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Optimal Reconfiguration Method for Thermoelectric Power Array Based on Artificial Bee Colony Algorithm YANG Bo, HU Yuanweiji, GUO Zhengxun, SHU Hongchun, CAO Pulin, LI Zilin Journal of Shanghai Jiao Tong University    2024, 58 (1): 111-126.   DOI: 10.16183/j.cnki.jsjtu.2022.284 Abstract （2541）   HTML （10）    PDF（pc） （9997KB）（106）       Knowledge map    Save With the rapid development of new energy generation technology, the thermoelectric generation technology (TEG) can make good use of the waste heat generated in new energy generation. However, the change of temperature distribution will worsen the output characteristics and reduce the power generation efficiency of the TEG system. In this paper, a TEG array reconfiguration method based on the artificial bee colony (ABC) algorithm is proposed. In three different temperature distributions, ABC is used for dynamic reconfiguration of symmetric 9×9 and unsymmetric 10×15 TEG arrays. Three meta-heuristic algorithms, the genetic algorithm, the particle swarm optimization algorithm, and the bald eagle search are compared with the proposed method, and the temperature distribution of the TEG array reconfiguration by ABC is given. The results show that ABC can improve the output power of the TEG array, and the output power-voltage curves tend to show a single peak value. In addition, real-time hardware-in-the-loop (HIL) experiment based on the RTLAB platform is undertaken to verify the implementation feasibility. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Low-Carbon Operation Strategy of Integrated Energy System Based on User Classification ZHANG Chunyan, DOU Zhenlan, BAI Bingqing, WANG Lingling, JIANG Chuanwen, XIONG Zhan Journal of Shanghai Jiao Tong University    2024, 58 (1): 1-10.   DOI: 10.16183/j.cnki.jsjtu.2022.321 Abstract （2251）   HTML （32）    PDF（pc） （1783KB）（339）       Knowledge map    Save Integrated energy system (IES) is an important means to achieve the goal of “carbon peaking and carbon neutrality”. However, different types of users in the system have different energy consumption behaviors, which makes the coordinated optimization and low-carbon operation of the integrated energy system more difficult. In order to give full play to the subjective initiative of users, the user behavior of the integrated energy system is modelled based on user behavior analysis, and users are classified into aggressive and conservative types by convolutional neural network (CNN). Then, the decision model of integrated energy system operator is constructed to determine the supply mode of electric heating energy, and the corresponding energy package is designed for different types of users. Finally, the effectiveness of the above models and methods is analyzed based on actual data, and the value of user classification in low-carbon operation of integrated energy systems is verified. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Improved Magnetic Circuit-Motion Coupled Model and Fast Simulation of Direct-Acting Electromechanical Motion Device JIANG Peng, GUAN Zhenqun, ZHAO Guozhong, ZHANG Qun, QIN Zhiqiang Journal of Shanghai Jiao Tong University    2024, 58 (1): 102-110.   DOI: 10.16183/j.cnki.jsjtu.2022.243 Abstract （2109）   HTML （3）    PDF（pc） （3985KB）（227）       Knowledge map    Save The rapid simulation of the dynamic performance of electromechanical devices such as solenoid valves and relays is important for product development and design. A magnetic circuit model of the non-saturated direct-acting electromechanical motion device is improved, and then coupled with the motion equation of the mechanism to realize the rapid simulation of the electromechanical motion device. In contrast to the ideal magnetic resistance in the conventional magnetic circuit model, the non-saturated total magnetic resistance is expressed by a cubic polynomial of the movement displacement of mechanism. The four undetermined coefficients of the polynomial are calibrated by the simulation values of static magnetic force and inductance at the upper and lower motion limits. The improved magnetic circuit model can more accurately predict the changes of magnetic attraction force and inductance with the motion displacement. Furthermore, coupled with the motion equation of the electromechanical motion device, the improved model establishes an improved magnetic circuit-motion coupled model and realizes fast second-level simulation of an electromagnetic brake and valve in the Simulink system, which can greatly reduce the finite element simulation time while maintaining simulation accuracy. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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A Method for Carbon Emission Measurement and a Carbon Reduction Path of Urban Power Sector HU Zhuangli, LUO Yichu, CAI Hang Journal of Shanghai Jiao Tong University    2024, 58 (1): 82-90.   DOI: 10.16183/j.cnki.jsjtu.2022.222 Abstract （1986）   HTML （8）    PDF（pc） （1670KB）（280）       Knowledge map    Save To measure and reduce carbon emissions in the urban power sector, a method for measuring carbon emissions in the urban power sector and a carbon reduction path are proposed. First, a carbon emission measurement model for the urban power sector is established based on the data of local power generation and net inward power. Then, carbon reduction measures for the urban power sector are proposed from the generation side, grid side, load side and energy storage side. After that, an evaluation model for the effect of the carbon reduction measures is established. Finally, taking a typical city F in the Pearl River Delta as an example, the proposed carbon emission calculation model is used to calculate the carbon emissions of power sector of the city, and the effectiveness of carbon reduction in 2030 carbon peak scenario of the city is evaluated based on the carbon reduction measures. The results show that the proposed model can accurately measure the carbon emissions of the urban power sector, and by utilizing carbon reduction measures, carbon emissions of the city can be reduced by at least 10.6 million tons in 2030. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Robust Evaluation Method of Integrated Energy System Based on Variable Step Simulation and Improved Entropy Weight Method FAN Hong, HE Jie, TIAN Shuxin Journal of Shanghai Jiao Tong University    2024, 58 (1): 59-68.   DOI: 10.16183/j.cnki.jsjtu.2022.186 Abstract （1949）   HTML （6）    PDF（pc） （5076KB）（192）       Knowledge map    Save As an important manifestation of the energy Internet, the integrated energy system improves the energy utilization rate. However, it also brings more risks due to the high coupling and the large difference in the response speed between the various systems. From the perspective of system security, it becomes crucial to accurately identify the weak links in the system and evaluate the robustness of the system. Therefore, a robustness evaluation method combining variable step size simulation and improved entropy weight method is proposed in the complex network environment. First, the structure of the integrated energy system is introduced and the coupling links of the system are further explained. Then, the robustness indicators including network damage degree and connectivity factor are proposed, and a variable step according to the difference of the response time of different systems is adopted. Based on the simulation results, an improved entropy weight method is proposed, and a more objective evaluation method is constructed. Finally, the superiority of the evaluation method is verified by a case study. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Comprehensive Evaluation of Key Technologies in Power Internet of Things Based on Comprehensive Similarity of Cloud Model CHEN Lianfu, ZHONG Haiwang, TAN Zhenfei, RUAN Guangchun Journal of Shanghai Jiao Tong University    2024, 58 (1): 19-29.   DOI: 10.16183/j.cnki.jsjtu.2022.420 Abstract （1899）   HTML （15）    PDF（pc） （1954KB）（116）       Knowledge map    Save Currently, the comprehensive evaluation of the application of key technologies in the power Internet of Things (PIoT) has the characteristics of a single evaluation object, and the traditional evaluation methods are not applicable. In order to comprehensively evaluate the technology maturity and operational effectiveness of PIoT projects, a comprehensive evaluation index for key technologies in PIoT is established to comprehensively consider the different development stages. According to the characteristics of application scenario, an evaluation model based on the comprehensive similarity of cloud model is proposed. By reforming the technique for order preference by similarity to an ideal solution (TOPSIS) method, a decision matrix for a single evaluation object is constructed, and the shape-distance comprehensive similarity of the cloud model is used as a measure to characterize the relative closeness of the TOPSIS method, and the accurate evaluation of a single object is realized. Finally, the proposed method is applied to assess a PIoT demonstration project. The results show that the proposed comprehensive evaluation index and evaluation method can objectively and comprehensively evaluate the comprehensive application effect of each key technology in the construction and operation stages of PIoT. Table and Figures | Reference | Supplementary Material | Related Articles | Metrics | Comments（0）

