本文作者提出了一种含储能的混合式配电变压器(Hybrid Distribution Transformer,HDT)电路拓扑,并重点研究了双向DC/DC变换器的设计。该拓扑结合储能电池和超级电容,通过双向DC/DC变换器实现HDT与储能装置之间的双向电能流动。本文推导...本文作者提出了一种含储能的混合式配电变压器(Hybrid Distribution Transformer,HDT)电路拓扑,并重点研究了双向DC/DC变换器的设计。该拓扑结合储能电池和超级电容,通过双向DC/DC变换器实现HDT与储能装置之间的双向电能流动。本文推导了双向DC/DC变换器的小信号模型,详细阐述了电路参数选取方法,并设计了相应的控制器。在Matlab/Simulink中实现了仿真验证,结果表明所设计的系统能够实现功率的双向传递,验证了所提出拓扑和控制策略的有效性和可行性。展开更多
Atractylodes macrocephala Koidz.(A.macrocephala)is a medicinal and edible plant species belonging to the Compositae family.Its rhizome serves both therapeutic and nutritional purposes in China.This investigation led t...Atractylodes macrocephala Koidz.(A.macrocephala)is a medicinal and edible plant species belonging to the Compositae family.Its rhizome serves both therapeutic and nutritional purposes in China.This investigation led to the isolation of thirteen novel rearranged 9(8→7)-abeo-eudesmane-type sesquiterpenoid dimers(SDs),atramacronins A-M(1-13),three eudesmane-type SDs,atramacronins N-P(14-16),and two previously identified meroterpenoids,atrachinenin G(17)and atrachineninΙ(18),from Atractylodes macrocephala.Structure elucidation was accomplished through comprehensive spectroscopic analysis and single-crystal X-ray diffraction.Compounds 1,4-7,9,and 10 exhibited notable cytotoxicity against Hep3B,HepG2,and Huh7 cell lines,with half maximal inhibitory concentration(IC50)values ranging from 3.71 to 13.99μmol·L-1.展开更多
为保证核电安全级分布式控制系统(Distributed Control System,DCS)通信模块光电转换的安全与可靠通信,本文介绍了一种基于DCS通信模块的光电复用技术,并设计开发了光电复用装置。梳理安全级DCS的每种通信板卡需要的接口类型、通信介质...为保证核电安全级分布式控制系统(Distributed Control System,DCS)通信模块光电转换的安全与可靠通信,本文介绍了一种基于DCS通信模块的光电复用技术,并设计开发了光电复用装置。梳理安全级DCS的每种通信板卡需要的接口类型、通信介质及通信速率,将各种通信接口的接口电路从电平转换与信号类型等方面进行兼容设计,并从硬件结构上进行统一物料选型,统一选择接口。通过现场可编程门阵列(Field-Programmable Gate Array,FPGA)的GTX接口配置串行千兆媒体独立接口(Serial Gigabit Media Independent Interface,SGMII)模式,实现10/100/1000 Mbps自适应,光、电模块采用小型可插拔式(Small Form-factor Pluggable,SFP)模块统一封装,单板卡支持多种介质,通过选择可插拔光模块或者可插拔电模块将光电通信接口设计为光电复用接口。该设计解决了目前复杂网络中的光路、电路切换时面临的设备频繁更换问题,实现了核电安全级DCS系统中通信模块的光电兼容复用设计,提高了产品的可靠性和可用性。展开更多
This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine t...This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine the transmission power of the DC and AC paths to simultaneously improve voltage quality and reduce losses.First,considering the embedded interconnected,unbalanced power structure of the distribution area,a power flow calculation method for EDC-LVDA that accounts for three-phase unbalanced compensation is introduced.This method accurately describes the power flow distribution characteristics under both AC and DC power allocation scenarios.Second,an optimization scheduling model for EDC-LVDA under three-phase unbalanced conditions is developed,incorporating network losses,voltage quality,DC link losses,and unbalance levels.The proposed model employs an improved particle swarm optimization(IPSO)two-layer algorithm to autonomously select different power allocation coefficients for the DC link and AC section under various operating conditions.This enables embedded economic optimization scheduling while maintaining compensation for unbalanced conditions.Finally,a case study based on the IEEE 13-node system for EDC-LVDA is conducted and tested.The results show that the proposed optimal operation method achieves a 100%voltage compliance rate and reduces network losses by 13.8%,while ensuring three-phase power balance compensation.This provides a practical solution for the modernization and upgrading of low-voltage power grids.展开更多
