to suppress short-term wind power fluctuation, and participate in the electric energy market and the reserve ancillary service market, so as to realize the collaborative optimization among different call time scale scenarios application and maximize the economic benefits of the combined wind-storage system. First, considering the profit mechanism of different scenarios, the objective function is established with the objective of maximizing the economic benefits of multiple scenarios of the combined wind-storage system. Then, the constraints of the combined wind-storage system participating in various application scenarios and multi call time scale coupling constraints are established. Finally, the numerical simulation verifies that the proposed method can improve the comprehensive operation profit of the combined wind-storage system in the day-ahead electric energy market and the reserve ancillary service market while ensuring that the wind power fluctuation does not exceed the limit.

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    Switching Modeling and Application in Fault Diagnosis Algorithm Testing of Distribution Network
    XUE Guiting, LIU Zhe, HAN Zhaoru, SHI Fang, WANG Ti, WANG Xiao
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1381-1389.   DOI: 10.16183/j.cnki.jsjtu.2023.129
    Abstract2523)   HTML6)    PDF(pc) (4150KB)(224)       Save

    Fault diagnosis in power distribution networks is crucial for fault location, enhancement of fault processing efficiency, and reduction of power outage losses. Currently, the impact of switch operations and other interferences is seldomly considered in fault diagnosis algorithm designing and testing, which may lead to frequent mal-function and poor performance in practical applications. In this paper, a detailed analysis and modeling of the transient process of switch operation in distribution networks is proposed with the combination of the Mayr and the Helmer models. The transient waveform of the on-site operation process is compared and analyzed with the simulation waveforms generated in PSCAD. Based on the accuracy verification of the model, typical fault scenarios in distribution networks, including switch operation processes, are constructed for fault diagnosis algorithm tests. Compared to the traditional model, the model proposed can simulate and generate disturbance data close to the on-site switch operation process for reliability testing of fault diagnosis algorithms. Finally, several suggestions for optimizing the fault diagnosis algorithm and testing process are proposed through result analysis.

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    Research and Development of High-Performance Magnesium Alloys for Aerospace Applications
    SU Yang, HAO Liang, LI Yangxin, ZENG Xiaoqin
    Air & Space Defense    2024, 7 (6): 1-11.  
    Abstract2463)      PDF(pc) (2081KB)(939)       Save
    Magnesium alloys, currently recognized as the lightest structural metallic material in practical engineering applications, have broad prospects for application in the aerospace field, where lightweight demands are increasing. However, the three major bottleneck issues, “relatively low absolute strength”, “ weak deformation capacity”, and “insufficient corrosion resistance”, greatly limit the application scope of traditional magnesium alloys. Based on a review of the latest application status of magnesium alloys in the aerospace field, this paper has elaborated on the research progress of high-strength, tough, and corrosion-resistant magnesium alloys and prospected the development trends of high-performance magnesium alloys in future aerospace applications.
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    Joint Economic Optimization of AGV Logistics Scheduling and Orderly Charging in a Low-Carbon Automated Terminal
    WANG Xuan, WANG Bao, CHEN Yanping, LIU Hong, MA Xiaohui
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1370-1380.   DOI: 10.16183/j.cnki.jsjtu.2023.027
    Abstract2281)   HTML13)    PDF(pc) (3702KB)(843)       Save

    To improve the current automated guided vehicle (AGV) charging strategy at automated terminals, which is not fully coordinated with the distributed power supply, a joint optimization method of AGV logistics scheduling and orderly charging is proposed. First, the synergetic relationship between AGV logistics scheduling and charging scheduling is analyzed, and a joint optimization framework is built. Then, a method to calculate the distance traveled by AGVs while considering the segregation requirements of trucks inside and outside the terminal is proposed. Afterwards, for the AGV charging module, the judgment conditions of AGV charging status and the pile selection method are defined. Furthermore, to minimize the cost of purchasing electricity at the terminal, a joint optimization model of logistics scheduling and orderly charging is constructed by considering time-of-use tariff, distributed power feed-in tariff, power balance constraint, state of charge constraint at the termination moment, upper and lower bound constraints of decision variables, and logistics scheduling constraint. Finally, a fast solution method based on improved particle swarm optimization algorithm is proposed, of which the effectiveness and economic efficiency are verified by an actual case of a terminal.

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    Cited: CSCD(1)
    Research progress of Hashimoto thyroiditis
    TIAN Limin, FENG Jing
    Journal of Internal Medicine Concepts & Practice    2024, 19 (04): 217-223.   DOI: 10.16138/j.1673-6087.2024.04.01
    Abstract2241)   HTML37)    PDF(pc) (973KB)(916)       Save

    Hashimoto thyroiditis (HT) is a very common organic autoimmune thyroid disease, and its incidence is increasing year by year. It not only causes hypothyroidism in clinical practice, but also has many connections with a variety of immune diseases, endocrine diseases, rheumatic diseases and thyroid cancer. Although the exact etiology of HT has not been fully clarified, the mainstream treatment is still based on management and alternative treatment of hypothyroidism. However, as the research further deepens, more clinical variants have been gradually discovered, more and more factors have been found to be related to the onset of HT, and new discoveries have been made in treatment methods. This article reviews the research progress on clinical manifestations, pathological features, diagnosis, pathogenesis, relationship with other diseases and treatment of HT.