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Reliability Index Calculation and Reserve Capacity Optimization Considering Multiple Uncertainties YE Lun, OUYANG Xu, YAO Jiangang, YANG Shengjie, YIN Jungang Journal of Shanghai Jiao Tong University    2024, 58 (1): 30-39.   DOI: 10.16183/j.cnki.jsjtu.2022.366 Abstract （1871）   HTML （7）    PDF（pc） （1413KB）（143）       Knowledge map    Save In power systems with a high proportion of renewable energy, to achieve coordinated optimal scheduling of source and load considering multiple uncertainties is an important issue in power system operation. Therefore, a probabilistic spinning reserve optimization model based on multiple scenarios is constructed. Multiple uncertain factors are considered in the model, such as wind power and solar power forecast errors, load forecast error and unscheduled generator outage. Renewable energy curtailment and load shedding are used as special reserve resources in the day-ahead security-constrained unit commitment (SCUC) to improve the economic operation efficiency. The calculations of reliability indexes, expected energy not served and expected energy curtailment, are simplified, and the inequality constraints related to these two indexes are reduced, which improves the computational performance of the model. The model optimizes the total expected cost considering multiple uncertainties. Case studies based on the IEEE-RTS demonstrate the effectiveness of the proposed model. The numerical results show that the improved calculation method of reliability indexes can effectively reduce the solution time of the SCUC model. The reserve optimization model can realize the dynamic allocation of the spinning reserve capacity of the system and improve economic operation of the system. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Optimization Design of New Bionic Propeller WU Chunxiao, LU Yu, LIU Shewen, GU Zhuhao, SHAO Siyu, SHAO Wu, LI Chuang Journal of Shanghai Jiao Tong University    2023, 57 (11): 1421-1431.   DOI: 10.16183/j.cnki.jsjtu.2022.174 Abstract （1779）   HTML （27）    PDF（pc） （10709KB）（375）       Knowledge map    Save A novel method for optimal design of hydrodynamic performance of bionic propeller with a deformable leading edge is proposed. Based on the bionics principle and method of parameterized modeling, the fore-fin concave-convex structure of humpback whales is applied to the propeller leading edge, the leading edge in the propeller to meet flow region according to the exponential decay curve and the standard sine curve smooth leading edge for similar humpback fins protuberant structure of concave and convex deformation, and the leading edge of concave and convex bionic propeller. The hydrodynamic performance, the cavitation performance, and the noise performance of the exponential decay bionic propeller and the sinusoidal function bionic propeller were simulated respectively. The propeller with a better performance is selected, and the simulation based design (SBD) technology is introduced into the optimization design of the new bionic propeller. The parameters controlling the shape of the exponential attenuation curve of the guide edge deformation are taken as optimization design variables, the torque of the parent propeller is taken as the constraint condition, the open water efficiency is selected as the objective function, and the optimization algorithm of Sobol and T-Search is adopted. A bionic propeller optimization system based on the exponential decay curve is constructed. The results show that the application of the concave and convex structure of the humpback whale fore-fin to the guide edge of the propeller improves the cavitation performance and noise performance of the propeller, but the improvement of the open water performance of the propeller is not particularly significant. It is verified that the hydrodynamic performance optimization design method of the bionic propeller established in this paper is effective and reliable, which provides a certain theoretical basis and technical guidance for the performance numerical calculation and configuration optimization design of the bionic propeller. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Refined Simulation of Near-Surface Wind Field of Atmospheric Boundary Layer Based on WRF-LES Model LIU Dalin, TAO Tao, CAO Yong, ZHOU Dai, HAN Zhaolong Journal of Shanghai Jiao Tong University    2024, 58 (2): 220-231.   DOI: 10.16183/j.cnki.jsjtu.2022.415 Abstract （1741）   HTML （26）    PDF（pc） （9950KB）（427）       Knowledge map    Save Extreme meteorological disasters such as typhoons pose a serious threat to the safety of engineering structures. Therefore, the refined simulation on the near-surface atmospheric boundary layer (ABL) is valuable for civil engineering. Large-eddy simulation (LES) implemented in the weather research and forecating (WRF) model has the advantages of multiple options of numerical schemes and high accuracy. It is generally suitable for the refined simulation of the near-surface wind field, although the performance of simulation results is closely related to the numerical methods. This paper assesses the impacts of vital parameters regarding subfilter-scale (SFS) stress models, mesh size, and spatial difference schemes within WRF-LES to simulate the ideal ABL in order to figure out appropriate numerical schemes for the refined simulation of the near-surface wind field. The wind field characteristics are addressed and analyzed such as mean wind speed profile, turbulence intensity profile, and power of spectrum. Comparisons of simulation results among different SFS stress models indicate that the nonlinear backscatter and anisotropy one (NBA1) SFS stress model can effectively improve the accuracy of simulation in the near-surface wind profiles. Investigations of mesh resolution effects indicate that the nonuniformly refined vertical grid near the surface agrees much better with the expected profiles and reduces the expenditure of computational resources. Furthermore, the results show that the even-order spatial difference schemes produce more small-scale turbulent structures than the odd-order difference schemes. The numerical methods of WRF-LES proposed can provide a technical reference for refined simulation of the near-surface wind field and typhoon boundary layer. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Stepwise Inertial Intelligent Control of Wind Power for Frequency Regulation Based on Stacked Denoising Autoencoder and Deep Neural Network WANG Yalun, ZHOU Tao, CHEN Zhong, WANG Yi, QUAN Hao Journal of Shanghai Jiao Tong University    2023, 57 (11): 1477-1491.   DOI: 10.16183/j.cnki.jsjtu.2022.157 Abstract （1684）   HTML （16）    PDF（pc） （10551KB）（198）       Knowledge map    Save Stepwise inertial control (SIC) provides a step-increase of power after load fluctuation, which can effectively prevent system frequency decline and ensure the safety of grid frequency. However, in the power recovery stage, secondary frequency drop (SFD) is easy to occur. Therefore, it is necessary to optimize SIC to obtain a better frequency regulation effect. The traditional method has the disadvantages of high calculation dimension and long consuming time, which is difficult to meet the requirements of providing the optimal control effect in different scenarios. In order to realize the optimal stepwise inertial fast control of wind power frequency regulation in load disturbance events, this paper introduces the deep learning algorithm and proposes a stepwise inertial intelligent control of wind power for frequency regulation based on stacked denoising autoencoder(SDAE) and deep neural network(DNN). First, sparrow search algorithm (SSA) is used to obtain the optimal parameters, and SDAE is used to extract the data features efficiently. Then, DNN is used to learn the data features, and the accelerated adaptive moment estimation is introduced to optimize the network parameters to improve the global optimal parameters of the network. Finally, the stepwise inertial online control of wind power frequency regulation after disturbance event is realized according to SDAE-DNN. The simulation analysis is conducted for a single wind turbine and a wind farm in the IEEE 30-bus test system. Compared with the results obtained by the traditional method, shallow BP neural network and original DNN network, it is found that the proposed network structure has a better prediction accuracy and generalization ability, and the proposed method can achieve a great effect of stepwise inertia frequency regulation. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Wake Field Characteristics of Non-Ducted and Ducted Propellers in Large-Angle Oblique Flow ZHANG Qin, WANG Xinyu, WANG Zhicheng, WANG Tianyuan Journal of Shanghai Jiao Tong University    2023, 57 (11): 1432-1441.   DOI: 10.16183/j.cnki.jsjtu.2022.159 Abstract （1673）   HTML （11）    PDF（pc） （18498KB）（183）       Knowledge map    Save In order to explore the wake characteristics of non-ducted and ducted propellers in oblique inflow with a large drift angle, based on the delayed detached eddy simulation, a numerical simulation of non-ducted and ducted propellers in oblique inflow is conducted with an advance coefficient (J=0.4) and a large drift angle (β=45°, 60°). It is found that the deflection degree of the non-ducted propeller wake is higher than that of the ducted propeller. However, the overall distribution area of the wake vortex behind the ducted propeller is kinked. The wake field in the oblique flow shows its complexity, and the evolution process of vortices on the windward side differs from that on the leeward side. The above characteristic of the non-ducted propeller is more prominent. At the same time, the leading edge of the nozzle on the leeward side will produce local shedding vortices and transmit to the downstream due to flow separation. Part of the kinetic energy of the ducted propeller is converted into the nozzle thrust, which makes the turbulence kinetic energy of the wake lower than that of the non-ducted propeller. This phenomenon is more evident with the increase in the drift angle. Compared with the non-ducted propeller, the ducted propeller can maintain a better handling stability in large-angle oblique flow. This paper analyzes the influence of large-angle oblique inflow on the non-ducted and ducted propellers from the perspective of wake field characteristics and explores the theoretical basis for the ducted propeller to maintain a better handling stability in oblique flow. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Analysis of Fluid-Structure Coupling Energy Transfer Characteristics Slender Structure with Variable Cross-Section at Low Reynolds Number DENG Xiubing, YU Yuemin, PANG Xiyuan Journal of Shanghai Jiao Tong University    2023, 57 (11): 1400-1409.   DOI: 10.16183/j.cnki.jsjtu.2022.133 Abstract （1665）   HTML （11）    PDF（pc） （18587KB）（161）       Knowledge map    Save The wavy deformed cross-section cylindrical structure has excellent properties of drag reduction in fluid flow, but the flow-induced vibration characteristics of flexible structure with such variable cross-section are still unclear. In this paper, based on the high-performance spectral element method, a fluid-structure coupled mechanistic model and a numerical algorithm for slender structures are established. The wake characteristics, structural dynamic responses, energy transfers, and spanwise variations of vortex shedding frequencies are discussed. The numerical simulation results show that slender structure with the wavy-deformed cross-section can greatly suppress the vortex-induced vibration response at an appropriate cross-section disturbance wave height, and the special vortex structure formed on both sides of the wavy-shaped slender structure can stabilize the flow around the shear layer and elongate the vortex formation length, thereby reducing the fluid-structure coupling effect between the wake structure and the slender structure, and suppressing the vortex-induced vibration response. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Strategy of Wind-Storage Combined System Participating in Power System Secondary Frequency Regulation Based on Model Predictive Control LIU Chuanbin, JIAO Wenshu, WU Qiuwei, CHEN Jian, ZHOU Qian Journal of Shanghai Jiao Tong University    2024, 58 (1): 91-101.   DOI: 10.16183/j.cnki.jsjtu.2022.217 Abstract （1647）   HTML （5）    PDF（pc） （2262KB）（207）       Knowledge map    Save With the increasing penetration of wind power in power grids, it is necessary for wind storage joint farms to participate in power grid frequency modulation to maintain frequency stability of the power grid. By analyzing the mechanical characteristics of the wind turbine and the operation characteristics of the energy storage system, this paper determines the adjustability of the wind turbine power output in the pitch angle load shedding operation mode, and proposes a control strategy for the wind farm with an energy storage system to participate in the secondary frequency regulation of the power grid based on model predictive control (MPC). It establishes a prediction model for pitch angle control of the wind farm and an electrochemical energy storage system, optimizing the active power output of the wind turbine and the energy storage system, and better reducing the wind energy loss based on frequency regulation. The pitch angle control is further corrected based on the difference between the active power command value of the superior system and the actual power output of the wind turbine, so that the wind turbine can better track the power command value of the superior system during secondary frequency regulation, quickly respond to the frequency changes, reduce the dynamic frequency deviation, avoid load rejection due to too low frequency drop, and complete the task of secondary frequency regulation. The simulation results show that under the control strategy proposed in this paper, the controllable secondary frequency regulation ability of the wind turbine and the characteristics of fast response and accurate tracking of the energy storage system are comprehensively considered, the active power command issued by the superior system is better tracked, and the task of the wind farm including the energy storage system participating in the secondary frequency regulation is realized. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Optimization of Wind Turbine Vortex Generator Based on Back Propagation Neural Network XIA Yunsong, TAN Jianfeng, HAN Shui, GAO Jin’e Journal of Shanghai Jiao Tong University    2023, 57 (11): 1492-1500.   DOI: 10.16183/j.cnki.jsjtu.2022.169 Abstract （1612）   HTML （12）    PDF（pc） （9995KB）（179）       Knowledge map    Save The optimal Latin hypercube experimental design method is used to refine the vortex generator parameters, determine the test scheme, simulate and calculate the thrust and torque of the wind turbine, and obtain the experimental data. Based on the back propagation (BP) neural network, the aerodynamic performance model of the wind turbine vortex generator optimized by genetic algorithm is constructed. The reliability of the aerodynamic performance model is verified by calculating the error and root mean square of the predicted and simulated values of the aerodynamic performance model. Coupling the fish swarm algorithm and the aerodynamic performance model of the wind turbine vortex generator, an optimization method of the wind turbine vortex generator is established, and the height, length, and installation angle of the vortex generator are solved iteratively to realize the optimization of the vortex generator. The results show that compared with the original vortex generator scheme, the flow separation of the wind turbine blade section optimized by the vortex generator is effectively restrained and delayed, the surface fluid separation phenomenon is improved, the power of the wind turbine is increased by 1.711%, and the thrust of the wind turbine is decreased by 0.875%. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Experimental Investigation of Dynamic Response of Pile-Supported Wharf in Liquefiable Ground Under Wave Action BI Jianwei, SU Lei, XIE Libo, ZHANG Yu, LING Xianzhang Journal of Shanghai Jiao Tong University    2023, 57 (11): 1442-1454.   