In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results i...In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results in increased leakage current,decreased breakdown voltage,and lower nonlinearity,ultimately compromising their protective performance.To investigate the evolution in electrical properties during DC aging,this work developed a finite element model based on Voronoi networks and conducted accelerated aging tests on commercial varistors.Throughout the aging process,current-voltage characteristics and Schottky barrier parameters were measured and analyzed.The results indicate that when subjected to constant voltage,current flows through regions with larger grain sizes,forming discharge channels.As aging progresses,the current focus increases on these channels,leading to a decline in the varistor’s overall performance.Furthermore,analysis of the Schottky barrier parameters shows that the changes in electrical performance during aging are non-monotonic.These findings offer theoretical support for understanding the aging mechanisms and condition assessment of modern stable ZnO varistors.展开更多
The hybrid dc circuit breaker(HCB)has the advantages of fast action speed and low operating loss,which is an idealmethod for fault isolation ofmulti-terminal dc grids.Formulti-terminal dc grids that transmit power thr...The hybrid dc circuit breaker(HCB)has the advantages of fast action speed and low operating loss,which is an idealmethod for fault isolation ofmulti-terminal dc grids.Formulti-terminal dc grids that transmit power through overhead lines,HCBs are required to have reclosing capability due to the high fault probability and the fact that most of the faults are temporary faults.To avoid the secondary fault strike and equipment damage that may be caused by the reclosing of the HCB when the permanent fault occurs,an adaptive reclosing scheme based on traveling wave injection is proposed in this paper.The scheme injects traveling wave signal into the fault dc line through the additionally configured auxiliary discharge branch in the HCB,and then uses the reflection characteristic of the traveling wave signal on the dc line to identify temporary and permanent faults,to be able to realize fast reclosing when the temporary fault occurs and reliably avoid reclosing after the permanent fault occurs.The test results in the simulation model of the four-terminal dc grid show that the proposed adaptive reclosing scheme can quickly and reliably identify temporary and permanent faults,greatly shorten the power outage time of temporary faults.In addition,it has the advantages of easiness to implement,high reliability,robustness to high-resistance fault and no dead zone,etc.展开更多
Given the grave local and international network security landscape,a national strategic level analysis indicates that the modernization and advancement within the Industry 4.0 era are closely correlated with overall c...Given the grave local and international network security landscape,a national strategic level analysis indicates that the modernization and advancement within the Industry 4.0 era are closely correlated with overall competitive strength.Consequently,China proposed a strategy for the integration of industrialization and informatization,optimizing and adjusting its industrial structure to swiftly achieve transformation and upgrading in the Industry 4.0 era,thereby enhancing the sophistication of intelligent industrial control systems.The distributed control system in a nuclear power plant functions as an industrial control system,overseeing the operational status of the physical process.Its ability to ensure safe and reliable operation is directly linked to nuclear safety and the cybersecurity of the facility.The management of network security in distributed control systems(DCS)is crucial for achieving this objective.Due to the varying network settings and parameters of the DCS implemented in each nuclear power plant,the network security status of the system sometimes diverges from expectations.During system operation,it will undoubtedly encounter network security issues.Consequently,nuclear power plants utilize the technical criteria outlined in GB/T 22239 to formulate a network security management program aimed at enhancing the operational security of DCS within these facilities.This study utilizes existing network security regulations and standards as a reference to analyze the network security control standards based on the nuclear power plant’s control system.It delineates the fundamental requirements for network security management,facilitating integration with the entire life cycle of the research,development,and application of the nuclear power plant’s distributed control system,thereby establishing a network security management methodology that satisfies the control requirements of the nuclear power plant.Initially,it presents DCS and network security management,outlines current domestic and international network security legislation and standards,and specifies the standards pertinent to the administration of DCS in nuclear power plants.Secondly,the design of network security management for DCS is executed in conjunction with the specific context of nuclear power plants.This encompasses the deployment of network security apparatus,validation