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    Pattern Recognition and Ultra-Short-Term Probabilistic Forecasting of Power Fluctuating in Aggregated Distributed Photovoltaics Clusters
    WANG Yubo, HAO Ling, XU Fei, CHEN Wenbin, ZHENG Libin, CHEN Lei, MIN Yong
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1334-1343.   DOI: 10.16183/j.cnki.jsjtu.2023.048
    Abstract2235)   HTML9)    PDF(pc) (4167KB)(501)       Save

    The quantitative evaluation of the uncertainty in distributed photovoltaic power is significant for the safe and stable operation of distribution network. Considering the significant differences in power characteristics of different output fluctuation patterns, in order to obtain a prediction model suitable for different fluctuation patterns and to perform a refined assessment of power uncertainty, this paper proposes a method for pattern recognition and ultra-short-term probabilistic forecasting of power fluctuating in aggregated distributed photovoltaic clusters. First, the satellite cloud images and photovoltaic power data are integrated, and the pattern recognition model of fluctuation is constructed via the feature extraction of power fluctuation, realizing the mining of fluctuation rules. On this basis, the difference in predictability of different fluctuation patterns and the correlation between fluctuation patterns and prediction errors are considered via classification modeling, so that the width of prediction interval can better adapt to the characteristics of prediction error distribution. Thus, refined consideration of power uncertainty of different fluctuation patterns is realized to improve the precision of probabilistic prediction, provide more references for power grid dispatching, and weaken the influence of the strong volatility in distributed photovoltaic power on the power system.

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    Parameter Control of Adaptive Bistable Point Absorber Wave Energy Converter in Irregular Waves
    LI Yang, ZHANG Xiantao, XIAO Longfei
    Journal of Shanghai Jiao Tong University    2025, 59 (3): 293-302.   DOI: 10.16183/j.cnki.jsjtu.2023.309
    Abstract2209)   HTML19)    PDF(pc) (4987KB)(371)       Save

    Although the adaptive bistable wave energy generation device solves the problem that the bistable system may be difficult to cross the barrier when the amplitude of the incident wave is small, its efficiency can still be improved. Previous studies have proved that the change of the parameters of the device will have a great impact on its performance, and the optimal device parameters are closely related to the spectral peak frequency at a given time. Therefore, in the control study of the device, a control scheme is designed and the device parameters are adjusted accordingly in order to improve efficiency assuming that the peak frequency within a period of time is predictable. In this study, three control parameters are selected, and the optimal device parameter library with different spectral peak frequencies is determined by simulation calculation. The control module is then added to the simulation program to control the parameters by interpolation. The results show that the device with variable parameter control improves energy capture efficiency.

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    Online Monitoring Method for Inertial Support Capacity of Point-to-Grid in New Power Systems
    DENG Xiaoyu, LIU Muyang, CHANG Xiqiang, NAN Dongliang, MO Ruo, CHEN Junru
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1390-1399.   DOI: 10.16183/j.cnki.jsjtu.2023.029
    Abstract2171)   HTML10)    PDF(pc) (2472KB)(109)       Save

    An accurate and timely monitoring for the inertia support capability of the point of interconnection of aggregated sources to the grid in a low-inertia new power system is crucial for the safety, stability, and economic operation of the system. In order to explain the basic idea of the online point-to-grid inertia monitoring method, the definition of inertia of power system based on the swing equation and existing online monitoring methods are analyzed. Then, in order to improve the accuracy of the existing online inertia monitoring method, an equivalent inertia constant identification method based on the regression method is developed. Combining the proposed inertia constant identification method with the online inertia monitoring method, a systematic method for online monitoring of the inertia support capacity of point-to-grid in new power system is developed based on synchronous phasor measurement units. Finally, the simulation analysis of a modified New England 10-machine 39-bus system proves the accuracy and the feasibility of the developed real-time inertia monitoring method for the new power system.

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    Robust Optimal Scheduling of Micro Energy Grid Considering Multi-Interval Uncertainty Set of Source-Load and Integrated Demand Response
    MI Yang, FU Qixin, ZHAO Haihui, MA Siyuan, WANG Yufei
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1323-1333.   DOI: 10.16183/j.cnki.jsjtu.2023.022
    Abstract2138)   HTML8)    PDF(pc) (1898KB)(449)       Save

    Aiming at the uncertainty of the source and load in micro energy grid, a robust optimal scheduling model considering multi-interval uncertainty set of source-load and integrated demand response is proposed. First, considering the uncertainty of wind power, photovoltaic output and electric, and thermal and cooling loads in the micro energy grid, a multi-interval uncertainty set of source-load is established. Then, in order to fully tap the potential of load side dispatching, an integrated demand response model is established, which includes reducible electric load, transferable electric load, flexible cooling, heating load, and replaceable load, based on which, the uncertainty of integrated demand response is considered. Afterwards, with the lowest dispatching cost of micro energy grid as the objective function, a two-stage robust optimal scheduling model of micro energy network is constructed, which considers the multi-interval uncertainty set of source load and the integrated demand response. The model is solved by the column and constraint generation algorithm, the strong duality theory, and the large M method. Finally, the rationality and effectiveness of the proposed model are verified through the analysis of numerical examples.

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    A Short-Term Carbon Emission Accounting Method for Power Industry Using Electricity Data Based on a Combined Model of CNN and LightGBM
    ZENG Jincan, HE Gengsheng, LI Yaowang, DU Ershun, ZHANG Ning, ZHU Haojun
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 746-757.   DOI: 10.16183/j.cnki.jsjtu.2023.382
    Abstract2088)   HTML3)    PDF(pc) (6089KB)(3092)       Save

    The electric power industry plays a pivotal role in carbon emission control. Accurate and real-time accounting of carbon emissions in the power industry is essential for supporting the carbon reduction of the power industry. At present, the measurement of carbon emissions in the power industry relies mainly on direct measurement or the accounting methods, which often struggles to balance low measurement costs with real-time accuracy. Therefore, in this paper, the robust power data infrastructure in the power industry is leveraged and the correlation between electricity consumption and carbon emissions is explored to propose a short-term electricity-to-carbon method using machine learning methods based on historical data of electricity. This method utilizes convolutional neural networks (CNNs) for feature extraction, and light gradient boosting machine (LightGBM) for carbon emission estimation based on extracted features. Moreover, K-fold cross-validation is used in model training, with parameter optimization using grid search to enhance the generalization capability and robustness of the model. To validate the proposed method, it is compared with other machine learning models under the same data segmentation condition for daily and hourly data sets. The results indicate that the proposed model outperforms other models in both performance evaluation and the consistency between estimated and target values.