DOI: 10.16183/j.cnki.jsjtu.2022.163 Abstract （1607）   HTML （9）    PDF（pc） （8259KB）（246）       Knowledge map    Save Pile-supported wharf (PSW) is widely used in the deep-water port engineering construction, most of which are located in liquefiable ground. The effect of wave action on the working performance of PSW in liquefiable ground cannot be ignored, but few studies have been reported. This study performs the wave flume test of PSW in liquefiable ground considering the soil-structure-wave interaction. This test really reproduces the operating condition of PSW, and explores the internal response difference of wharf structure under wave. The influence of wave height on dynamic response of the PSW system is discussed systematically. The result shows that the acceleration and displacement of the PSW deck gradually increase first and finally remain relatively stable with the increase of wave action. The hydrodynamic pressure and deformation of each pile in pile group are obviously different, and the response variation is related to the pile position. The pore pressure of the soil layer in the free field and around the pile decreases with the increase of depth, and the existence of the pile group can reduce the pore pressure in the soil layer around the pile, and increase the acceleration of the soil layer. The effect of wave height on the soil layer decreases with the increase of depth. The above results can provide reference for the similar PSW test under wave and the support for the design and wave protection of PSW. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Robust Optimization of Power Grid Investment Decision-Making Considering Regional Development Stage Uncertainties HUANG Wandi, ZHANG Shenxi, CHENG Haozhong, CHEN Dan, ZHAI Xiaomeng, WU Shuang Journal of Shanghai Jiao Tong University    2023, 57 (11): 1455-1464.   DOI: 10.16183/j.cnki.jsjtu.2022.053 Abstract （1588）   HTML （15）    PDF（pc） （2782KB）（94）       Knowledge map    Save Aimed at the problem of uncertainties in the regional development stage and the difficulties in quantifying regional investment demand in different development stages, a robust optimization method for power grid investment decision-making considering regional development stage uncertainties is proposed to promise the matching degree between power grid investment decisions and development needs, and to improve the ability of decision-making results to deal with portfolio risks and uncertainties in regional development stage. First, investment risk constraints are constructed based on the modern portfolio theory. Then, a box uncertainty set is used to characterize uncertainties in regional development stage, and a robust optimization model for power grid investment decision-making considering uncertainties in development stage is established. In the optimization model, the outer minimization problem is used to solve the uncertain variables in regional development stage in the worst scenario, while inner maximization problem is used to obtain the decision-making plan that can maximize investment return in the worst scenario. Furthermore, according to the strong duality theory, the double-layer optimization model is transformed into a single-layer model that can be solved directly, and the big-M method is used to solve the model proposed. Finally, an actual example of 13 cities in an eastern coastal province verifies the applicability and effectiveness of the power grid investment decision-making model. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Distribution Network Fault Diagnosis Technology Based on Multi-Source Data Fusion ZHANG Chunmei, XU Xingque, LIU Silin Journal of Shanghai Jiao Tong University    2024, 58 (5): 739-746.   DOI: 10.16183/j.cnki.jsjtu.2022.317 Abstract （1531）   HTML （7）    PDF（pc） （1475KB）（183）       Knowledge map    Save How to make full use of existing information to improve the accuracy of fault diagnosis in distribution networks, and provide accurate research and judgement for emergency repair of distribution networks, is an urgent problem to be solved. To address the problem of the single source of fault diagnosis information in existing distribution networks, a fault diagnosis model of distribution network is proposed which integrates the medium and low voltage information of the distribution networks and the outgoing current information of the substation. The model first applies the existing overcurrent diagnosis method to the problem of large-scale distribution network, and adopts hierarchical reduction of the size of the distribution networks to improve the location speed of fault section. Then, in view of the accuracy of overcurrent alarm information, an auxiliary fault judgment method for distribution networks based on switch relay protection sequence of events (SOE) data and substation outgoing load sag data is proposed. Finally, the steps for fault diagnosis in distribution networks of multi-directional information and data fusion in practical engineering are summarized, which provides reference for fault diagnosis of dispatchers. Engineering practice proves that the method proposed in this paper can effectively diagnose faults and is very adaptable to large-scale distribution networks. The auxiliary diagnosis model combining switch operation SOE and telemetering voltage information can compensate for the accuracy requirements of the overcurrent diagnosis model for remote communication information, which is complementary to each other and has a good engineering value. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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An Improved NLC and Capacitor Voltage Control Method for Medium-/Low-Voltage MMCs ZHANG Wei, HAN Junfei, ZHONG Ming, WANG Yuqiang Journal of Shanghai Jiao Tong University    2023, 57 (11): 1465-1476.   DOI: 10.16183/j.cnki.jsjtu.2022.172 Abstract （1521）   HTML （12）    PDF（pc） （2806KB）（155）       Knowledge map    Save The modular multilevel converter (MMC) suffers from low output level and high harmonic distortion in medium-/low-voltage applications such as direct current (DC) distribution networks. In addition, the capacitor voltage of MMC is coupled with DC bus voltage in the traditional modulation method, leading to large fluctuations of capacitor voltages and deviation from the rated value under DC bus voltage margin. In order to solve the problems above, this paper proposes an improved nearest level control method, which can increase the output level of medium-/low-voltage MMCs by introducing a step wave correction. Based on the proposed modulation method, a capacitor voltage feedback control is thus proposed to limit the range of capacitor voltage fluctuations and improve equipment safety. The effectiveness of the proposed method is verified by MATLAB/Simulink simulation and real-time digital simulation system hardware-in-the-loop test. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Source-Load Matching Analysis and Optimal Planning of Wind-Solar-Thermal Coupled System Considering Renewable Energy Ramps XIA Qinqin, LUO Yongjie, WANG Rongmao, ZOU Yao, LUO Huanhuan, LI Jincan, ZHOU Niancheng, WANG Qianggang Journal of Shanghai Jiao Tong University    2024, 58 (1): 69-81.   DOI: 10.16183/j.cnki.jsjtu.2022.260 Abstract （1405）   HTML （8）    PDF（pc） （3526KB）（114）       Knowledge map    Save Wind, photovoltaic, and thermal power generation can form a coupled system through the same grid-connected point, which is a high coordination and low-carbon approach of renewable energy and flexible regulating power source at generation side in northern China. By considering renewable energy ramps and source-load matching analysis, this paper studies the optimal capacity planning of a wind-solar-thermal coupled system to provide reference for coupled system planning. First, the operation model and the uncertainty method of coupled system are briefly described. Then, considering the wind-solar complementary, ramp events, and critical load characteristics, relevant indices are selected and proposed for source-load matching evaluation. After that, considering the constraints of source-load characteristics, matching, and cost, an optimal capacity planning model of wind-solar-thermal coupled system is established. Finally, based on the actual data in Liaoning Province, a case study is conducted to acquire the optimal capacity of the wind and solar generation in the area, and the interaction between the source-load relevant indices and the planning results is analyzed, which provides reference and suggestion for the optimal capacity planning of renewable energy generation. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Simulation Study of Reentry Dynamics of a Deep-Water Drilling Riser System Based on Model Predictive Control ZHANG Chenyu, MENG Shuai Journal of Shanghai Jiao Tong University    2023, 57 (11): 1389-1399.   