of the network security management strategy,and optimization adjustments.Consequently,recommendations beneficial to the network security management of nuclear power plants are compiled,aimed at establishing a management system and incorporating the concept of full life cycle management,which is predicated on system requirements,system design,and both software and hardware considerations.Conversely,it presents the notion of comprehensive life cycle management and suggests network security management strategies encompassing system requirements,system architecture,detailed hardware and software design and implementation,procurement,internal system integration,system validation and acceptance testing,system installation,operational maintenance,system modifications,and decommissioning.We will consistently enhance the performance and functionality of DCS in nuclear power plants,establish a safe and secure operational environment,and thereby facilitate the implementation of DCS in nuclear facilities while ensuring robust network security in the future.展开更多
Conventional coordinated control strategies for DC bus voltage signal(DBS)in islanded DC microgrids(IDCMGs)struggle with coordinating multiple distributed generators(DGs)and cannot effectively incorporate state of cha...Conventional coordinated control strategies for DC bus voltage signal(DBS)in islanded DC microgrids(IDCMGs)struggle with coordinating multiple distributed generators(DGs)and cannot effectively incorporate state of charge(SOC)information of the energy storage system,thereby reducing the system flexibility.In this study,we propose an adaptive coordinated control strategy that employs a two-layer fuzzy neural network controller(FNNC)to adapt to varying operating conditions in an IDCMG with multiple PV and battery energy storage system(BESS)units.The first-layer FNNC generates optimal operating mode commands for each DG,thereby avoiding the requirement for complex operating modes based on SOC segmentation.An optimal switching sequence logic prioritizes the most appropriate units during mode transitions.The second-layer FNNC dynamically adjusts the droop power to overcome power distribution challenges among DG groups.This helps in preventing the PV power from exceeding the limits and mitigating the risk of BESS overcharging or over-discharging.The simulation results indicate that the proposed strategy enhances the coordinated operation of multi-DG IDCMGs,thereby ensuring the efficient and safe utilization of PV and BESS.展开更多
With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limite...With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limited.This poses challenges for conventional fault distance estimation methods,which are often tailored to simple topologies and are thus difficult to apply to large-scale,multi-node DC networks.To address this,a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper.First,a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range and improve localization efficiency.Then,leveraging the high-frequency impedance characteristics and the voltage-current relationship of electrical quantities,a fault distance estimation approach based on high-frequency measurements from both ends of a line is designed.This enables accurate distance estimation even when the measurement devices are not directly placed at both ends of the faulted line,overcoming the dependence on specific sensor placement inherent in traditional methods.Finally,to further enhance accuracy,an optimization model based on minimizing the high-frequency voltage error at the fault point is introduced to reduce estimation error.Simulation results demonstrate that the proposed method achieves a fault distance estimation error of less than 1%under normal conditions,and maintains good performance even under adverse scenarios.展开更多
Security constrained multi area multi objective dynamic economic dispatch (SCMAMODED) with renewable energy (RE) and all the possible MTDC stability constraints is formulated for the first time. The stability merits o...Security constrained multi area multi objective dynamic economic dispatch (SCMAMODED) with renewable energy (RE) and all the possible MTDC stability constraints is formulated for the first time. The stability merits of multi terminal DC (MTDC) tie lines as compared to the traditional HVAC forms the main objective of this paper. Probabilistic load flow (PLF) is applied to determine the system parameters while the uncertainties are modelled using Scenario Based Method (SBM). The simulation results reveal that with the use of MTDC tie lines, the frequency and voltage stability in the MAMODED with renewable energy sources (RES) are enhanced while keeping the MTDC power exchange interface nodes at secure levels.展开更多
