Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,th...Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm.The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control.Then,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy.Precise pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid voltage.Additionally,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee algorithm.These operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load transients.This strategy effectively mitigated transient voltage and current surges during mode transitions.Consequently,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid inverter.The enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability.展开更多
This paper addresses the distributed optimization problem of discrete-time multiagent systems with nonconvex control input constraints and switching topologies.We introduce a novel distributed optimization algorithm w...This paper addresses the distributed optimization problem of discrete-time multiagent systems with nonconvex control input constraints and switching topologies.We introduce a novel distributed optimization algorithm with a switching mechanism to guarantee that all agents eventually converge to an optimal solution point,while their control inputs are constrained in their own nonconvex region.It is worth noting that the mechanism is performed to tackle the coexistence of the nonconvex constraint operator and the optimization gradient term.Based on the dynamic transformation technique,the original nonlinear dynamic system is transformed into an equivalent one with a nonlinear error term.By utilizing the nonnegative matrix theory,it is shown that the optimization problem can be solved when the union of switching communication graphs is jointly strongly connected.Finally,a numerical simulation example is used to demonstrate the acquired theoretical results.展开更多
This paper considers a dynamic optimization problem(DOP)of 1,3-propanediol fermentation process(1,3-PFP).Our main contributions are as follows.Firstly,the DOP of 1,3-PFP is modeled as an optimal control problem of swi...This paper considers a dynamic optimization problem(DOP)of 1,3-propanediol fermentation process(1,3-PFP).Our main contributions are as follows.Firstly,the DOP of 1,3-PFP is modeled as an optimal control problem of switched dynamical systems.Unlike the existing switched dynamical system optimal control problem,the state-dependent switching method is applied to design the switching rule.Then,in order to obtain the numerical solution,by introducing a discrete-valued function and using a relaxation technique,this problem is transformed into a nonlinear parameter optimization problem(NPOP).Although the gradient-based algorithm is very efficient for solving NPOPs,the existing algorithm is always trapped in a local minimum for such problems with multiple local minima.Next,in order to overcome this challenge,a gradient-based random search algorithm(GRSA)is proposed based on an improved gradient-based algorithm(IGA)and a novel random search algorithm(NRSA),which cannot usually be trapped in a local minimum.The convergence results are also established,and show that the GRSA is globally convergent.Finally,a DOP of 1,3-PFP is provided to illustrate the effectiveness of the GRSA proposed by this paper.展开更多
This paper systematically evaluates and compares three well-engineered and popular multi-objective optimization algorithms for the design of switched reluctance machines.The multi-physics and multi-objective nature of...This paper systematically evaluates and compares three well-engineered and popular multi-objective optimization algorithms for the design of switched reluctance machines.The multi-physics and multi-objective nature of electric machine design problems are discussed,followed by benchmark studies comparing generic algorithms(GA),differential evolution(DE)algorithms and particle swarm optimizations(PSO)on a 6/4 switched reluctance machine design with seven independent variables and a strong nonlinear multi-objective Pareto front.To better quantify the quality of the Pareto fronts,five primary quality indicators are employed to serve as the algorithm testing metrics.The results show that the three algorithms have similar performances when the optimization employs only a small number of candidate designs or ultimately,a significant amount of candidate designs.However,DE tends to perform better in terms of convergence speed and the quality of Pareto front when a relatively modest amount of candidates are considered.展开更多
By using Impulsive Maximum Principal and three stage optimization method,this paper discusses optimization problems for linear impulsive switched systems with hybridcontrols, which includes continuous control and impu...By using Impulsive Maximum Principal and three stage optimization method,this paper discusses optimization problems for linear impulsive switched systems with hybridcontrols, which includes continuous control and impulsive control. The linear quadratic optimizationproblems without constraints such as optimal hybrid control, optimal stability and optimalswitching instants are addressed in detail. These results are applicable to optimal control problemsin economics,mechanics, and management.展开更多