DOI: 10.16183/j.cnki.jsjtu.2022.235 Abstract （1369）   HTML （25）    PDF（pc） （2622KB）（217）       Knowledge map    Save A marine drilling riser at normal operation condition is required to disconnect the lower marine riser package (LMRP) and blow-out preventer (BOP) in case of severe weather. When the weather gets fine, it must reconnect the LMRP and the BOP. This process is called riser reentry. Marine drilling operations have been driven into extreme deep-waters characterized by severe weather which inevitably leads to a much higher incidence of disconnection. In addition, it requires to accomplish the reentry in a fast way owing to the capricious ocean environment. This study tries to develop a novel reentry control system based on model predictive control (MPC). First, the transverse governing equation of the hanging-off riser system with an end-mass is established based on the modified Hamilton’s principle. The optimization function and constraints in MPC are designed by use of the riser prediction model and the target location. A nonlinear disturbance observer is established for compensation of the model uncertainties and ocean environment disturbances. Finally, simulations are conducted after introducing the dynamic position system (DPS). The riser dynamics employing MPC are compared with that when adopting proportional-integral-derivative (PID) controller. It has found that the drilling riser system based on MPC has a higher response speed, which can complete the reentry process in a faster and more stable manner. It can handle the hydrodynamic force model uncertainties well and has a good robustness for current velocity disturbances. As the flexibility of the riser system is notably enhanced with the significant increase of aspect ratio, the higher-order mode of the flexible hanging-off riser can be triggered in the fast reentry process subjected to the excitations of the mother vessel and ocean environment. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Fast Stability of New Power System Based on a PMU Gradient Dynamic Deviation Method YU Miao, HU Jingxuan, ZHANG Shouzhi, WEI Jingjing, SUN Jianqun, WU Yixiao Journal of Shanghai Jiao Tong University    2024, 58 (1): 40-49.   DOI: 10.16183/j.cnki.jsjtu.2022.370 Abstract （1365）   HTML （3）    PDF（pc） （2171KB）（130）       Knowledge map    Save The high proportion of renewable energy and power electronic equipment is emerging as a significant trend and key characteristic of the power system development driven by the dual promotion of the energy transformation and scientific technological advancement. Major modifications have been made to the dynamic behavior of the new power system. The traditional small signal stability analysis approach is difficult to apply, and there are still urgent issues to be resolved for the quick change of operating conditions. In this paper, a Lyapunov direct analysis method of gradient dynamic deviation based on phasor measurement unit (PMU) data is proposed to analyze the small signal stability of the new power system. First, the PMU data matrix is used to reduce the dimension to obtain the low dimension matrix, which is substituted into the power system matrix model with a doubly-fed induction generator (DFIG). The diagonal matrix is obtained by solving the Lyapunov equation, and the positive definiteness of the matrix is determined to judge the system stability. Then, the dynamic deviation of corresponding state variable is calculated by solving the obtained diagonal matrix. The gradient descent method is applied to the corresponding state variable curve to iterate the extreme point value of curve. The time-weighted dynamic deviation of the whole oscillation process is calculated by time weighting, which provides guidance for the subsequent configuration position of damping stability controller, i.e., power system stabilizer (PSS). The method can improve the small interference stability of the system. The effectiveness of the fast stability analysis of the new power system is verified by simulations of the new England 10-machine 39-bus system with DFIG. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Fully Distributed Economic Dispatch of Combined Heat and Power System Considering Individual Selfishness MI Yang, WU Jiwei, TIAN Shuxin, MA Siyuan, WANG Yufei Journal of Shanghai Jiao Tong University    2024, 58 (1): 50-58.   DOI: 10.16183/j.cnki.jsjtu.2022.495 Abstract （1338）   HTML （4）    PDF（pc） （1726KB）（100）       Knowledge map    Save In response to the defects of the traditional centralized economic dispatching strategy which needs to obtain global information and cannot adapt to the flexible topology of the system, and considering the coexistence of energy in the form of electricity and heat, a completely distributed cogeneration economic dispatching strategy based on the consistency algorithm is proposed. The incremental cost of electricity price and heat price of each unit in the cogeneration system is taken as the consistent variable to conduct the iterative calculation until the incremental cost converges to achieve the economic optimum of the system. In addition, the case of individual unit transmitting to neighboring units with deviating incremental cost values in order to enhance their own interests is also analyzed, and an incremental cost compensation term is designed to eliminate the impact of this selfish behavior. The simulation results indicate that the proposed strategy is effective and viable in the solution of the cogeneration economic dispatching problems. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Key Technologies and Applications of Shared Energy Storage SONG Meng, LIN Gujing, MENG Jing, GAO Ciwei, CHEN Tao, XIA Shiwei, BAN Mingfei Journal of Shanghai Jiao Tong University    2024, 58 (5): 585-599.   DOI: 10.16183/j.cnki.jsjtu.2022.360 Abstract （1333）   HTML （25）    PDF（pc） （4173KB）（376）       Knowledge map    Save Under the goal of “carbon peaking and carbon neutrality”, the penetration rate of renewable energy continues to rise, whose volatility, intermittency, and uncertainty pose significant challenges to the safe and stable operation of the power system. As a typical application of the sharing economy in the field of energy storage, shared energy storage (SES) can maximize the utilization of resources by separating the “ownership” and “usage” of energy storage resources, which provides a new solution to the problem of imbalance between supply and demand caused by the large-scale integration of renewable energy into the grid, and has broad development prospects. The business model of SES is explored based on value positioning, cost modeling, and profitability strategies, and a detailed summary of SES trading varieties, operational structure, and engineering applications is discussed. Finally, the future trend of shared energy storage is discussed and envisioned. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Coordinated Active Power-Frequency Control Based on Safe Deep Reinforcement Learning ZHOU Yi, ZHOU Liangcai, SHI Di, ZHAO Xiaoying, SHAN Xin Journal of Shanghai Jiao Tong University    2024, 58 (5): 682-692.   DOI: 10.16183/j.cnki.jsjtu.2022.358 Abstract （1211）   HTML （4）    PDF（pc） （2823KB）（283）       Knowledge map    Save The continuous increase in renewables penetration poses a severe challenge to the frequency control of interconnected power grid. Since the conventional automatic generation control (AGC) strategy does not consider the power flow constraints of the network, the traditional approach is to make tentative generator power adjustments based on expert knowledge and experience, which is time consuming. The optimal power flow-based AGC optimization model has a long solution time and convergence issues due to its non-convexity and large size. Deep reinforcement learning has the advantage of “offline training and online end-to-end strategy formation”, which yet cannot ensure the security of artificial intelligence (AI) in power grid applications. A coordinated optimal control method is proposed for active power and frequency control based on safe deep reinforcement learning. First, the method models the frequency control problem as a constrained Markov decision process, and an agent is designed by considering various safety constraints. Then, the agent is trained using the example of East China Power Grid through continuous interactions with the grid. Finally, the effect of the agent and the conventional AGC strategy is compared. The results show that the proposed approach can quickly generate control strategies under various operating conditions, and can assist dispatchers to make decisions online. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Low Carbon Economic Operation of Hydrogen-Enriched Compressed Natural Gas Integrated Energy System Considering Step Carbon Trading Mechanism FAN Hong, YANG Zhongquan, XIA Shiwei Journal of Shanghai Jiao Tong University    2024, 58 (5): 624-635.   