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    Coordinate Scheduling Model of Electric Vehicle-Unmanned Aerial Vehicle Joint Rescue System
    BAI Wenchao, BAN Mingfei, SONG Meng, XIA Shiwei, LI Zhiyi, SONG Wenlong
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1443-1453.   DOI: 10.16183/j.cnki.jsjtu.2023.052
    Abstract2080)   HTML12)    PDF(pc) (3151KB)(518)       Save

    The rapid development of electric vehicles (EVs) and unmanned aerial vehicles (UAVs) provides new ways for personnel search and material distribution during emergency periods. This paper proposes an EV-UAV joint rescue system, in which the UAVs use the EVs as charging and maintenance base stations to provide various services for the objects to be rescued, and the EVs can use distributed generations to obtain diversified electricity supply, which improves the adaptability and endurance level of the system in emergencies. The coordinated scheduling model of the EV-UAV system is established in the mixed-integer linear programming (MILP) formulation, which considers factors including electricity consumption, electricity replenishment, loading capacity, distribution route, and distribution time window of the EVs and the UAVs. Case studies verify the validity of the model proposed, compare the EV-UAV and ground vehicle (GV)-UAV rescue systems, and illustrate the technical characteristics and application potential of the EV-UAV system in emergency assistance.

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    Influence of DC-Bus Voltage on Synchronization Stability of Grid-Following Converters
    SI Wenjia, CHEN Junru, ZHANG Chenglin, LIU Muyang
    Journal of Shanghai Jiao Tong University    2025, 59 (3): 313-322.   DOI: 10.16183/j.cnki.jsjtu.2023.321
    Abstract2071)   HTML7)    PDF(pc) (2943KB)(251)       Save

    With the increasing penetration of new energy sources and the development of new power systems, grid-following converter (GFL) plays a crucial role in maintaining the stability of power systems. However, existing transient stability analyses of GFLs assume that the direct current (DC) side behaves as a constant-voltage source, neglecting the effects of DC-bus voltage control. This paper aims to investigate the transient instability mechanism of GFL considering DC-bus voltage control. First, a transient synchronous stability model considering DC voltage control is established, followed by an analysis of the transient synchronous stability of GFL under DC-bus voltage control. The findings indicate that DC voltage control increases the active current reference value and decreases the equivalent damping of the GFL, which in turn reduces its transient synchronous stability of GFL. By increasing the proportional coefficient or reducing the integral coefficient of DC-bus voltage control, transient synchronous stability can be appropriately improved. Finally, the theoretical analysis is validated through MATLAB/Simulink simulations.

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    Robust Optimal Scheduling of Agricultural Microgrid Combined with Irrigation System Under Uncertainty Conditions
    YANG Sen, GUO Ning, ZHANG Shouming
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1432-1442.   DOI: 10.16183/j.cnki.jsjtu.2023.035
    Abstract2070)   HTML9)    PDF(pc) (2680KB)(172)       Save

    Agricultural microgrids offer a promising solution for energy supply in remote rural areas in a low-cost manner. In this paper, under uncertain conditions of renewable energy output and electricity load demand, a robust optimal scheduling model combined with the isolated agricultural microgrid and irrigation system containing a pumped hydro storage (PHS) power station is proposed, considering the factors that the wind-landscape pumped storage integrated agricultural microgrid can satisfy the uncertain fluctuations of power load demand and water load demand. By utilizing the abundant water resources in rural areas and the advantages of landscape drainage and storage compensation, the total cost of the system is minimized while the absorption of renewable energy is increased. Considering distributed generation, power load demand and water load demand, turbine flow, and irrigation flow, the proposed model is characterized by diversity, multi-constraint, and discontinuity. A gravitational whale optimization algorithm (GWOA) is proposed to solve the model. The simulation results of an agricultural microgrid show that the GWOA can obtain a more competitive solution than the CPLEX solver and other newly developed algorithms do. In addition, the impact of the change of water load demand caused by precipitation uncertainty on the operating cost of the irrigation system and the necessity of using PHS power station are explored.

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    Trends in global major disease burden and health conditions—interpretation of the Global Burden of Disease Study 1990-2021
    FAN Bonan, LI Yan
    Journal of Diagnostics Concepts & Practice    2024, 23 (05): 474-483.   DOI: 10.16150/j.1671-2870.2024.05.003
    Abstract2051)   HTML64)    PDF(pc) (3009KB)(4813)       Save

    The Global Burden of Disease Study 2021 (GBD 2021) analyzed 371 diseases and injuries using 100,983 data sources, estimating years lived with disability, years of life lost, disability-adjusted life years, and healthy life expectancy. From 1990 to 2019, the annual rate of change in global all-cause mortality ranged from -0.9% to 2.4%, while deaths increased by 10.8% and 7.5% in 2020 and 2021 respectively due to COVID-19. In 2021, COVID-19 was the second lea-ding cause of death globally, with a mortality rate of 94.0 per 100 000. The mortality rates of other major causes, such as ischemic heart disease and stroke were 108.7 and 87.4 per 100 000, respectively. Global life expectancy rose from 65.5 years in 1990 to 73.3 years in 2019 but dropped to 71.7 years in 2021 due to COVID-19, which reduced life expectancy by 2.2 years, significantly impacting the trend of health improvement. In China, GBD 2021 data shows a significant increase in life expectancy from 1990 to 2021: from 69.9 to 80.7 years for women and from 65.7 to 74.9 years for men. However, non-communicable diseases such as cardiovascular diseases, cancers, and chronic respiratory diseases remain major health threats. In 2021, these diseases had the highest burden among the top ten causes in China, with rising incidence and morta-lity rates. Major health risk factors in China include tobacco, hypertension, and dietary risks. This paper, through the systematic analysis of GBD 2021 data, reveals current trends in disease burden globally and in China, and proposes public health strategy recommendations. China should enhance chronic disease management, improve public health emergency responses, address health inequalities, and promote basic research and international cooperation to improve overall health levels.