The rapid integration of photovoltaic(PV)generation and energy storage systems has significantly increased the operational complexity of low-voltage direct current(LVDC)distribution networks in zero-carbon parks.Under...The rapid integration of photovoltaic(PV)generation and energy storage systems has significantly increased the operational complexity of low-voltage direct current(LVDC)distribution networks in zero-carbon parks.Under highly variable operating conditions,conventional DC protection schemes relying on fixed overcurrent thresholds often suffer from maloperation or failure to trip,particularly during fluctuations in PV power,load switching,and changes in network topology.To address these challenges,this paper proposes an adaptive DC protection strategy based on an artificial neural network(ANN)-driven dynamic threshold optimization mechanism.The proposed method replaces static protection settings with an adaptive threshold that is continuously updated according to real-time system operating conditions.A dual-layer ANN architecture is developed to capture the nonlinear relationship between grid parameter variations and optimal protection thresholds.To enhance learning accuracy and convergence performance,the backpropagation neural network is further optimized using an improved grey wolf optimizer with a nonlinear convergence factor and mutation operator.The optimized ANN enables rapid and reliable threshold adjustment without relying on high-speed communication,making the scheme suitable for decentralized and edge-computing-based protection architectures.A comprehensive simulation platform for a PV-energy storage LVDC distribution system is established in MATLAB/Simulink to generate training and testing datasets under diverse scenarios,including variations in PV output,load shedding,different fault types,and measurement uncertainties.Simulation results demonstrate that the proposed adaptive protection strategy effectively eliminates threshold mismatch problems observed in fixed-setting methods.The results confirm that the proposed ANN-based adaptive protection strategy provides a robust,fast,and communication-independent solution for reliable protection of LVDC distribution networks with high penetration of renewable energy sources.展开更多
To address the operational challenges posed by renewable energy generation uncertainty and load fluctuations in DC microgrids,this paper proposes a hierarchical coordinated optimization control strategy for electricit...To address the operational challenges posed by renewable energy generation uncertainty and load fluctuations in DC microgrids,this paper proposes a hierarchical coordinated optimization control strategy for electricity-hydrogen hybrid DC microgrids(EH-DC-MG).The strategy aims to leverage the synergistic advantages of hybrid electricity-hydrogen energy storage to simultaneously achieve multiple objectives,including economic system operation,efficient utilization of renewable energy,and reliable power supply.The upper optimization scheduling layer formulates a mixed-integer linear programming model with the objective of minimizing the total system cost,which incorporates equipment operation and maintenance expenses,battery depreciation,penalties for renewable energy curtailment,and power/hydrogen supply shortages.By solving this model,optimal power reference signals are generated for devices.The lower device control layer employs designed DC/DC converter control strategies to ensure fast and accurate tracking of the optimization commands while maintaining DC bus voltage stability.Simulation results demonstrate that the proposed strategy can effectively coordinate electricity-hydrogen energy conversion and storage.Under various typical and extreme scenarios,the system maintains a high renewable energy utilization rate—remaining above 97.572%even under extreme conditions—while keeping the power shortage rate and hydrogen load curtailment rate at low levels.Specifically,under extreme power deficit scenarios,these rates are limited to 2.003%and 5.081%,respectively,which are significantly below the 10%quality constraint threshold,thereby ensuring a high degree of supply reliability.In addition,the DC bus voltage fluctuation is stabilized within 0.37%,far below the 5%safety operation threshold,validating the effectiveness of the control strategy.This study confirms that the proposed hierarchical coordinated optimization control strategy can support electricity-hydrogen hybrid DC microgrids in achieving economical,reliable,and resilient operation,providing a key technical reference for the optimized management of microgrids with high penetration of renewable energy.展开更多