DOI: 10.16183/j.cnki.jsjtu.2022.377 Abstract （1150）   HTML （8）    PDF（pc） （3488KB）（293）       Knowledge map    Save Hydrogen energy plays a crucial role in meeting the “carbon peaking and carbon neutrality” goals, and the carbon capture technology is a vital technique for emission reduction in the energy industry. Blending hydrogen with natural gas to produce hydrogen-enriched compressed natural gas (HCNG) facilitates the transportation and utilization of hydrogen energy. At the same time, applying the carbon capture technology to retrofit thermal power units can effectively promote the large-scale consumption of renewable energy and reduce carbon emissions. For this purpose, a detailed model of hydrogen production equipment and fuel cells is established. Then, aimed at the problem of system carbon emissions, a carbon emission and output model of carbon capture thermal power units and a mathematical model of hydrogen doped cogeneration are established, and a stepped carbon trading mechanism is introduced to control carbon emissions. Based on this, an optimal scheduling model for hydrogen-enriched compressed natural gas integrated energy system is established with the goal of minimizing the sum of energy purchase cost, carbon emission cost, wind abandonment cost, and carbon sequestration cost, and taking into account the constraints such as hydrogen blending ratio and carbon capture in the pipeline network, which is solved by using the particle swarm optimization algorithm in conjunction with CPLEX. The analysis of the models built in different scenarios verifies the advantages of the proposed scheduling model in low-carbon economy. Table and Figures | Reference | Supplementary Material | Related Articles | Metrics | Comments（0）

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Operation Optimization for Integrated System of Wind-PV-Thermal-Storage with CC-P2G CHENG Renli, LI Jiangnan, ZHOU Baorong, ZHAO Wenmeng, LIU Ya Journal of Shanghai Jiao Tong University    2024, 58 (5): 709-718.   DOI: 10.16183/j.cnki.jsjtu.2022.270 Abstract （1142）   HTML （2）    PDF（pc） （3049KB）（170）       Knowledge map    Save The carbon capture (CC) and power to gas (P2G) devices can utilize the abundant new energy of the system to capture the carbon emissions generated by thermal power combustion and generate usable gas, forming a carbon resource recycling chain. In order to reduce the carbon emission of the power system, promote new energy absorption, and improve the operation flexibility of the power system, an integrated system architecture including CC and P2G is proposed and its optimization operation model is designed. The operational characteristics of power flow and carbon flow in this architecture are mainly discussed. Considering the benefits of carbon emission trading under the quota system, an optimized operation model for the integrated system of wind-PV-thermal-storage with CC-P2G is proposed, aimed at maximizing the comprehensive benefits of the integrated system and taking the operation characteristics of various equipment as constraint conditions. Furthermore, the effectiveness of the CC-P2G system in improving new energy consumption capacity and system operation efficiency is verified. The results show that the participation of the CC-P2G system needs to be effectively coordinated with market mechanisms such as carbon emissions quota trading, which can reduce the overall carbon emissions of the system and improve its operation efficiency. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Green Energy Trading in Distribution Network Considering Credit Value WU Qing, JIA Qiangang, YAN Zheng, ZHONG Zhun, GUO Song, LI Zhiyong Journal of Shanghai Jiao Tong University    2024, 58 (1): 11-18.   DOI: 10.16183/j.cnki.jsjtu.2022.130 Abstract （1130）   HTML （16）    PDF（pc） （1504KB）（226）       Knowledge map    Save Developing distributed renewable energy is vital to energy system transformation, while organizing market trading will promote the production and consumption of distributed renewable energy. However, the uncertainty of renewable energy output causes deviations during market delivery, which threats the security of distribution system operation. It is still difficult for existing market-based trading mechanisms to motivate market players to reduce the deviations. Therefore, this paper gives guidance to the honest delivery behaviors of distributed green energy producers by quantifying credit costs. Considering the strategic bidding behaviors of distributed green energy producers, it establishes a market model taking the credit costs into account. Then, it proposed an iterative algorithm based on the optimal response theory to calculate the Nash equilibria of the green energy market. The results of the case study show that the market mechanism proposed can give guidance to the integrity behavior of green energy producers in an incentive-compatible way, reducing the delivery deviation while improving social welfare. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Fast Fault Location Technology for Distribution Network Based on Quantum Ant Colony Algorithm BI Zhongqin, YU Xiaowan, WANG Baonan, HUANG Wentao, ZHANG Dan, DONG Zhen Journal of Shanghai Jiao Tong University    2024, 58 (5): 693-708.   DOI: 10.16183/j.cnki.jsjtu.2023.004 Abstract （1122）   HTML （9）    PDF（pc） （2880KB）（253）       Knowledge map    Save Integration of distributed generations into distribution networks has become one of the important features of new power systems. The integration of distributed generation and the uncertainty of power generation make the power flow in distribution networks complex and variable, which poses higher technical requirements for rapid fault location in distribution networks. However, existing intelligent optimization algorithms may encounter problems such as slow convergence speed and susceptibility to local optimization when solving the problem of fault section location in distribution networks. To address these challenges and problems, a rapid fault section location technology based on quantum ant colony algorithm (QACA) is proposed. First, a location mathematical model is constructed based on the state approximation idea and the minimum fault set theory. Then, an information self-correction method is proposed for the missing information uploaded by feeder terminal unit, and a hierarchical location model is proposed to shorten the location time. Afterwards, three improvement techniques are proposed to improve the QACA. The update mechanism of the quantum rotary gate is improved, the rotation angle is dynamically adjusted in the form of function control, and the elite strategy is introduced to accelerate the convergence speed of the algorithm. Finally, after the key parameters are determined, the effectiveness of the improved technique, the information self-correction method, and the hierarchical positioning model is verified. A comparison with 7 different algorithms indicates that the improved QACA can effectively locate the fault section, and has a fast convergence speed, great accuracy, and fault tolerance. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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A Review of Numerical Studies of Wave Impacts on Marine Structures ZHANG Nianfan, XIAO Longfei, CHEN Gang Journal of Shanghai Jiao Tong University    2024, 58 (2): 127-140.   DOI: 10.16183/j.cnki.jsjtu.2022.500 Abstract （1116）   HTML （24）    PDF（pc） （4659KB）（185）       Knowledge map    Save Wave impact is a strongly nonlinear interaction between waves and structures, and its load usually has the characteristics of a large peak value and short duration. In recent years, the extreme environment has frequently led to severe wave impacts on marine structures, resulting in loss of life and property, thus making the issue of wave impact become a great concern. For the complicated impact process, the theoretical analysis and model experiments can only provide simplified analytical solution and limited information on the slamming flow field. Therefore, numerical simulation has gradually become an effective means to study the issue of wave impact. Scholars at home and abroad have conducted a large number of numerical investigations on the load characteristics of wave impact, impact process, and its influencing factors on marine structures, gaining numerous important research conclusions. In this paper, the current progress, existing methods, and important conclusions of the numerical study of wave impact on marine structures are reviewed, which can provide useful references for further research on the numerical simulation of wave impact. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Low Carbon Economy Optimization of Integrated Energy System Considering Electric Vehicle Charging Mode and Multi-Energy Coupling ZHANG Cheng, KUANG Yu, CHEN Wenxing, ZHENG Yang Journal of Shanghai Jiao Tong University    2024, 58 (5): 669-681.   