The AC/DC hybrid distribution network is one of the trends in distribution network development, which poses great challenges to the traditional distribution transformer. In this paper, a new topology suitable for AC/D...The AC/DC hybrid distribution network is one of the trends in distribution network development, which poses great challenges to the traditional distribution transformer. In this paper, a new topology suitable for AC/DC hybrid distribution network is put forward according to the demands of power grid, with advantages of accepting DG and DC loads, while clearing DC fault by blocking the clamping double sub-module(CDSM) of input stage. Then, this paper shows the typical structure of AC/DC distribution network that is hand in hand. Based on the new topology, this paper designs the control and modulation strategies of each stage, where the outer loop controller of input stage is emphasized for its twocontrol mode. At last, the rationality of new topology and the validity of control strategies are verified by the steady and dynamic state simulation. At the same time, the simulation results highlight the role of PET in energy regulation.展开更多
In order to guarantee quality during mass serial production of motors, a convenient approach on how to detect and diagnose the faults of a permanent-magnetic DC motor based on armature current analysis and BP neural n...In order to guarantee quality during mass serial production of motors, a convenient approach on how to detect and diagnose the faults of a permanent-magnetic DC motor based on armature current analysis and BP neural networks was presented in this paper. The fault feature vector was directly established by analyzing the armature current. Fault features were extracted from the current using various signal processing methods including Fourier analysis, wavelet analysis and statistical methods. Then an advanced BP neural network was used to finish decision-making and separate fault patterns. Finally, the accuracy of the method in this paper was verified by analyzing the mechanism of faults theoretically. The consistency between the experimental results and the theoretical analysis shows that four kinds of representative faults of low power permanent-magnetic DC motors can be diagnosed conveniently by this method. These four faults are brush fray, open circuit of components, open weld of components and short circuit between armature coils. This method needs fewer hardware instruments than the conventional method and whole procedures can be accomplished by several software packages developed in this paper.展开更多
A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to...A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.展开更多
An optimized commutation method based on backpropagation(BP)neural network is proposed to resolve the low stability and high-power consumption caused by inaccurate commutation point prediction in conventional commutat...An optimized commutation method based on backpropagation(BP)neural network is proposed to resolve the low stability and high-power consumption caused by inaccurate commutation point prediction in conventional commutation strategy during acceleration and deceleration.This article also builds a complete brushless DC motor drive system based on the GD32F103 micro control unit(MCU),with an Artix-7 XC7A35T field programmable gate array(FPGA)to meet the performance requirements of neural network calculation for real-time motor commutation control.Experimental results show that the proposed optimization strategy can effectively improve the system stability during system acceleration and deceleration,and reduce the current spikes generated during speed chan-ges.The system power consumption is reduced by about 11.7%on average.展开更多
A new kind of dynamic neural network--diagonal recurrent neural network (DRNN) and its learning method and architecture are presented. A direct adaptive control scheme is also developed that is applied to a DC (Direct...A new kind of dynamic neural network--diagonal recurrent neural network (DRNN) and its learning method and architecture are presented. A direct adaptive control scheme is also developed that is applied to a DC (Direct Current) speed control system with the ability to auto-tune PI (Proportion Integral) parameters based on combining DRNN with PI controller. The simulation results of DRNN show better control performances and potential practical use in comparison with PI controller.展开更多
Brushless DC(BLDC)motor is a complex nonlinear system,of which some parameters will also change during operation.Therefore,obtaining accurate rotor position directly through the line voltage becomes more difficult.So ...Brushless DC(BLDC)motor is a complex nonlinear system,of which some parameters will also change during operation.Therefore,obtaining accurate rotor position directly through the line voltage becomes more difficult.So a new method is proposed in this paper which uses three line voltages as the input signal to identify the motor position based on adaptive wavelet neural network(WNN)and the differential evolution(DE)algorithm to optimize WNN structures,thus realizing the improvement of accuracy,exactness of the communication signals and convergence speed of the rotor position identification.Finally,both simulations and experimental results show that the proposed method has high accuracy of recognizing rotor position and strong orientation ability.展开更多