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    Shared Energy Storage Multi-Objective Allocation Strategy Considering Integrated Energy Microgrid Access to Active Distribution Network
    MI Yang, CHEN Yuyang, CHEN Boyang, HAN Yunhao, YUAN Minghan
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1309-1322.   DOI: 10.16183/j.cnki.jsjtu.2023.021
    Abstract2026)   HTML16)    PDF(pc) (4556KB)(234)       Save

    In order to give full play to the advantages of shared energy storage in improving economy and energy utilization, while considering the role of multi-energy complementation and coupling of integrated energy microgrids in active distribution networks, a multi-objective optimal allocation strategy of shared energy storage is proposed for the active distribution network connected with integrated energy microgrid. First, the optimization objectives of the economy and voltage stability of the distribution network and the configuration capacity of the shared energy storage are analyzed, the coordinated operation of the source-net-load side multi-flexible resources of the active distribution network is considered, and the active distribution network and the integrated energy microgrid are modeled. Then, the model is solved based on the Pareto optimal multi-objective particle swarm algorithm. Finally, the optimization algorithm of shared energy storage configuration is established in conjunction with the IEEE 33-node distribution system to verify the effectiveness of the proposed configuration strategy.

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    An Optimization Method for Iteration Path Search of Large-Scale Power Grid Unit Commitment State
    CUI Yiyang, PAN Dounan, LI Canbing, LIU Jianzhe
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 711-719.   DOI: 10.16183/j.cnki.jsjtu.2024.301
    Abstract2003)   HTML15)    PDF(pc) (1544KB)(40)       Save

    To address the computational challenge posed by the “curse of dimensionality” inherent in traditional branch and bound algorithms for large-scale power grid unit commitment problems, an optimization method for iteration path search of unit commitment state is proposed. To prevent the loss of the optimal solution due to the simplification of the problem and the reduction of the feasible region, the determination of the unit state scheme is divided into a two-stage process of depth traverse and breadth iteration. Based on an initial solution, the unit dynamic priority list is used as the search direction for the unit state iteration path. In deep traverse stage, the optimal shutdown redundant units and their corresponding shutdown time are determined. Breadth iteration is then used to expand the feasible region of the problem to improve the optimality of the solution. The results of a comparative case study conducted on the IEEE 118 system and ACTIVSg10k system indicate that the proposed method effectively reduces the scale of the problem, minimizes the number of unit state attempts, and achieves efficient search and iteration of unit states, exhibiting fast computational speed, high efficiency, which has practical applicability for solving problems of large-scale unit commitment.

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    A Review of Equivalent Model-Based State of Charge Estimation Algorithms of Lithium-Ion Battery
    TANG Diyin, WANG Yufu, ZHENG Wenjian, HUANG Xucong, XING Yalan
    Air & Space Defense    2024, 7 (6): 104-111.  
    Abstract1987)      PDF(pc) (1086KB)(1331)       Save
    Due to their high energy density and long life, Lithium-ion batteries are widely applied in fields such as aerospace and smart driving. Accurate estimation of the state of charge (SOC) of a battery is critical. In recent years, SOC estimation methods based on battery equivalent models have been widely used because oftheir advantages of accurate estimation and easy understanding. This paper has elaborated on the classification of battery equivalent models, SOC estimation algorithms, and factors affecting SOC estimation from three aspects. Firstly, the common types of battery models and their characteristics were analyzed; secondly, the commonly used SOC estimation techniques based on battery models were reviewed; finally, the factors affecting the accuracy of SOC estimation and possible solutions were analyzed. The summary of this paper provides references for future research.
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    Research Progress on High-Temperature Resistant Wave Transparent Silicon Nitride Based Ceramics
    YAO Dongxu, YU Xing, GU Hao, LI Jiahao, LIU Wen, LI Rui
    Air & Space Defense    2024, 7 (6): 46-57.  
    Abstract1959)      PDF(pc) (2858KB)(635)       Save
    Silicon nitride ceramics comprehensively have excellent properties such as high strength, high elastic modulus, high-temperature resistance, thermal shock resistance, and low dielectric constant. They are the major candidate materials for high-temperature wave transmitting radome. Currently, research in silicon nitride-based ceramics and composites is popular. This paper has reviewed the research status of silicon nitride ceramics, SiALON ceramics, silicon oxynitride ceramics, nitrogen oxide ceramics, and their composite materials in the past five years. Through the combination of material design and different molding processes, including 3D printing, chemical vapor infiltration (CVI), and precursor impregnation cracking (PIP), the preparation of high-strength-low dielectric silicon nitride-based ceramic materials was acquired, which enables the selection of materials and design support for wavetransparent components of high-Mach vehicles.
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    Distributed Photovoltaic Power Outlier Detection Based on Quantile Regression Neural Network
    WANG Xiaoqian, ZHOU Yusheng, MAO Yuanjun, LI Bin, ZHOU Wenqing, SU Sheng
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 836-844.   DOI: 10.16183/j.cnki.jsjtu.2023.412
    Abstract1958)   HTML1)    PDF(pc) (3885KB)(68)       Save

    The distributed photovoltaic power generation system is widely dispersed and lacks a scientific and standardized operation and maintenance management system. Due to the limited availability of data, it is difficult to accurately detect abnormal conditions in photovoltaic devices caused by fluctuations in weather. In this paper, according to the operation and maintenance status and data characteristics of distributed photovoltaic, a quantile regression neural network (QRNN)-based method is proposed for detecting photovoltaic power outliers. First, the solar irradiance characteristics of sunny days are analyzed, and the influence of rainy weather is excluded by using a sunny day screening method. Then, the power output correlation of different power stations is analyzed to identify the photovoltaic stations with high power output correlation, which is used as a horizontal reference. Subsequently, the curves of the power output of the stations tested on different sunny days are compared vertically to eliminate the interfering factors such as weather and environmental conditions. The measured active power data is fed into the QRNN model to establish the normal active power range for the photovoltaic system, whose threshold is used to detect photovoltaic power outliers. The simulation results of actual photovoltaic system data show that the method proposed can eliminate the meteorological influence, accurately identify the faulty photovoltaic system, and promote the fine operation and maintenance of distributed photovoltaic.