DOI: 10.16183/j.cnki.jsjtu.2022.364 Abstract （1112）   HTML （6）    PDF（pc） （4514KB）（181）       Knowledge map    Save In order to enable a multi-energy coupling integrated energy system (IES) to meet the needs of load diversity in low-carbon economic operation, a bi-level optimal configuration method for low-carbon economic operation of multi-energy coupling IES in different charging modes of electric vehicles (EVs) is proposed. First, an IES including cold-thermal-electric-gas coupling is established. Then, in the day-to-day operation stage, factors such as hierarchical carbon trading mechanism and different charging modes of EVs are considered to achieve the lowest daily scheduling cost. In the configuration planning stage, based on the daily operation cost, the equipment capacity is configured with the lowest equipment investment cost and annual operation cost. Finally, Cplex is used to solve the above two-stage objective functions and obtain the optimal configuration scheme and scheduling results through mutual iteration. The results show that the charging method considering the remaining charge of EVs and carbon trading mechanism can significantly reduce carbon emissions and operating costs of the system. The proposed configuration approach can well realize low-carbon economic operation of the multi-energy coupling IES. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Numerical Analysis of Hydrodynamic Performance of Propeller in Waves ZHANG Geng, YAO Jianxi Journal of Shanghai Jiao Tong University    2024, 58 (2): 175-187.   DOI: 10.16183/j.cnki.jsjtu.2022.247 Abstract （1105）   HTML （11）    PDF（pc） （14901KB）（250）       Knowledge map    Save The hydrodynamic performance of propeller is mostly studied in calm water, but the propeller working behind ship is often affected by waves. According to the literature, there is relatively little research on hydrodynamic performance of propeller in waves at present. In view of this, RANS solver based on OpenFOAM is used to calculate and analyze the influence of waves on the thrust and torque of propeller. The results show that time history curves of thrust and torque oscillate under the influence of waves. The disturbance of free surface and the oscillation amplitude of time history curves increase with the decrease of immersion depth and advance coefficient. Compared with the calm water condition, the average thrust and torque of propeller in waves are reduced when the immersion depth and advance coefficient are the same. The computational results are in good agreement with the experimental data. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Dynamic Optimization of Carbon Reduction Pathways in Coastal Metropolises Considering Hidden Influence of Decarbonization on Energy Demand XIAO Yinjing, ZHANG Di, WEI Juan, GE Rui, CHEN Dawei, YANG Guixing, YE Zhiliang Journal of Shanghai Jiao Tong University    2024, 58 (5): 600-609.   DOI: 10.16183/j.cnki.jsjtu.2022.437 Abstract （1095）   HTML （13）    PDF（pc） （1733KB）（167）       Knowledge map    Save Setting a reasonable carbon reduction plan in coastal metropolises is the key part to reach the global carbon target. Carbon reduction will change urban climate and influence energy demand, both of which affect the optimization results of carbon reduction pathways. Current generation expansion optimization models consider direct abatement contribution and solve most problems of planning for long-term carbon emission reduction in energy systems. However, the construction of new type power systems also indirectly impacts carbon emissions by changing microclimate factors such as heat island intensity. By combining generation expansion with carbon emission prediction model, the proposed approach in this paper considers the hidden mechanism of carbon and heat emission change on air-conditioning loads and dynamically optimizes the carbon reduction pathways in coastal metropolises. Taking Pudong Area in Shanghai as an example, the estimated cost of carbon reduction is reduced by the proposed approach. Some suggestions for the carbon reduction in coastal metropolises are made according to the simulation results. Table and Figures | Reference | Supplementary Material | Related Articles | Metrics | Comments（0）

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Optimization of Lithium Battery Lifetime Based on Dual-Stage Active Topology ZHANG Cheng, JU Changjiang, XIONG Can, YANG Genke Journal of Shanghai Jiao Tong University    2024, 58 (5): 719-729.   DOI: 10.16183/j.cnki.jsjtu.2022.285 Abstract （1091）   HTML （3）    PDF（pc） （1687KB）（249）       Knowledge map    Save With the increasing demand for energy storage charging stations, many energy storage systems utilize lithium batteries as the major carriers. However, due to frequent charging and discharging at high power levels, the cycle life of lithium batteries is greatly reduced, which increases the energy storage costs. Given the longevity of supercapacitors, a supercapacitor-lithium hybrid energy storage system has been developed to effectively extend the lifespan of lithium batteries and reduce both investment and operational costs of energy storage charging stations. Based on the dual-stage active topology, a hybrid energy storage system combining supercapacitor-lithium is proposed. Under mild load conditions, two supercapacitor modules are alternatively charged by the lithium battery. Then, the supercapacitor modules are discharges when high power demands are encountered. Accordingly, based on working conditions of the charging pile, a multi-stage strategy, integrating state-of-power estimation and programming, is proposed to optimize the power distribution, smooth the power fluctuation of the lithium battery, and protect the lithium battery. The simulation results show that compared with the lithium batteries only energy storage and the traditional full active topology energy storage, the dual-stage active topology energy storage significantly improves the cycle life of lithium batteries. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Layout Optimization Design of Human Machine Interface in Wheelhouse Based on Ergonomics JI Yuheng, LI Chuntong, LUO Xiaomeng, YANG Xuelian, WANG Deyu Journal of Shanghai Jiao Tong University    2024, 58 (2): 201-210.   DOI: 10.16183/j.cnki.jsjtu.2022.401 Abstract （1089）   HTML （12）    PDF（pc） （6622KB）（178）       Knowledge map    Save To solve the problems of empiricism, subjectivity and randomness in the manual layout of human machine interface in wheelhouse, an optimization layout design method of human machine interface that combines virtual simulation and optimization algorithm is proposed. First, the optimal operating point and the operating comfort of each area of the human machine interface are obtained through virtual simulation. Then, the layout criteria and ergonomics criteria of human machine interface are quantified as objective functions and constraints, a layout optimization mathematical model of human machine interface is established, and a large number of initial positions of the particles in the particle swarm optimization (PSO) algorithm are obtained through the differential evolution algorithm. Finally, the optimal layout scheme is obtained, and virtual simulation evaluation is conducted. Taking a control panel as an example for layout optimization and virtual simulation, the optimal layout scheme obtained is proved to satisfy ergonomic criteria, and the performance of the human machine interface has been improved. This paper can provide references for the layout design of the high performance human machine interface in wheelhouse. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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A Highly Robust State of Health Estimation Method for Lithium-Ion Batteries Based on ECM and SGPR CUI Xian, CHEN Ziqiang Journal of Shanghai Jiao Tong University    2024, 58 (5): 747-759.   DOI: 10.16183/j.cnki.jsjtu.2022.221 Abstract （1085）   HTML （5）    PDF（pc） （6197KB）（135）       Knowledge map    Save Accurately estimating the state of health (SOH) of lithium-ion batteries is of great significance in ensuring the safe operation of the battery system. Addressing the issue where traditional SOH estimation methods fail under variable working conditions, an online SOH estimation method for lithium-ion batteries based on equivalent circuit model (ECM) and sparse Gaussian process regression (SGPR) is proposed. During the constant current charging process, the parameters of the ECM of lithium-ion battery are dynamically identified by two online filters, based on which, a condition-insensitive health indicator is constructed. In combination with the SGPR, the indirect SOH estimation is achieved. This method uses the unified signal processing method and feature mapping model under various working conditions, and features strong robustness with low redundancy. The experimental results show that the average absolute error of the method proposed under various working conditions does not exceed 0.94%, and the root mean square error stays below 1.12%. When benchmarked against existing methods, this method has significant advantages in comprehensive performance. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Day-Ahead Scheduling of Traction Power Supply System with Photovoltaic and Energy Storage Access GAO Fengyang, SONG Zhixiang, GAO Jianning, GAO Xuanyu, YANG Kaiwen Journal of Shanghai Jiao Tong University    2024, 58 (5): 760-775.   DOI: 10.16183/j.cnki.jsjtu.2022.253 Abstract （1085）   HTML （5）    PDF（pc） （8888KB）（147）       Knowledge map    Save In recent years, in order to achieve the goal of “carbon peaking and carbon neutrality” of the electrified railway, a number of railroad energy optimization initiatives have been implemented, but with little success. To further reduce the carbon emissions of the electrified railway, its energy supply structure is changed by connecting photovoltaic and energy storage devices to the traction power supply system. First, the composite traction power supply system is constructed, and its working conditions are classified according to the composition of system energy supply. Then, the priorities are set based on the priorities of system operation constraints, and the optimal state of the system under different operating conditions is realized through hierarchical optimization. Finally, the converter capacity is reasonably optimized to achieve the minimum carbon emission under the win-win situation of the system operation performance and economic benefits. The simulation results show that the composite traction power supply system ensures the stable operation of the system while greatly reducing the carbon emission of the system and achieving the optimal performance. Table and Figures | Reference | Supplementary Material | Related Articles | Metrics | Comments（0）

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Low-Carbon Optimal Operation Strategy of Integrated Energy System Considering Generalized Energy Storage and LCA Carbon Emission SUN Yi, GU Jiaxun, ZHENG Shunlin, LI Xiong, LU Chunguang, LIU Wei Journal of Shanghai Jiao Tong University    2024, 58 (5): 647-658.   DOI: 10.16183/j.cnki.jsjtu.2022.350 Abstract （1085）   HTML （4）    PDF（pc） （3035KB）（145）       Knowledge map    Save Integrated energy system (IES) is the key to achieve the “dual carbon goals” in face of the current energy industry transformation and low-carbon development. In order to improve the carbon emission reduction capacity of the IES, it is necessary to make full use of the load resources on the demand side and the generalized energy storage resources such as traditional energy storage equipment to participate in the optimization of the IES. First, an IES optimization operation model considering renewable energy, energy conversion equipment, generalized energy storage equipment, and energy market transaction is established. Then, the life cycle assessment (LCA) method is used to calculate the carbon emission of the whole process of energy cycle and equipment cycle in the IES, and the carbon emission cost is included in the total cost of the system. The results of simulation experiments show that the proposed model is not only conducive to reducing the total scheduling cost of the IES, but also able to reduce the carbon emissions of the system and effectively promote the low-carbon development of the IES. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Prediction of Slip and Torsion Performance of Right-Angle Fasteners Based on Machine Learning Methods BAO Zhujie, LI Zhen, WANG Feiliang, PANG Bo, YANG Jian Journal of Shanghai Jiao Tong University    2024, 58 (2): 242-252.   DOI: 10.16183/j.cnki.jsjtu.2022.399 Abstract （1080）   HTML （9）    PDF（pc） （11483KB）（139）       Knowledge map    Save Aiming at the issue of large CPU costs and low calculation accuracy in the design of right-angle fasteners in scaffolding structures, prediction models of fastener anti-slip performance and torsion performance based on machine learning are proposed. A three-dimensional solid model of right-angle fasteners is established using the finite element method, the effectiveness of the numerical simulation method is verified through test results, and the comprehensive influence of various design parameters on the performance of fasteners is revealed by the parametric analysis method. The database is established by combining the test and numerical simulation results, and the fastener stiffness prediction models are proposed based on random forest (RF), support vector machine (SVM) and K-most proximity algorithm (K-NN), respectively. The expressions for the measured point displacement of the anti-slip model and the stiffness prediction of the torsion model are proposed in combination with genetic expression programming. The results indicate that SVM and GEP can predict the displacement and torsional stiffness of right-angle fasteners more accurately, which is important for guiding the safety design of fasteners in engineering scaffolding structures. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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In-Situ X-Ray CT Characterization of Damage Mechanism of Plain Weave SiCf/SiC Composites Under Compression CHENG Xiangwei, ZHANG Daxu, DU Yonglong, GUO Hongbao, HONG Zhiliang Journal of Shanghai Jiao Tong University    2024, 58 (2): 232-241.   DOI: 10.16183/j.cnki.jsjtu.2022.322 Abstract （1065）   HTML （5）    PDF（pc） （27080KB）（212）       Knowledge map    Save In order to reveal the damage evolution and failure mechanism of ceramic matrix composites (CMCs), in-situ X-ray CT compression tests of plain weave SiCf/SiC composites were conducted, and the CT data during loading and after failure were obtained. Displacement and strain distributions of the material were evaluated by the digital volume correlation (DVC) technology. The three-dimensional visual model of the composite was created by using image processing software. The spatial distributions of tow split and other damages were segmented by the deep learning algorithm. The qualitative and quantitative analysis of compression damage evolution were performed. The results show that there is a relatively large expansion induced by barreling in the thickness direction and a little shrinkage in the width direction during the unidirectional compression, while the barreling in the thickness direction is the main reason to trigger compressive damages of the material. Damages such as matrix falling-off at surface, tow split, delamination, will occur as the compression was approaching the ultimate load. Fiber kinking results in the final compressive failure of the material, while an obvious V-shaped shear band is observed in the fracture. The analysis of compressive damage evolution of plain weave SiCf/SiC shows that the DVC technology and deep learning-based image segmentation methods could effectively reveal the compressive damage evolution mechanism of ceramic matrix composites. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Identification of Inrush Current and Fault Current Based on Long Short-Term Memory Neural Network ZHANG Guodong, LIU Kai, PU Haitao, YAO Fuqiang, ZHANG Shuaishuai Journal of Shanghai Jiao Tong University    2024, 58 (5): 730-738.   DOI: 10.16183/j.cnki.jsjtu.2022.352 Abstract （1063）   HTML （8）    PDF（pc） （2182KB）（151）       Knowledge map    Save The problem of differential protection maloperation caused by inrush current during no-load closing of transformer has not been completely solved so far. To solve this problem, a method using long short-term memory (LSTM) neural network to identify inrush current and fault current is proposed. First, the simulation model of no-load closing and internal fault of transformer is built on the PSCAD software platform, and a large amount of three-phase current instantaneous sampling data is generated through simulation as the sample set to train the neural network. Then, the LSTM neural network model is built and trained by using the Keras platform. Finally, the new simulation data and fault recorder data is used to test the trained LSTM neural network. The results show that the LSTM neural network can quickly and accurately distinguish the inrush current and fault current under various conditions, which proves the effectiveness of the proposed method. Table and Figures | Reference | Related Articles | Metrics | Comments（0）