A lifetime prediction method for high-reliability tantalum (Ta) capacitors was proposed, based on multiple degradation measures and grey model (GM). For analyzing performance degradation data, a two-parameter mode...A lifetime prediction method for high-reliability tantalum (Ta) capacitors was proposed, based on multiple degradation measures and grey model (GM). For analyzing performance degradation data, a two-parameter model based on GM was developed. In order to improve the prediction accuracy of the two-parameter model, parameter selection based on particle swarm optimization (PSO) was used. Then, the new PSO-GM(1, 2, co) optimization model was constructed, which was validated experimentally by conducting an accelerated testing on the Ta capacitors. The experiments were conducted at three different stress levels of 85, 120, and 145℃. The results of two experiments were used in estimating the parameters. And the reliability of the Ta capacitors was estimated at the same stress conditions of the third experiment. The results indicate that the proposed method is valid and accurate.展开更多
In order to reduce the torque ripple,increase the average torque and optimize the drive performance of the switched reluctance motor (SRM),the nonlinear dynamic model of SRM is established in the MATLAB /Simulink envi...In order to reduce the torque ripple,increase the average torque and optimize the drive performance of the switched reluctance motor (SRM),the nonlinear dynamic model of SRM is established in the MATLAB /Simulink environment.The effects of the turn-on and turn-off angles are investigated by the simulation results of the dynamic model,and the function is made among the rotor speed,turn-on angle and turn-off angle.To optimize the torque dynamic performance,the two-objective simultaneous optimization function is proposed by two weight factors.And the optimized turn-on and turn-off angles as functions of rotor speed are developed by using the simultaneous optimization method.Then the optimized torque controller is designed based on the optimized turn-on and turn-off angles.The simulation results show that the optimized torque controller designed in this paper can effectively reduce the torque ripple and increase the average torque,and optimize the torque dynamic performance of the SRM.展开更多
Since practical mathematical model for the design optimization of switched reluctance motor(SRM)is difficult to derive because of the strong nonlinearity,precise prediction of electromagnetic characteristics is of gre...Since practical mathematical model for the design optimization of switched reluctance motor(SRM)is difficult to derive because of the strong nonlinearity,precise prediction of electromagnetic characteristics is of great importance during the optimization procedure.In this paper,an improved generalized regression neural network(GRNN)optimized by fruit fly optimization algorithm(FOA)is proposed for the modeling of SRM that represent the relationship of torque ripple and efficiency with the optimization variables,stator pole arc,rotor pole arc and rotor yoke height.Finite element parametric analysis technology is used to obtain the sample data for GRNN training and verification.Comprehensive comparisons and analysis among back propagation neural network(BPNN),radial basis function neural network(RBFNN),extreme learning machine(ELM)and GRNN is made to test the effectiveness and superiority of FOA-GRNN.展开更多
Alternating Current–Direct Current(AC–DC)converters require a high value bulk capacitor or afilter capacitor between the DC–DC conversion stages,which in turn causes many problems in the design of a AC–DC converter...Alternating Current–Direct Current(AC–DC)converters require a high value bulk capacitor or afilter capacitor between the DC–DC conversion stages,which in turn causes many problems in the design of a AC–DC converter.The component package size for this capacitor is large due to its high voltage rating and capacitance value.In addition,the high charging current creates more pro-blems during the product compliance testing phase.The shelf life of these specific high value capacitors is less than that of Multilayer Ceramic Capacitors(MLCC),which limits its use for the highly reliable applications.This paper presents a fea-sibility study to overcome these two problems by adding a few sensing mechan-isms to the typical AC–DC converter topology.In majority of the AC–DC converter,Al-Elko capacitor takes approximately 3%to 5%of the converter size.The proposed method reduces this to approximately 50%size and so it effectively approximates 2%to 3%size reduction in converter size.The proposed method basically works based on the load current prediction method and hence it is highly suitable for the constant load application.Moreover,the converter response time increases in this method,which limit its application in high-speed systems.The high temperature application of Al-Elko capacitor is limited because of its poor performance,which is significantly rectified by replacing the Al-Elko with MLCC as it delivers good performance in high temperature.展开更多
Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into p...Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into power system.Under this condition if capacitor banks are not properly selected and placed in the power system,they could amplify and propagate these harmonics and deteriorate power quality to unacceptable levels.With attention of disadvantages of passive filters,such as occurring resonance,nowadays the usage of this type of harmonic compensator is restricted.On the other side,one of parallel multi-function compensating devices which are recently used in distribution system to mitigate voltage sag and harmonic distortion,performs power factor correction,and improves the overall power quality as active power conditioner(APC).Therefore,the utilization of APC in harmonic distorted system can affect and change the optimal location and size of shunt capacitor bank under harmonic distortion condition.This paper presents an optimization algorithm for improvement of power quality using simultaneous optimal placement and sizing of APC and shunt capacitor banks in radial distribution networks in the presence of voltage and current harmonics.The algorithm is based on particle swarm optimization(PSO).The objective function includes the cost of power losses,energy losses and those of the capacitor banks and APCs.展开更多
We present an electrical grid optimization method for economical benefit. After simplifying an IEEE feeder diagram, we build a compact smart grid system including a photovoltaic-inverter system, a shunt capacitor, an ...We present an electrical grid optimization method for economical benefit. After simplifying an IEEE feeder diagram, we build a compact smart grid system including a photovoltaic-inverter system, a shunt capacitor, an on-load tapchanger(OLTC) and transmission lines. The system power factor(PF) regulation and reactive power dispatching are indispensable to improve power quality. Our control method uses predictive weather and load data to decide engaging or tripping the shunt capacitor, or reactive power injection by the photovoltaic-inverter system, ultimately to keep the system PF in a good range. From the perspective of economics, the economical model is considered as a decision maker in our predictive data control method.Capacitor-only control strategy is a common photovoltaic(PV)regulation method, which is treated as a baseline case. Simulations with GridLAB-D on profiled loads and residential loads have been carried out. The comparison results with baseline control strategy and our predictive data control method show the appreciable economical benefit of our method.展开更多
A multiobjective quality of service (QoS) routing algorithm was proposed and used as the QoS-aware path selection approach in differentiated services and multi-protocol label switching (DiffServ-MPLS) networks. It sim...A multiobjective quality of service (QoS) routing algorithm was proposed and used as the QoS-aware path selection approach in differentiated services and multi-protocol label switching (DiffServ-MPLS) networks. It simultaneously optimizes multiple QoS objectives by a genetic algorithm in conjunction with concept of Pareto dominance. The simulation demonstrates that the proposed algorithm is capable of discovering a set of QoS-based near optimal paths within in a few iterations. In addition, the simulation results also show the scalability of the algorithm with increasing number of network nodes.展开更多
In order to solve the problem of vibration bounce caused by the contact between moving and stationary contacts in the process of switching on,two-degree-of-freedom motion differential equation of the contact system is...In order to solve the problem of vibration bounce caused by the contact between moving and stationary contacts in the process of switching on,two-degree-of-freedom motion differential equation of the contact system is established.Genetic algorithm is used to optimize the pull in process of AC contactor.The whole process of contact bounce was observed and analyzed by high-speed photography experiment.The theory and experimental results were very similar.The iron core has collided before the contact is separated,which further aggravates the contact bounce.When the iron core bounces collided again,the bounce of the contact was not affected.During the operation of the contactor,the movement of the moving iron core will cause slight vibration of the system.The contact bounce time and the maximum amplitude are reduced.The research results provide a theoretical basis for further control and reduction of contact bounce.展开更多
With the recent advances of the VLSI technologies, stabilizing the physical behavior of VLSI chips is becoming a very complicated problem. Power grid optimization is required to minimize the risks of timing error by I...With the recent advances of the VLSI technologies, stabilizing the physical behavior of VLSI chips is becoming a very complicated problem. Power grid optimization is required to minimize the risks of timing error by IR drop, defects by electro migration (EM), and manufacturing cost by the chip size. This problem includes complicated tradeoff relationships. We propose a new approach by observing the direct objectives of manufacturing cost, and timing error risk caused by IR drop and EM. The manufacturing cost is based on yield for LSI chip. The optimization is executed in early phase of the physical design, and the purpose is to find the rough budget of decoupling capacitors that may cause block size increase. Rough budgeting of the power wire width is also determined simultaneously. The experimental result shows that our approach enables selection of a cost sensitive result or a performance sensitive result in early physical design phase.展开更多