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    Research Progress on Lightweight Resin-Based Thermal Protection Materials
    LI Liang, REN Zhiyi, WANG Peng, LUO Yi, SU Zhe, CAI Hongxiang, TIAN Hao, NIU Bo, LONG Donghui
    Air & Space Defense    2024, 7 (6): 58-75.  
    Abstract1944)      PDF(pc) (5237KB)(736)       Save
    Thermal protection systems are significantly important in modern aerospace engineering. When the new generation of vehicles evolves towards higher Mach flight speeds, there is an increasing demand for thermal protection systems that could combine high-temperature resistance, lightweight construction, and integrated thermal protection and insulation. This paper has reviewed the research progress on lightweight resin-based thermal protection materials domestically and internationally and analyzed their development trends in enhanced oxidation resistance, nanoporous structures, and gradient designs. Besides, this study has introduced the thermal protection and insulation mechanisms as well as the mechanical failure mechanisms of nanoporous resin-based materials, thus providing valuable insights for effective design and fabrication.
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    Unit Commitment Optimization Model Considering Impact of Multiple Operating Conditions on Unit Life Loss
    LUO Yifu, HU Qinran, QIAN Tao, CHEN Tao, ZHANG Yuanshi, ZHANG Fei, WANG Qi
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 768-779.   DOI: 10.16183/j.cnki.jsjtu.2023.401
    Abstract1905)   HTML5)    PDF(pc) (3746KB)(759)       Save

    Thermal power units face a dilemma of accelerated lifespan degradation and extended service duration. On one hand, large-scale integration of new energy sources has increased peak shaving conditions and accelerated losses of the units. On the other hand, service units will reach designed lifespan before carbon neutrality is achieved, while flexible operation of the power system necessitates extending their service life of units. Therefore, it is of great significance to consider the losses caused by varicus operating conditions on the lifespan of the unit and optimize the operating structure of the unit in scheduling simulation for unit longevity and carbon reduction efforts. To make unit life losses in theoretical research more practical, the traditional model that averages the losses in deep peak shaving conditions has been discarded. Instead, new judgment criteria for conventional and various special operating conditions of thermal power units are established. The lifespan loss cost of the unit is integrated into the operating objective function and the corresponding constraint conditions are modified. Finally, a unit commitment model considering the multi-operating condition lifespan losses of thermal power units is constructed. Example simulations indicate that the conventional model underestimates the actual loss cost of the units. In constrast, the proposed model can not only reduce the operating cost and unit life loss by considering the lifespan impacts of multi-operating conditions, but also enhance the peak shaving capacity of thermal power units and promote wind power consumption.

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    Preparation and Electromagnetic Properties of ZIF-67 Derived Carbon Spheres Loaded on Graphene
    LIU Zhenglin, ZHA Borui, WEI Bo, ZHOU Jintang, TAO Jiaqi, CHENG Zhenyu, LIU Jun, WU Fan
    Air & Space Defense    2024, 7 (6): 120-127.  
    Abstract1900)      PDF(pc) (2413KB)(689)       Save
    With the arrival of the 5G era, electromagnetic pollution has also become a new public concern, which has already received extensive attention from the social and scientific communities. Thus, it’s significant to develop materials with efficient microwave absorption properties. In this paper, a simple preparation method was used to uniformly load spherical ZIF-67 on graphene nanosheets, and a novel electromagnetic wave absorbing material consisting of twodimensional (2D) and three-dimensional (3D) materials was achieved after high-temperature annealing (spherical ZIF-67 derived carbon spheres loaded on graphene, Co@C/GNs ). Conductivity loss, natural resonance and exchange resonance in the low and middle-frequency bands, as well as polarization loss and eddy current loss in the high-frequency band, can together enhance the effective absorption of electromagnetic waves. Among them, wave absorbers with 5% graphene by mass of ZIF-67 have the best wave absorbing performance, with the minimum reflection loss value of − 31.66 dB at a matching thickness of 2.5 mm and the effective bandwidth up to 5.56 GHz at a matching thickness of 1.5 mm. This work provides an alternative option for the preparation of electromagnetic absorbing composites.
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    Research and Development of High-Temperature Titanium Alloys for Hypersonic Aircraft
    CHEN Zhiyong
    Air & Space Defense    2024, 7 (6): 38-45.  
    Abstract1862)      PDF(pc) (1510KB)(887)       Save
    High-temperature titanium alloys allow broad application prospects in hypersonic aircraft. They have ideal lightweight and heat-resistant metallic materials, enhancing the performance and reliability of hypersonic aircraft in extreme flight environments, thus achieving higher speeds and longer flight distances. Considering the services of thermal structures in China’s hypersonic aircraft, starting from the characteristics of high-temperature titanium alloys, this paper has reviewed the latest development status of high-temperature titanium alloys domestically and abroad. It focused on introducing China’s independent research, development and application of 550-650 °C high-temperature titanium alloys. To achieve higher operating temperature requirements, the research and development of a new 700-750 °C high-temperature titanium alloy Ti750S was proposed, and the respective application directions and prospects of high-temperature titanium alloys for future hypersonic aircraft were prospected.
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    Optimal Scheduling Strategy of Newly-Built Microgrid in Small Sample Data-Driven Mode
    CHEN Shi, YANG Linsen, LIU Yihong, LUO Huan, ZANG Tianlei, ZHOU Buxiang
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 732-745.   DOI: 10.16183/j.cnki.jsjtu.2023.394
    Abstract1852)   HTML6)    PDF(pc) (4880KB)(200)       Save