ADC distribution network is an effective solution for increasing renewable energy utilization with distinct benefits,such as high efficiency and easy control.However,a sudden increase in the current after the occurren...ADC distribution network is an effective solution for increasing renewable energy utilization with distinct benefits,such as high efficiency and easy control.However,a sudden increase in the current after the occurrence of faults in the network may adversely affect network stability.This study proposes an artificial neural network(ANN)-based fault detection and protection method for DC distribution networks.The ANN is applied to a classifier for different faults ontheDC line.The backpropagationneuralnetwork is used to predict the line current,and the fault detection threshold is obtained on the basis of the difference between the predicted current and the actual current.The proposed method only uses local signals,with no requirement of a strict communication link.Simulation experiments are conducted for the proposed algorithm on a two-terminal DC distribution network modeled in the PSCAD/EMTDC and developed on the MATLAB platform.The results confirm that the proposed method can accurately detect and classify line faults within a few milliseconds and is not affected by fault locations,fault resistance,noise,and communication delay.展开更多
This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal mod...This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.展开更多
The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optim...The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach.展开更多
[Objectives]To expose the plausible mechanism of Blumea balsamifera(L.)DC.against Alzheimer s disease via network pharmacology and HPLC-ESI-HRMS technology.[Methods]To begin with,HPLC-ESI-HRMS was employed to identify...[Objectives]To expose the plausible mechanism of Blumea balsamifera(L.)DC.against Alzheimer s disease via network pharmacology and HPLC-ESI-HRMS technology.[Methods]To begin with,HPLC-ESI-HRMS was employed to identify the components of B.balsamifera.Secondly,the potential targets of the components were identified and predicted based on chemical similarity and online databases.Thirdly,by way of topological analysis of a component-disease target interaction network,the primary candidate targets and potential active components were identified.Lastly,molecular docking analysis was used to confirm the interaction between active components and therapeutic targets.[Results]According to the final results,HPLC-ESI-HRMS identified 70 components.Out of these,20 components were potentially biologically active,and most of them were sesquiterpenoids.According to the molecular docking results,the primary active components were appropriately coordinated with the core targets,indicating a high level of pharmacodynamic activity.Thus,the sesquiterpenes present in B.balsamifera are considered potential active ingredients having multi-target and multi-pathway effects for treating Alzheimer s disease.[Conclusions]This research will provide a scientific reference for the future pharmacological activity and clinical application of B.balsamifera.展开更多
文摘In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results in increased leakage current,decreased breakdown voltage,and lower nonlinearity,ultimately compromising their protective performance.To investigate the evolution in electrical properties during DC aging,this work developed a finite element model based on Voronoi networks and conducted accelerated aging tests on commercial varistors.Throughout the aging process,current-voltage characteristics and Schottky barrier parameters were measured and analyzed.The results indicate that when subjected to constant voltage,current flows through regions with larger grain sizes,forming discharge channels.As aging progresses,the current focus increases on these channels,leading to a decline in the varistor’s overall performance.Furthermore,analysis of the Schottky barrier parameters shows that the changes in electrical performance during aging are non-monotonic.These findings offer theoretical support for understanding the aging mechanisms and condition assessment of modern stable ZnO varistors.
基金supported by the Science and Technology Project of State Grid Corporation of China under Grant 520201210025。
文摘The hybrid dc circuit breaker(HCB)has the advantages of fast action speed and low operating loss,which is an idealmethod for fault isolation ofmulti-terminal dc grids.Formulti-terminal dc grids that transmit power through overhead lines,HCBs are required to have reclosing capability due to the high fault probability and the fact that most of the faults are temporary faults.To avoid the secondary fault strike and equipment damage that may be caused by the reclosing of the HCB when the permanent fault occurs,an adaptive reclosing scheme based on traveling wave injection is proposed in this paper.The scheme injects traveling wave signal into the fault dc line through the additionally configured auxiliary discharge branch in the HCB,and then uses the reflection characteristic of the traveling wave signal on the dc line to identify temporary and permanent faults,to be able to realize fast reclosing when the temporary fault occurs and reliably avoid reclosing after the permanent fault occurs.The test results in the simulation model of the four-terminal dc grid show that the proposed adaptive reclosing scheme can quickly and reliably identify temporary and permanent faults,greatly shorten the power outage time of temporary faults.In addition,it has the advantages of easiness to implement,high reliability,robustness to high-resistance fault and no dead zone,etc.