The Rate Distortion Optimization(RDO)algorithm in High Efficiency Video Coding(HEVC)has many iterations and a large number of calculations.In order to decrease the calculation time and meet the requirements of fast sw...The Rate Distortion Optimization(RDO)algorithm in High Efficiency Video Coding(HEVC)has many iterations and a large number of calculations.In order to decrease the calculation time and meet the requirements of fast switching of RDO algorithms of different scales,an RDO dynamic reconfigurable structure is proposed.First,the Quantization Parameter(QP)and bit rate values were loaded through an H⁃tree Configurable Network(HCN),and the execution status of the array was detected in real time.When the switching request of the RDO algorithm was detected,the corresponding configuration information was delivered.This self⁃reconfiguration implementation method improved the flexibility and utilization of hardware.Experimental results show that when the control bit width was only increased by 31.25%,the designed configuration network could increase the number of controllable processing units by 32 times,and the execution cycle was 50%lower than the same type of design.Compared with previous RDO algorithm,the RDO algorithm implemented on the reconfigurable array based on the configuration network had an average operating frequency increase of 12.5%and an area reduction of 56.4%.展开更多
Switched reluctance motor(SRM)usually adopts Direct Instantaneous Torque Control(DITC)to suppress torque ripple.However,due to the fixed turn-on angle and the control mode of the two-phase exchange region,the conventi...Switched reluctance motor(SRM)usually adopts Direct Instantaneous Torque Control(DITC)to suppress torque ripple.However,due to the fixed turn-on angle and the control mode of the two-phase exchange region,the conventional DITC control method has low adaptability in different working conditions,which will lead to large torque ripple.For this problem,an improved DITC control method based on turn-on angle optimization is proposed in this paper.Firstly,the improved BP neural network is used to construct a nonlinear torque model,so that the torque can be accurately fed back in real time.Secondly,the turn-on angle optimization algorithm based on improved GRNN neural network is established,so that the turn-on angle can be adjusted adaptively online.Then,according to the magnitude of inductance change rate,the two-phase exchange region is divided into two regions,and the phase with larger inductance change rate and current is selected to provide torque in the sub-regions.Finally,taking a 3-phase 6/20 SRM as example,simulation and experimental verification are carried out to verify the effectiveness of this method.展开更多
Network reconfiguration and capacitor switching are important measures to reduce power loss and improve security and economy in automation of distribution. A new method based on parallel genetic algorithm is proposed ...Network reconfiguration and capacitor switching are important measures to reduce power loss and improve security and economy in automation of distribution. A new method based on parallel genetic algorithm is proposed to search the whole problem space for better solution. Multiple populations evolve independently and communicate periodically, which simulates parallel computing process to save computing time. The results show that the method is robust and has better benefit than the alterative iteration method. In addition, the effect of overall optimization is better than optimization alone. Power loss can be reduced and the level of voltage can be greatly improved.展开更多
Power integrity (PI) has become a limiting factor for the chip's overall performance, and how to place in-package decoupling capacitors to improve a chip's PI performance has become a hot issue. In this paper,...Power integrity (PI) has become a limiting factor for the chip's overall performance, and how to place in-package decoupling capacitors to improve a chip's PI performance has become a hot issue. In this paper, we propose an improved trans- mission matrix method (TMM) for fast decoupling capacitance allocation. An irregular grid partition mechanism is proposed, which helps speed up the impedance computation and complies better with the irregular power/ground (P/G) plane or planes with many vias and decoupling capacitors. Furthermore, we also ameliorate the computation procedure of the impedance matrix whenever decoupling capacitors are inserted or removed at specific ports. With the fast computation of impedance change, in-package decoupling capacitor allocation is done with an efficient change based method in the frequency domain. Experimental results show that our approach can gain about 5× speedup compared with a general TMM, and is efficient in restraining the noise on the P/G plane.展开更多