    Newly built microgrids lack historical operation data, making it challenging to predict renewable power output accurately using conventional data-driven methods, which in turn affects the accuracy of scheduling plans. To address this problem, an optimal scheduling method for newly built microgrids in scenarios with limited sample data is proposed. First, an improved network structure integrating a domain adversarial neural network with a long-short-term memory network is designed. The domain adversarial approach and gradient inversion mechanism are incorporated into transfer learning to improve the generalization ability of the model. This reduces the domain distribution discrepancy in the data, and uses the rich operation data of power stations with similar output characteristics to predict the output of the target station, which overcomes the challenge of poor accuracy under the conditions of small samples. Additionally, the optimal scheduling model is transformed into a Markov decision process and solved using double-delay deep deterministic policy gradient algorithm. Finally, the effectiveness of the proposed method is validated through a case study involving an improved CIGRE 14-node microgrid.

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    Reliability Allocation Method for Electric Aircraft Lightweight Propulsion System
    LI Jinghao, LI Ran, HUA Hao, HUANG Wentao, GAO Fei, TAI Nengling
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 867-876.   DOI: 10.16183/j.cnki.jsjtu.2023.425
    Abstract1805)   HTML4)    PDF(pc) (2862KB)(214)       Save

    In order to solve the contradiction between lightweight and high reliability in the electric aircraft electric propulsion system, a reliability allocation method considering lightweight constraint is proposed for the first time. An analytical expression between weight and reliability is integrated into the electric propulsion system design model as constraints, and a flexible “weight-reliability” optimization method is proposed, considering the uncertainty of the operating conditions of electric aircraft. This method achieves minimum weight under reliability constraints and maximum reliability under weight constraints. Taking the “Spirit of Innovation” electric aircraft as an example, the results show that the proposed method can reduce the total weight of the power system of the electric aircraft by 3.5% while ensuring the reliability of the system. The applicability of the proposed method is verified in different scenarios designed, providing technical support for the development of high power-to-weight ratio in electric aircrafts.

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    Detection of Foreign Bodies in Transmission Line Channels Based on Fusion of Swin Transformer and YOLOv5
    XUE Ang, JIANG Enyu, ZHANG Wentao, LIN Shunfu, MI Yang
    Journal of Shanghai Jiao Tong University    2025, 59 (3): 413-423.   DOI: 10.16183/j.cnki.jsjtu.2023.301
    Abstract1802)   HTML7)    PDF(pc) (26717KB)(468)       Save

    To address the challenges of complex detection background and poor detection performance for small targets, a transmission line channel security detection algorithm based on the fusion of window self-attention network and the YOLOv5 model is proposed. First, the Swin Transformer (S-T) is employed to optimize the backbone network, expanding the perception field of the model and enhancing its ability to extract effective information. Then, the adaptive spatial feature fusion (ASFF) module is improved to enhance the feature fusion ability of the model. Finally, considering the mismatch between the real frame and the predicted frame, the structural similarity intersection over union (SIoU) is introduced to optimize the boundary errors and improve the generalization ability of the model. The experimental results show that the model proposed achieves a multi-target intrusion detection accuracy of 90.2%, and with significant improvements in the detection of small targets. This approach better meets the requirements of foreign object detection in transmission line channels compared to other object detection algorithms.

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    DC-Bus Voltage Oscillation Suppressor Based on Active Capacitor and Its Control Method
    YANG Jipei, YANG Ling, WEI Maohua
    Journal of Shanghai Jiao Tong University    2025, 59 (3): 303-312.   DOI: 10.16183/j.cnki.jsjtu.2023.327
    Abstract1775)   HTML18)    PDF(pc) (8081KB)(186)       Save

    The constant power load (CPL) in a DC microgrid can reduce the effective damping of the system, resulting in high frequency voltage oscillations on the DC bus, which threatens the safe and stable operation of the system. To address this issue, this paper proposes a DC-bus voltage oscillation suppressor based on an active capacitor and its control method. The oscillation suppressor is connected in parallel to the DC bus, enabling direct interaction with the DC bus. The energy storage capacitor in the oscillator suppressor effectively stores the transient energy generated by voltage oscillations, thereby reducing the amplitude of voltage oscillation and improving the voltage stability of the bus. The voltage of the power supply in the oscillation suppressor adapts to the voltage of the DC bus, allowing for stable operation in the face of load changes in the system. The design offers advantages such as plug-and-play functionality, strong applicability, and flexible control. In addition, by analyzing the operating mode and mechanism of the oscillation suppressor, a small signal model is established, and the influence of controller parameters on the stability and dynamic performance of the suppressor is analyzed, based on which the controller parameter optimization scheme is proposed. Finally, the effectiveness of the oscillatory suppressor is validated through the experimental results.

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    Damage Monitoring Method for Deep-Sea Net Cage Rope Structure Based on Tension Signal
    YANG Mengjie, REN Haojie, REN Hao, XU Yuwang, ZHANG Mengmeng
    Journal of Shanghai Jiao Tong University    2025, 59 (4): 550-560.   DOI: 10.16183/j.cnki.jsjtu.2023.372
    Abstract1750)   HTML4)    PDF(pc) (6465KB)(445)       Save

    The net system is an important component of the deep-sea net cages. As the bone structure of the net system, the rope structure bears the main hydrodynamic load of the net system, making the monitoring its health status essential. Aiming at the online damage monitoring of the rope structure, a finite element numerical model of the rope structure is developed, and the mechanical properties of the rope structure under intact and damaged conditions are compared and analyzed. The results show that when the rope is damaged, the end tension load of the damaged rope decreases sharply, while the end tension load of the adjacent rope increases. Based on the characteristics of these sudden tension changes and the influence of the damaged rope on the load of undamaged rope, three damage identification parameters are defined as the tension correlation coefficient, the total influence value, and the tension variation coefficient of the rope structure. Additionly, an online damage monitoring method based on rope tension signal is proposed. This method identifies the damaged rope by detecting an extremum step in the tension variation coefficient, and determines the specific damaged position by analyzing the proportion relationship between the tension change coefficient and the distance from the end to the damaged position. The research provides a reliable method for online monitoring of rope structure damage for the healthy operation and maintenance of deep-sea net cages.