文摘Given the grave local and international network security landscape,a national strategic level analysis indicates that the modernization and advancement within the Industry 4.0 era are closely correlated with overall competitive strength.Consequently,China proposed a strategy for the integration of industrialization and informatization,optimizing and adjusting its industrial structure to swiftly achieve transformation and upgrading in the Industry 4.0 era,thereby enhancing the sophistication of intelligent industrial control systems.The distributed control system in a nuclear power plant functions as an industrial control system,overseeing the operational status of the physical process.Its ability to ensure safe and reliable operation is directly linked to nuclear safety and the cybersecurity of the facility.The management of network security in distributed control systems(DCS)is crucial for achieving this objective.Due to the varying network settings and parameters of the DCS implemented in each nuclear power plant,the network security status of the system sometimes diverges from expectations.During system operation,it will undoubtedly encounter network security issues.Consequently,nuclear power plants utilize the technical criteria outlined in GB/T 22239 to formulate a network security management program aimed at enhancing the operational security of DCS within these facilities.This study utilizes existing network security regulations and standards as a reference to analyze the network security control standards based on the nuclear power plant’s control system.It delineates the fundamental requirements for network security management,facilitating integration with the entire life cycle of the research,development,and application of the nuclear power plant’s distributed control system,thereby establishing a network security management methodology that satisfies the control requirements of the nuclear power plant.Initially,it presents DCS and network security management,outlines current domestic and international network security legislation and standards,and specifies the standards pertinent to the administration of DCS in nuclear power plants.Secondly,the design of network security management for DCS is executed in conjunction with the specific context of nuclear power plants.This encompasses the deployment of network security apparatus,validation of the network security management strategy,and optimization adjustments.Consequently,recommendations beneficial to the network security management of nuclear power plants are compiled,aimed at establishing a management system and incorporating the concept of full life cycle management,which is predicated on system requirements,system design,and both software and hardware considerations.Conversely,it presents the notion of comprehensive life cycle management and suggests network security management strategies encompassing system requirements,system architecture,detailed hardware and software design and implementation,procurement,internal system integration,system validation and acceptance testing,system installation,operational maintenance,system modifications,and decommissioning.We will consistently enhance the performance and functionality of DCS in nuclear power plants,establish a safe and secure operational environment,and thereby facilitate the implementation of DCS in nuclear facilities while ensuring robust network security in the future.
基金supported by National Key R&D Program of ChinaunderGrant,(2021YFB2601403).
文摘Conventional coordinated control strategies for DC bus voltage signal(DBS)in islanded DC microgrids(IDCMGs)struggle with coordinating multiple distributed generators(DGs)and cannot effectively incorporate state of charge(SOC)information of the energy storage system,thereby reducing the system flexibility.In this study,we propose an adaptive coordinated control strategy that employs a two-layer fuzzy neural network controller(FNNC)to adapt to varying operating conditions in an IDCMG with multiple PV and battery energy storage system(BESS)units.The first-layer FNNC generates optimal operating mode commands for each DG,thereby avoiding the requirement for complex operating modes based on SOC segmentation.An optimal switching sequence logic prioritizes the most appropriate units during mode transitions.The second-layer FNNC dynamically adjusts the droop power to overcome power distribution challenges among DG groups.This helps in preventing the PV power from exceeding the limits and mitigating the risk of BESS overcharging or over-discharging.The simulation results indicate that the proposed strategy enhances the coordinated operation of multi-DG IDCMGs,thereby ensuring the efficient and safe utilization of PV and BESS.