A day-ahead voltage-stability-constrained network topology optimization(DVNTO)problem is proposed to find the day-ahead topology schemes with the minimum number of operations(including line switching and bus-bar split...A day-ahead voltage-stability-constrained network topology optimization(DVNTO)problem is proposed to find the day-ahead topology schemes with the minimum number of operations(including line switching and bus-bar splitting)while ensuring the sufficient hourly voltage stability margin and the engineering operation requirement of power systems.The AC continuation power flow and the uncertainty from both renewable energy sources and loads are incorporated into the formulation.The proposed DVNTO problem is a stochastic,largescale,nonlinear integer programming problem.To solve it tractably,a tailored three-stage solution methodology,including a scenario generation and reduction stage,a dynamic period partition stage,and a topology identification stage,is presented.First,to address the challenges posed by uncertainties,a novel problem-specified scenario reduction process is proposed to obtain the representative scenarios.Then,to obtain the minimum number of necessary operations to alter the network topologies for the next 24-hour horizon,a dynamic period partition strategy is presented to partition the hours into several periods according to the hourly voltage information based on the voltage stability problem.Finally,a topology identification stage is performed to identify the final network topology scheme.The effectiveness and robustness of the proposed three-stage solution methodology under different loading conditions and the effectiveness of the proposed partition strategy are evaluated on the IEEE 118-bus and 3120-bus power systems.展开更多
基金received funding from the Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX23_1633)2023 University Student Innovation and Entrepreneurship Training Program(202311463009Z)+1 种基金Changzhou Science and Technology Support Project(CE20235045)Open Project of Jiangsu Key Laboratory of Power Transmission&Distribution Equipment Technology(2021JSSPD12).
文摘Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm.The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control.Then,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy.Precise pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid voltage.Additionally,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee algorithm.These operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load transients.This strategy effectively mitigated transient voltage and current surges during mode transitions.Consequently,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid inverter.The enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability.
基金Project supported by the National Engineering Research Center of Rail Transportation Operation and Control System,Beijing Jiaotong University(Grant No.NERC2019K002)。
文摘This paper addresses the distributed optimization problem of discrete-time multiagent systems with nonconvex control input constraints and switching topologies.We introduce a novel distributed optimization algorithm with a switching mechanism to guarantee that all agents eventually converge to an optimal solution point,while their control inputs are constrained in their own nonconvex region.It is worth noting that the mechanism is performed to tackle the coexistence of the nonconvex constraint operator and the optimization gradient term.Based on the dynamic transformation technique,the original nonlinear dynamic system is transformed into an equivalent one with a nonlinear error term.By utilizing the nonnegative matrix theory,it is shown that the optimization problem can be solved when the union of switching communication graphs is jointly strongly connected.Finally,a numerical simulation example is used to demonstrate the acquired theoretical results.
基金the National Natural Science Foundation of China(61963010 and 61563011)the special project for cultivation of new academic talent and innovation exploration of Guizhou Normal University in 2019(11904-0520077)。
文摘This paper considers a dynamic optimization problem(DOP)of 1,3-propanediol fermentation process(1,3-PFP).Our main contributions are as follows.Firstly,the DOP of 1,3-PFP is modeled as an optimal control problem of switched dynamical systems.Unlike the existing switched dynamical system optimal control problem,the state-dependent switching method is applied to design the switching rule.Then,in order to obtain the numerical solution,by introducing a discrete-valued function and using a relaxation technique,this problem is transformed into a nonlinear parameter optimization problem(NPOP).Although the gradient-based algorithm is very efficient for solving NPOPs,the existing algorithm is always trapped in a local minimum for such problems with multiple local minima.Next,in order to overcome this challenge,a gradient-based random search algorithm(GRSA)is proposed based on an improved gradient-based algorithm(IGA)and a novel random search algorithm(NRSA),which cannot usually be trapped in a local minimum.The convergence results are also established,and show that the GRSA is globally convergent.Finally,a DOP of 1,3-PFP is provided to illustrate the effectiveness of the GRSA proposed by this paper.