The high-temperature dissolution behavior of carbides during the quenching process significantly influences grain growth,mechanical properties,and secondary carbide precipitation,thereby playing a major role in the he...The high-temperature dissolution behavior of carbides during the quenching process significantly influences grain growth,mechanical properties,and secondary carbide precipitation,thereby playing a major role in the heat treatment process of die steel.This study investigated the changes in carbide type,particle size distribution,and weight percentage in DC53 steel after holding at 1060℃for 2 h,followed by oil quenching.The analysis was conducted using Thermo-Calc,DICTRA computations,and experimental methods including electron backscatter diffraction,transmission electron microscopy and laser particle size analysis.The experimental results showed that four types of carbides(M7C3,M6C,M23C6,and MC)existed in DC53 steel before quenching.After quenching,M23C6carbides were almost entirely dissolved,while the other three types partially dissolved into the matrix.The volume-weighted geometric mean size of carbides(xgeo,3)increased from 5.43 to 15.15μm,and the weight percentage decreased from 13.03%to 5.01%.Small-sized carbides(below 5μm)dissolved more readily,which primarily accounted for the reduction in carbide weight percentage during quenching.In contrast,the weight percentage of large-sized carbides(greater than 10μm)varies less.DICTRA computations indicated that M7C3carbides smaller than 7μm can completely dissolve into the matrix after holding at 1060℃for 2 h.The findings provide an effective reference for optimizing carbide control during the heat treatment process of DC53 steel.展开更多
The increasing integration of distributed renewable energy sources in the distribution network leads to unbalanced load rates in the distribution network.The traditional load balancing methods are mainly based on netw...The increasing integration of distributed renewable energy sources in the distribution network leads to unbalanced load rates in the distribution network.The traditional load balancing methods are mainly based on network reconfiguration,which have problems such as a long time scale and poor adaptability.In response to these issues,this paper proposes a distributed iterative learning control(ILC)strategy for load balancing in flexible AC/DC hybrid distribution systems.This method combines the consensus algorithm with the ILC mechanism to construct a multi-terminal AC/DC flexible interconnection system model.It is only necessary to measure the load rate of adjacent units without observing the overall system status,which greatly reduces complexity and enhances robustness.In this paper,a new energy photovoltaic and energy storage integrated system was built through MATLAB/Simulink simulation,and the effectiveness of the proposed strategy under normal working conditions and port faults was verified through this system.Through comparative studies with event-triggered control and traditional consensus algorithms,as well as real-time simulations on the RT-LAB simulation platform,it has been confirmed that this method has superior performance in terms of convergence speed,steady-state accuracy,and dynamic response,and has the potential to be applied in practical models.It is suitable for application in medium and low voltage distribution systems with new energy access.展开更多
摘要本文作者提出了一种含储能的混合式配电变压器(Hybrid Distribution Transformer,HDT)电路拓扑,并重点研究了双向DC/DC变换器的设计。该拓扑结合储能电池和超级电容,通过双向DC/DC变换器实现HDT与储能装置之间的双向电能流动。本文推导了双向DC/DC变换器的小信号模型,详细阐述了电路参数选取方法,并设计了相应的控制器。在Matlab/Simulink中实现了仿真验证,结果表明所设计的系统能够实现功率的双向传递,验证了所提出拓扑和控制策略的有效性和可行性。
基金supported by the National Natural Science Foundation of China(Nos.32470414,32100319,and 82104377)the Fundamental Research Funds for the Central Universities,SWU(No.SWU-KR22052)+1 种基金the Natural Science Foundation of Chongqing,China(No.CSTB2022NSCQMSX0878)Chongqing Municipal Training Program of Innovation and Entrepreneurship for Undergraduates(No.S20241063290).