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    Oscillatory Stability Assessment of Renewable Power Systems Based on Frequency-Domain Modal Analysis
    GAO Lei, MA Junchao, LÜ Jing, LIU Jianing, WANG Chenxu, CAI Xu
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 821-835.   DOI: 10.16183/j.cnki.jsjtu.2023.358
    Abstract1749)   HTML2)    PDF(pc) (4521KB)(843)       Save

    The increasing penetration of the renewable energy has increased the risks of sub/super synchronous oscillations in power systems. Therefore, it is critical to accurately evaluate the oscillatory stability of renewable power systems ensuring the safe and stable operation of the systems. In this paper, a method for evaluating the oscillatory stability of renewable power systems based on frequency-domain modal analysis is investigated. First, the frequency-domain impedance or admittance models of key equipment and stations are established, including the renewable power generators and stations, transmission lines, synchronous generators, transformers, etc. Next, a system-level frequency-domain network model is constructed based on the actual system topology. Then, the oscillatory stability of the renewable power system is evaluated by solving the zeros of the determinant of the loop impedance matrix or the node admittance matrix of the system. The weak points of the system are identified using the participated matrix of the weak oscillation mode, which provides reference for implementation of oscillation suppression measures. Taking the practical renewable power system in East China as an example, the oscillatory stability of the system considering the varying access capacity of renewables under different grid operating conditions is assessed using the frequency-domain modal analysis method. Finally, the time-domain simulation model of the actual renewable power system is built in PSCAD/EMTDC to verify the theoretical analysis.

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    Irregular Wave Groups Simulation Based on Semi-Mixed Eulerian-Lagrangian Boundary Element Method
    XUE Wen, GAO Zhiliang
    Journal of Shanghai Jiao Tong University    2025, 59 (4): 435-446.   DOI: 10.16183/j.cnki.jsjtu.2023.302
    Abstract1735)   HTML13)    PDF(pc) (3375KB)(121)       Save

    In order to effectively simulate irregular wave groups that better represent the characteristics of real waves, a numerical wave tank based on a semi-mixed Eulerian-Lagrangian algorithm combined with boundary element method was developed in conjunction with a theoretical generation method for irregular wave groups. First, the impact of model parameters on the numerical solution was analyzed. The results showed that the accuracy of wave simulation improved with an increase in damping layer length or a decrease in the time step. Additionly, selecting appropriate deviation distance, distribution range, and the number of source points can balance computation accuracy and stability. Then, unidirectional irregular wave groups were simulated based on the verified model parameters. The numerical results were compared with the physical test data and theoretical values to validate the performance of the numerical tank in simulating irregular wave groups. The findings indicated that the developed numerical wave tank can effectively simulate the generation and propagation of irregular wave groups.

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    Dual-Transformer Series Resonant Converter with Full Range ZVS Operation
    LI Yinan, HU Song, LI Xiaodong, CHEN Wu, ZHONG Liping, YANG Qingqing
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 789-799.   DOI: 10.16183/j.cnki.jsjtu.2023.389
    Abstract1728)   HTML1)    PDF(pc) (4847KB)(217)       Save

    A dual-transformer series resonant converter (DTSRC) is proposed to solve the problem of excessive return power and loss of zero voltage switching (ZVS) operation under light load in the dual bridge resonant converter (DBRC). A dual-transformer structure is employed on the proposed converter, which can significantly reduce voltage stress across the transformers. Additionally, the ZVS operation under light-load conditions is achieved and switching losses are minimized by optimizing the turns ratio coefficient. To eliminate backflow power and reduce conduction loss, a minimum current trajectory (MCT) control strategy is implemented for the DTSRC. Thus, synchronous rectification is realized on the secondary side, which makes the converter always operate with minimum current. Finally, a 200 W/100 kHz prototype is built to verify the effectiveness of the proposed solution. The experimental results demonstrate that the ZVS of all active switches is achieved during full power ranges, and the overall operating efficiency of DTSRC exceeds 90%.

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    Reactive Power-Voltage Droop Gain Online Tuning Method of Photovoltaic Inverters for Improvement of Stable Output Power Capability in Weak Grids
    WANG Yuyang, ZHANG Chen, ZHANG Yu, WANG Yiming, XU Po, CAI Xu
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 845-856.   DOI: 10.16183/j.cnki.jsjtu.2023.353
    Abstract1726)   HTML2)    PDF(pc) (7800KB)(1501)       Save

    The active power output capability and small signal stability in weak grids are key factors that limit stable photovoltaic (PV) power generation. To improve stably generating PV power in weak grids, an adaptive control method for PV inverters based on online tuning of the reactive power-voltage (Q-V) droop gain is proposed. First, to ensure active power output capability in weak grids, a “first optimization” method for the Q-V droop gain is proposed, considering voltage and current constraints. Then, to address stability constraints in weak grids, impedance modeling and stability analysis of the PV inverter system are conducted. A mapping relationship between the “parameter-weakest pole” is established with the weakest pole of the closed-loop system as a stability constraint based on the artificial neural network. A “second adjustment” method for the Q-V droop gain is developed at stably generating active power. Combined with the extended Kalman-filter-based grid impedance estimation, the proposed Q-V droop gain adaptive tuning method is realized. The effectiveness of the proposed adaptive control method is validated on the Modeling Tech real-time simulation platform.