文摘This paper systematically evaluates and compares three well-engineered and popular multi-objective optimization algorithms for the design of switched reluctance machines.The multi-physics and multi-objective nature of electric machine design problems are discussed,followed by benchmark studies comparing generic algorithms(GA),differential evolution(DE)algorithms and particle swarm optimizations(PSO)on a 6/4 switched reluctance machine design with seven independent variables and a strong nonlinear multi-objective Pareto front.To better quantify the quality of the Pareto fronts,five primary quality indicators are employed to serve as the algorithm testing metrics.The results show that the three algorithms have similar performances when the optimization employs only a small number of candidate designs or ultimately,a significant amount of candidate designs.However,DE tends to perform better in terms of convergence speed and the quality of Pareto front when a relatively modest amount of candidates are considered.
文摘By using Impulsive Maximum Principal and three stage optimization method,this paper discusses optimization problems for linear impulsive switched systems with hybridcontrols, which includes continuous control and impulsive control. The linear quadratic optimizationproblems without constraints such as optimal hybrid control, optimal stability and optimalswitching instants are addressed in detail. These results are applicable to optimal control problemsin economics,mechanics, and management.
基金Project(Z132012) supported by the Second Five Technology-based Fund in Science and Industry Bureau of ChinaProject(1004GK0032) supported by General Armament Department for the Common Issues of Military Electronic Components,China
文摘A lifetime prediction method for high-reliability tantalum (Ta) capacitors was proposed, based on multiple degradation measures and grey model (GM). For analyzing performance degradation data, a two-parameter model based on GM was developed. In order to improve the prediction accuracy of the two-parameter model, parameter selection based on particle swarm optimization (PSO) was used. Then, the new PSO-GM(1, 2, co) optimization model was constructed, which was validated experimentally by conducting an accelerated testing on the Ta capacitors. The experiments were conducted at three different stress levels of 85, 120, and 145℃. The results of two experiments were used in estimating the parameters. And the reliability of the Ta capacitors was estimated at the same stress conditions of the third experiment. The results indicate that the proposed method is valid and accurate.
基金Sponsored by the Ph.D.Program Foundation of Ministry of Education of China(Grant No.20092302120)
文摘In order to reduce the torque ripple,increase the average torque and optimize the drive performance of the switched reluctance motor (SRM),the nonlinear dynamic model of SRM is established in the MATLAB /Simulink environment.The effects of the turn-on and turn-off angles are investigated by the simulation results of the dynamic model,and the function is made among the rotor speed,turn-on angle and turn-off angle.To optimize the torque dynamic performance,the two-objective simultaneous optimization function is proposed by two weight factors.And the optimized turn-on and turn-off angles as functions of rotor speed are developed by using the simultaneous optimization method.Then the optimized torque controller is designed based on the optimized turn-on and turn-off angles.The simulation results show that the optimized torque controller designed in this paper can effectively reduce the torque ripple and increase the average torque,and optimize the torque dynamic performance of the SRM.
基金This work was supported in part by the National Natural Science Foundation of China under Grant61503132 and Grant51477047the Hunan Provincial Natural Science Foundation of China under Grant2015JJ5029.
文摘Since practical mathematical model for the design optimization of switched reluctance motor(SRM)is difficult to derive because of the strong nonlinearity,precise prediction of electromagnetic characteristics is of great importance during the optimization procedure.In this paper,an improved generalized regression neural network(GRNN)optimized by fruit fly optimization algorithm(FOA)is proposed for the modeling of SRM that represent the relationship of torque ripple and efficiency with the optimization variables,stator pole arc,rotor pole arc and rotor yoke height.Finite element parametric analysis technology is used to obtain the sample data for GRNN training and verification.Comprehensive comparisons and analysis among back propagation neural network(BPNN),radial basis function neural network(RBFNN),extreme learning machine(ELM)and GRNN is made to test the effectiveness and superiority of FOA-GRNN.