摘要Atractylodes macrocephala Koidz.(A.macrocephala)is a medicinal and edible plant species belonging to the Compositae family.Its rhizome serves both therapeutic and nutritional purposes in China.This investigation led to the isolation of thirteen novel rearranged 9(8→7)-abeo-eudesmane-type sesquiterpenoid dimers(SDs),atramacronins A-M(1-13),three eudesmane-type SDs,atramacronins N-P(14-16),and two previously identified meroterpenoids,atrachinenin G(17)and atrachineninΙ(18),from Atractylodes macrocephala.Structure elucidation was accomplished through comprehensive spectroscopic analysis and single-crystal X-ray diffraction.Compounds 1,4-7,9,and 10 exhibited notable cytotoxicity against Hep3B,HepG2,and Huh7 cell lines,with half maximal inhibitory concentration(IC50)values ranging from 3.71 to 13.99μmol·L-1.
基金supported by the key technology project of China Southern Power Grid Corporation(GZKJXM20220041)partly by the National Key Research and Development Plan(2022YFE0205300).
摘要This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine the transmission power of the DC and AC paths to simultaneously improve voltage quality and reduce losses.First,considering the embedded interconnected,unbalanced power structure of the distribution area,a power flow calculation method for EDC-LVDA that accounts for three-phase unbalanced compensation is introduced.This method accurately describes the power flow distribution characteristics under both AC and DC power allocation scenarios.Second,an optimization scheduling model for EDC-LVDA under three-phase unbalanced conditions is developed,incorporating network losses,voltage quality,DC link losses,and unbalance levels.The proposed model employs an improved particle swarm optimization(IPSO)two-layer algorithm to autonomously select different power allocation coefficients for the DC link and AC section under various operating conditions.This enables embedded economic optimization scheduling while maintaining compensation for unbalanced conditions.Finally,a case study based on the IEEE 13-node system for EDC-LVDA is conducted and tested.The results show that the proposed optimal operation method achieves a 100%voltage compliance rate and reduces network losses by 13.8%,while ensuring three-phase power balance compensation.This provides a practical solution for the modernization and upgrading of low-voltage power grids.
基金supported by the Key Science and Technology Project of China Southern Power Grid Co.,Ltd.(GZKJXM20232507).
摘要The rapid integration of photovoltaic(PV)generation and energy storage systems has significantly increased the operational complexity of low-voltage direct current(LVDC)distribution networks in zero-carbon parks.Under highly variable operating conditions,conventional DC protection schemes relying on fixed overcurrent thresholds often suffer from maloperation or failure to trip,particularly during fluctuations in PV power,load switching,and changes in network topology.To address these challenges,this paper proposes an adaptive DC protection strategy based on an artificial neural network(ANN)-driven dynamic threshold optimization mechanism.The proposed method replaces static protection settings with an adaptive threshold that is continuously updated according to real-time system operating conditions.A dual-layer ANN architecture is developed to capture the nonlinear relationship between grid parameter variations and optimal protection thresholds.To enhance learning accuracy and convergence performance,the backpropagation neural network is further optimized using an improved grey wolf optimizer with a nonlinear convergence factor and mutation operator.The optimized ANN enables rapid and reliable threshold adjustment without relying on high-speed communication,making the scheme suitable for decentralized and edge-computing-based protection architectures.A comprehensive simulation platform for a PV-energy storage LVDC distribution system is established in MATLAB/Simulink to generate training and testing datasets under diverse scenarios,including variations in PV output,load shedding,different fault types,and measurement uncertainties.Simulation results demonstrate that the proposed adaptive protection strategy effectively eliminates threshold mismatch problems observed in fixed-setting methods.The results confirm that the proposed ANN-based adaptive protection strategy provides a robust,fast,and communication-independent solution for reliable protection of LVDC distribution networks with high penetration of renewable energy sources.
基金supported by the Science and Technology Project of China Southern Power Grid under Grant ZBKJXM20240021.