基金National Natural Science Foundation of China, grant number 52177074.
文摘With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limited.This poses challenges for conventional fault distance estimation methods,which are often tailored to simple topologies and are thus difficult to apply to large-scale,multi-node DC networks.To address this,a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper.First,a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range and improve localization efficiency.Then,leveraging the high-frequency impedance characteristics and the voltage-current relationship of electrical quantities,a fault distance estimation approach based on high-frequency measurements from both ends of a line is designed.This enables accurate distance estimation even when the measurement devices are not directly placed at both ends of the faulted line,overcoming the dependence on specific sensor placement inherent in traditional methods.Finally,to further enhance accuracy,an optimization model based on minimizing the high-frequency voltage error at the fault point is introduced to reduce estimation error.Simulation results demonstrate that the proposed method achieves a fault distance estimation error of less than 1%under normal conditions,and maintains good performance even under adverse scenarios.
文摘Security constrained multi area multi objective dynamic economic dispatch (SCMAMODED) with renewable energy (RE) and all the possible MTDC stability constraints is formulated for the first time. The stability merits of multi terminal DC (MTDC) tie lines as compared to the traditional HVAC forms the main objective of this paper. Probabilistic load flow (PLF) is applied to determine the system parameters while the uncertainties are modelled using Scenario Based Method (SBM). The simulation results reveal that with the use of MTDC tie lines, the frequency and voltage stability in the MAMODED with renewable energy sources (RES) are enhanced while keeping the MTDC power exchange interface nodes at secure levels.
基金supported by National Key Research and Development Program of China (2016YFB0900500,2017YFB0903100)the State Grid Science and Technology Project (SGRI-DL-F1-51-011)
文摘The AC/DC hybrid distribution network is one of the trends in distribution network development, which poses great challenges to the traditional distribution transformer. In this paper, a new topology suitable for AC/DC hybrid distribution network is put forward according to the demands of power grid, with advantages of accepting DG and DC loads, while clearing DC fault by blocking the clamping double sub-module(CDSM) of input stage. Then, this paper shows the typical structure of AC/DC distribution network that is hand in hand. Based on the new topology, this paper designs the control and modulation strategies of each stage, where the outer loop controller of input stage is emphasized for its twocontrol mode. At last, the rationality of new topology and the validity of control strategies are verified by the steady and dynamic state simulation. At the same time, the simulation results highlight the role of PET in energy regulation.
文摘In order to guarantee quality during mass serial production of motors, a convenient approach on how to detect and diagnose the faults of a permanent-magnetic DC motor based on armature current analysis and BP neural networks was presented in this paper. The fault feature vector was directly established by analyzing the armature current. Fault features were extracted from the current using various signal processing methods including Fourier analysis, wavelet analysis and statistical methods. Then an advanced BP neural network was used to finish decision-making and separate fault patterns. Finally, the accuracy of the method in this paper was verified by analyzing the mechanism of faults theoretically. The consistency between the experimental results and the theoretical analysis shows that four kinds of representative faults of low power permanent-magnetic DC motors can be diagnosed conveniently by this method. These four faults are brush fray, open circuit of components, open weld of components and short circuit between armature coils. This method needs fewer hardware instruments than the conventional method and whole procedures can be accomplished by several software packages developed in this paper.
文摘A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.
基金the National Key Research and Development Program(No.2017YFB0406204,2016YFC0105604)Beijing Science and Technology Projects(No.Z181100003818002)Science and Technology Service Network Initiative(No.FJ-STS-QYZX-099,KFJ-STS-ZDTP-069).
文摘An optimized commutation method based on backpropagation(BP)neural network is proposed to resolve the low stability and high-power consumption caused by inaccurate commutation point prediction in conventional commutation strategy during acceleration and deceleration.This article also builds a complete brushless DC motor drive system based on the GD32F103 micro control unit(MCU),with an Artix-7 XC7A35T field programmable gate array(FPGA)to meet the performance requirements of neural network calculation for real-time motor commutation control.Experimental results show that the proposed optimization strategy can effectively improve the system stability during system acceleration and deceleration,and reduce the current spikes generated during speed chan-ges.The system power consumption is reduced by about 11.7%on average.