文摘Alternating Current–Direct Current(AC–DC)converters require a high value bulk capacitor or afilter capacitor between the DC–DC conversion stages,which in turn causes many problems in the design of a AC–DC converter.The component package size for this capacitor is large due to its high voltage rating and capacitance value.In addition,the high charging current creates more pro-blems during the product compliance testing phase.The shelf life of these specific high value capacitors is less than that of Multilayer Ceramic Capacitors(MLCC),which limits its use for the highly reliable applications.This paper presents a fea-sibility study to overcome these two problems by adding a few sensing mechan-isms to the typical AC–DC converter topology.In majority of the AC–DC converter,Al-Elko capacitor takes approximately 3%to 5%of the converter size.The proposed method reduces this to approximately 50%size and so it effectively approximates 2%to 3%size reduction in converter size.The proposed method basically works based on the load current prediction method and hence it is highly suitable for the constant load application.Moreover,the converter response time increases in this method,which limit its application in high-speed systems.The high temperature application of Al-Elko capacitor is limited because of its poor performance,which is significantly rectified by replacing the Al-Elko with MLCC as it delivers good performance in high temperature.
文摘Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into power system.Under this condition if capacitor banks are not properly selected and placed in the power system,they could amplify and propagate these harmonics and deteriorate power quality to unacceptable levels.With attention of disadvantages of passive filters,such as occurring resonance,nowadays the usage of this type of harmonic compensator is restricted.On the other side,one of parallel multi-function compensating devices which are recently used in distribution system to mitigate voltage sag and harmonic distortion,performs power factor correction,and improves the overall power quality as active power conditioner(APC).Therefore,the utilization of APC in harmonic distorted system can affect and change the optimal location and size of shunt capacitor bank under harmonic distortion condition.This paper presents an optimization algorithm for improvement of power quality using simultaneous optimal placement and sizing of APC and shunt capacitor banks in radial distribution networks in the presence of voltage and current harmonics.The algorithm is based on particle swarm optimization(PSO).The objective function includes the cost of power losses,energy losses and those of the capacitor banks and APCs.
文摘We present an electrical grid optimization method for economical benefit. After simplifying an IEEE feeder diagram, we build a compact smart grid system including a photovoltaic-inverter system, a shunt capacitor, an on-load tapchanger(OLTC) and transmission lines. The system power factor(PF) regulation and reactive power dispatching are indispensable to improve power quality. Our control method uses predictive weather and load data to decide engaging or tripping the shunt capacitor, or reactive power injection by the photovoltaic-inverter system, ultimately to keep the system PF in a good range. From the perspective of economics, the economical model is considered as a decision maker in our predictive data control method.Capacitor-only control strategy is a common photovoltaic(PV)regulation method, which is treated as a baseline case. Simulations with GridLAB-D on profiled loads and residential loads have been carried out. The comparison results with baseline control strategy and our predictive data control method show the appreciable economical benefit of our method.
文摘A multiobjective quality of service (QoS) routing algorithm was proposed and used as the QoS-aware path selection approach in differentiated services and multi-protocol label switching (DiffServ-MPLS) networks. It simultaneously optimizes multiple QoS objectives by a genetic algorithm in conjunction with concept of Pareto dominance. The simulation demonstrates that the proposed algorithm is capable of discovering a set of QoS-based near optimal paths within in a few iterations. In addition, the simulation results also show the scalability of the algorithm with increasing number of network nodes.
基金Natural Science Foundation of Shaanxi Province(No.2011J2009)。
文摘In order to solve the problem of vibration bounce caused by the contact between moving and stationary contacts in the process of switching on,two-degree-of-freedom motion differential equation of the contact system is established.Genetic algorithm is used to optimize the pull in process of AC contactor.The whole process of contact bounce was observed and analyzed by high-speed photography experiment.The theory and experimental results were very similar.The iron core has collided before the contact is separated,which further aggravates the contact bounce.When the iron core bounces collided again,the bounce of the contact was not affected.During the operation of the contactor,the movement of the moving iron core will cause slight vibration of the system.The contact bounce time and the maximum amplitude are reduced.The research results provide a theoretical basis for further control and reduction of contact bounce.