摘要To address the operational challenges posed by renewable energy generation uncertainty and load fluctuations in DC microgrids,this paper proposes a hierarchical coordinated optimization control strategy for electricity-hydrogen hybrid DC microgrids(EH-DC-MG).The strategy aims to leverage the synergistic advantages of hybrid electricity-hydrogen energy storage to simultaneously achieve multiple objectives,including economic system operation,efficient utilization of renewable energy,and reliable power supply.The upper optimization scheduling layer formulates a mixed-integer linear programming model with the objective of minimizing the total system cost,which incorporates equipment operation and maintenance expenses,battery depreciation,penalties for renewable energy curtailment,and power/hydrogen supply shortages.By solving this model,optimal power reference signals are generated for devices.The lower device control layer employs designed DC/DC converter control strategies to ensure fast and accurate tracking of the optimization commands while maintaining DC bus voltage stability.Simulation results demonstrate that the proposed strategy can effectively coordinate electricity-hydrogen energy conversion and storage.Under various typical and extreme scenarios,the system maintains a high renewable energy utilization rate—remaining above 97.572%even under extreme conditions—while keeping the power shortage rate and hydrogen load curtailment rate at low levels.Specifically,under extreme power deficit scenarios,these rates are limited to 2.003%and 5.081%,respectively,which are significantly below the 10%quality constraint threshold,thereby ensuring a high degree of supply reliability.In addition,the DC bus voltage fluctuation is stabilized within 0.37%,far below the 5%safety operation threshold,validating the effectiveness of the control strategy.This study confirms that the proposed hierarchical coordinated optimization control strategy can support electricity-hydrogen hybrid DC microgrids in achieving economical,reliable,and resilient operation,providing a key technical reference for the optimized management of microgrids with high penetration of renewable energy.
基金supported by the Central Guide Local Science and Technology Development Project of Hubei Province of China(No.2023EGA008)the Wuhan Natural Science Foundation Exploration Project(Chenguang Project,2024040801020309)。
摘要The high-temperature dissolution behavior of carbides during the quenching process significantly influences grain growth,mechanical properties,and secondary carbide precipitation,thereby playing a major role in the heat treatment process of die steel.This study investigated the changes in carbide type,particle size distribution,and weight percentage in DC53 steel after holding at 1060℃for 2 h,followed by oil quenching.The analysis was conducted using Thermo-Calc,DICTRA computations,and experimental methods including electron backscatter diffraction,transmission electron microscopy and laser particle size analysis.The experimental results showed that four types of carbides(M7C3,M6C,M23C6,and MC)existed in DC53 steel before quenching.After quenching,M23C6carbides were almost entirely dissolved,while the other three types partially dissolved into the matrix.The volume-weighted geometric mean size of carbides(xgeo,3)increased from 5.43 to 15.15μm,and the weight percentage decreased from 13.03%to 5.01%.Small-sized carbides(below 5μm)dissolved more readily,which primarily accounted for the reduction in carbide weight percentage during quenching.In contrast,the weight percentage of large-sized carbides(greater than 10μm)varies less.DICTRA computations indicated that M7C3carbides smaller than 7μm can completely dissolve into the matrix after holding at 1060℃for 2 h.The findings provide an effective reference for optimizing carbide control during the heat treatment process of DC53 steel.
基金funded by State Grid Anhui Electric Power Co. (No. B3120524003J).
摘要The increasing integration of distributed renewable energy sources in the distribution network leads to unbalanced load rates in the distribution network.The traditional load balancing methods are mainly based on network reconfiguration,which have problems such as a long time scale and poor adaptability.In response to these issues,this paper proposes a distributed iterative learning control(ILC)strategy for load balancing in flexible AC/DC hybrid distribution systems.This method combines the consensus algorithm with the ILC mechanism to construct a multi-terminal AC/DC flexible interconnection system model.It is only necessary to measure the load rate of adjacent units without observing the overall system status,which greatly reduces complexity and enhances robustness.In this paper,a new energy photovoltaic and energy storage integrated system was built through MATLAB/Simulink simulation,and the effectiveness of the proposed strategy under normal working conditions and port faults was verified through this system.Through comparative studies with event-triggered control and traditional consensus algorithms,as well as real-time simulations on the RT-LAB simulation platform,it has been confirmed that this method has superior performance in terms of convergence speed,steady-state accuracy,and dynamic response,and has the potential to be applied in practical models.It is suitable for application in medium and low voltage distribution systems with new energy access.