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    Multi-Objective Optimization Design of Ship Propulsion Shafting Based on Response Surface Methodology and Genetic Algorithm
    ZHANG Cong, SHU Bingnan, ZHANG Jiangtao, JIN Yong
    Journal of Shanghai Jiao Tong University    2025, 59 (4): 466-475.   DOI: 10.16183/j.cnki.jsjtu.2023.318
    Abstract1704)   HTML10)    PDF(pc) (9630KB)(642)       Save

    In order to reduce the power loss of the transmission equipment, enhance the transmission efficiency of the propulsion shafting, and improve the vibration performance of the shafting, a multi-objective optimization design of a ship shafting experimental platform is performed based on the response surface model and genetic algorithm. The central composite design (CCD) method is used to select appropriate experimental points in the optimized design space, and the response surface model is developed with minimum total power consumption and vibration response amplitude. Based on the genetic algorithm, the Pareto optimal solution of response surface model regression function is solved through MATLAB software. The optimal design scheme is obtained by comparing and analyzing several groups of optimization results. The results show that the combined method can reduce the power loss of shafting by approximate 7.10% and reduce the vibration amplitude of shafting by 2.30%, while significantly improving the shafting transmission efficiency and effectively suppressing the vibration problem of propulsion shafting. The fiudings validate the feasibility of the multi-objective optimization method for the ship propulsion shafting.

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    Self-Adaptive Secondary Frequency Regulation Strategy Based on Distributed Model Predictive Control
    CAO Yongji, ZHANG Jiangfeng, WANG Tianyu, ZHENG Keke, WU Qiuwei
    Journal of Shanghai Jiao Tong University    2025, 59 (3): 333-341.   DOI: 10.16183/j.cnki.jsjtu.2023.352
    Abstract1703)   HTML16)    PDF(pc) (3126KB)(605)       Save

    To address the issues of reduced adaptability of secondary frequency regulation caused by changes in power system parameters, a self-adaptive secondary frequency regulation strategy based on distributed model predictive control (DMPC) is proposed. First, a model of a multi-area interconnected power system is built. Based on the frequency response trajectory, a parameter identification model for each area of the system is established. Then, the recursive least square method is used to solve the parameter identification model and update the parameters of each area online. Additionally, with the objective to minimize the area control error (ACE), DMPC is adopted to optimize the power of generators for secondary frequency regulation. Finally, a case study is conducted to demonstrate the effectiveness of the proposed strategy.

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    Asynchronous Coordinated Control Method for Regional Multi-Agent Integrated Energy Systems Considering Voltage Deviation
    LU Bin, WANG Yixiao, PU Chuanqing, CHEN Yunhui, CHEN Bobo, FAN Feilong
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 758-767.   DOI: 10.16183/j.cnki.jsjtu.2023.369
    Abstract1703)   HTML4)    PDF(pc) (3337KB)(520)       Save

    In order to address the power demand and voltage control challenges of a multi-energy network of electricity, heat, and gas coupled within an integrated energy system is an urban park, a distributed coordination methodology that incorporates voltage deviation control is proposed. First, operation models for local equipment and power flow coupling optimization in the electricity-gas-heat network are established. Then, a multi-objective day-ahead dispatch model and a local dispatch model for each agent are proposed, aiming to minimize both the overall operating cost and the mean voltage deviation. To achieve this, an asynchronous coordination approach based on preference prior expressions and the alternating direction method of multipliers (ADMM) is employed to enable distributed scheduling. The integrated energy system composed of a 14-node power grid, a 14-node heating network, and a 15-node gas network is taken as a simulation example, and the accuracy and practicability of the multi-objective programming method proposed are verified by comparing it with the existing multi-objective solutions and analyzing the Pareto front coordinates. Additionly, under the same calculation load distribution, the computational efficiency of the asynchronous coordination method is 16.6% higher than that of the synchronous method, which verifies the effectiveness of the proposed algorithm.

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    Multi-Agent Coordinated Dispatch of Power Grid and Pumped Hydro Storage with Embedded Market Game Model
    LOU Wei, HU Rong, YU Jinming, ZHANG Xipeng, FAN Feilong, LIU Songyuan
    Journal of Shanghai Jiao Tong University    2025, 59 (3): 365-375.   DOI: 10.16183/j.cnki.jsjtu.2023.354
    Abstract1685)   HTML4)    PDF(pc) (2651KB)(480)       Save

    In the context of large-scale energy storage stations, such as pumped storage, participating in both spot trading and grid scheduling, it is difficult for the grid to directly access the consumption of renewable energy in the spot market. In this regard, the influence of spot electricity trading on the pumped storage scheduling is considered and a multi-agent scheduling method with an embedded market game model is proposed. First, combined with the power spot market clearing model, with the objective of maximizing the benefits of the pumped storage power station in the spot market, a strategy for the pumped storage power station to participate in the spot trading of electric energy is developed. Then, combined with the two-part electricity price policy, the capacity allocation and power dispatching strategy of the grid operator about the pumped storage is formulated to minimize grid operating costs and the amount of renewable energy discarded in the entire grid. To formulate the proposed scheduling strategy, a bi-level optimization problem with an embedded game model is solved: the decision-making problem of the pumped storage power station participating in the electric energy spot market, and the optimization with the embedded marketing game model of capacity allocation and power scheduling strategy about pumped storage. The decision-making problem of pumped storage in the spot market follows a Stackelberg game model, which is integrated into the optimization problem of pumped storage capacity allocation and power scheduling strategy via the strong dual theory. The embedded bi-objective problem is solved by using the NSGA-II algorithm. Finally, based on the data from a pumped storage power station in East China, a simulation model is built to verify the effectiveness of the proposed method. The test results show that the proposed method can effectively coordinate the decision-making of direct grid dispatching and pumped storage participation in the electric energy spot market, enhancing the economic benefits of pumped storage, reducing the operating cost of the grid, and improving the consumption of renewable energy.

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