文摘A new kind of dynamic neural network--diagonal recurrent neural network (DRNN) and its learning method and architecture are presented. A direct adaptive control scheme is also developed that is applied to a DC (Direct Current) speed control system with the ability to auto-tune PI (Proportion Integral) parameters based on combining DRNN with PI controller. The simulation results of DRNN show better control performances and potential practical use in comparison with PI controller.
文摘Brushless DC(BLDC)motor is a complex nonlinear system,of which some parameters will also change during operation.Therefore,obtaining accurate rotor position directly through the line voltage becomes more difficult.So a new method is proposed in this paper which uses three line voltages as the input signal to identify the motor position based on adaptive wavelet neural network(WNN)and the differential evolution(DE)algorithm to optimize WNN structures,thus realizing the improvement of accuracy,exactness of the communication signals and convergence speed of the rotor position identification.Finally,both simulations and experimental results show that the proposed method has high accuracy of recognizing rotor position and strong orientation ability.
基金supported by Key Natural Science Research Projects of Colleges and Universities in Anhui Province(No.2022AH051831).
文摘ADC distribution network is an effective solution for increasing renewable energy utilization with distinct benefits,such as high efficiency and easy control.However,a sudden increase in the current after the occurrence of faults in the network may adversely affect network stability.This study proposes an artificial neural network(ANN)-based fault detection and protection method for DC distribution networks.The ANN is applied to a classifier for different faults ontheDC line.The backpropagationneuralnetwork is used to predict the line current,and the fault detection threshold is obtained on the basis of the difference between the predicted current and the actual current.The proposed method only uses local signals,with no requirement of a strict communication link.Simulation experiments are conducted for the proposed algorithm on a two-terminal DC distribution network modeled in the PSCAD/EMTDC and developed on the MATLAB platform.The results confirm that the proposed method can accurately detect and classify line faults within a few milliseconds and is not affected by fault locations,fault resistance,noise,and communication delay.
文摘This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.
基金the National Natural Science Foundation of China(52177074).
文摘The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach.
基金Supported by Science and Technology Project of Guizhou Province of China(QKHPTRC[2021]259,QKH LH[2017]7146)Doctoral Research Initiation Fund(GYZYYFY-BS-2018[14])+2 种基金2018 Guizhou Provincial High Level Innovative Talent ProjectResearch Project on Traditional Chinese Medicine and Ethnic Medicine Science and Technology in Guizhou Province(QZYY2017-079,QZYY2017-087)Project of Key Laboratory Characteristic Forestry of Guizhou Province of China(QJHKY[2021]002).
文摘[Objectives]To expose the plausible mechanism of Blumea balsamifera(L.)DC.against Alzheimer s disease via network pharmacology and HPLC-ESI-HRMS technology.[Methods]To begin with,HPLC-ESI-HRMS was employed to identify the components of B.balsamifera.Secondly,the potential targets of the components were identified and predicted based on chemical similarity and online databases.Thirdly,by way of topological analysis of a component-disease target interaction network,the primary candidate targets and potential active components were identified.Lastly,molecular docking analysis was used to confirm the interaction between active components and therapeutic targets.[Results]According to the final results,HPLC-ESI-HRMS identified 70 components.Out of these,20 components were potentially biologically active,and most of them were sesquiterpenoids.According to the molecular docking results,the primary active components were appropriately coordinated with the core targets,indicating a high level of pharmacodynamic activity.Thus,the sesquiterpenes present in B.balsamifera are considered potential active ingredients having multi-target and multi-pathway effects for treating Alzheimer s disease.[Conclusions]This research will provide a scientific reference for the future pharmacological activity and clinical application of B.balsamifera.