文摘With the recent advances of the VLSI technologies, stabilizing the physical behavior of VLSI chips is becoming a very complicated problem. Power grid optimization is required to minimize the risks of timing error by IR drop, defects by electro migration (EM), and manufacturing cost by the chip size. This problem includes complicated tradeoff relationships. We propose a new approach by observing the direct objectives of manufacturing cost, and timing error risk caused by IR drop and EM. The manufacturing cost is based on yield for LSI chip. The optimization is executed in early phase of the physical design, and the purpose is to find the rough budget of decoupling capacitors that may cause block size increase. Rough budgeting of the power wire width is also determined simultaneously. The experimental result shows that our approach enables selection of a cost sensitive result or a performance sensitive result in early physical design phase.
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.61834005,61772417,61802304,61602377,and 61634004)the Shaanxi Province Coordination Innovation Project of Science and Technology(Grant No.2016KTZDGY02-04-02)+1 种基金the Shaanxi Provincial Key R&D Plan(Grant No.2017GY-060)the Shaanxi International Science and Technology Cooperation Program(Grant No.2018KW-006).
文摘The Rate Distortion Optimization(RDO)algorithm in High Efficiency Video Coding(HEVC)has many iterations and a large number of calculations.In order to decrease the calculation time and meet the requirements of fast switching of RDO algorithms of different scales,an RDO dynamic reconfigurable structure is proposed.First,the Quantization Parameter(QP)and bit rate values were loaded through an H⁃tree Configurable Network(HCN),and the execution status of the array was detected in real time.When the switching request of the RDO algorithm was detected,the corresponding configuration information was delivered.This self⁃reconfiguration implementation method improved the flexibility and utilization of hardware.Experimental results show that when the control bit width was only increased by 31.25%,the designed configuration network could increase the number of controllable processing units by 32 times,and the execution cycle was 50%lower than the same type of design.Compared with previous RDO algorithm,the RDO algorithm implemented on the reconfigurable array based on the configuration network had an average operating frequency increase of 12.5%and an area reduction of 56.4%.
基金supported by National Natural Science Foundation of China under Grant 52167005Science and Technology Research Project of Jiangxi Provincial Department of Education under Grant GJJ200826。
文摘Switched reluctance motor(SRM)usually adopts Direct Instantaneous Torque Control(DITC)to suppress torque ripple.However,due to the fixed turn-on angle and the control mode of the two-phase exchange region,the conventional DITC control method has low adaptability in different working conditions,which will lead to large torque ripple.For this problem,an improved DITC control method based on turn-on angle optimization is proposed in this paper.Firstly,the improved BP neural network is used to construct a nonlinear torque model,so that the torque can be accurately fed back in real time.Secondly,the turn-on angle optimization algorithm based on improved GRNN neural network is established,so that the turn-on angle can be adjusted adaptively online.Then,according to the magnitude of inductance change rate,the two-phase exchange region is divided into two regions,and the phase with larger inductance change rate and current is selected to provide torque in the sub-regions.Finally,taking a 3-phase 6/20 SRM as example,simulation and experimental verification are carried out to verify the effectiveness of this method.
文摘Network reconfiguration and capacitor switching are important measures to reduce power loss and improve security and economy in automation of distribution. A new method based on parallel genetic algorithm is proposed to search the whole problem space for better solution. Multiple populations evolve independently and communicate periodically, which simulates parallel computing process to save computing time. The results show that the method is robust and has better benefit than the alterative iteration method. In addition, the effect of overall optimization is better than optimization alone. Power loss can be reduced and the level of voltage can be greatly improved.
基金the Ph.D Programs Foundation of Ministry of Education of China (No. 20060335065)the Natural Science Foundation of Zhejiang Province, China (No. Y106513)
文摘Power integrity (PI) has become a limiting factor for the chip's overall performance, and how to place in-package decoupling capacitors to improve a chip's PI performance has become a hot issue. In this paper, we propose an improved trans- mission matrix method (TMM) for fast decoupling capacitance allocation. An irregular grid partition mechanism is proposed, which helps speed up the impedance computation and complies better with the irregular power/ground (P/G) plane or planes with many vias and decoupling capacitors. Furthermore, we also ameliorate the computation procedure of the impedance matrix whenever decoupling capacitors are inserted or removed at specific ports. With the fast computation of impedance change, in-package decoupling capacitor allocation is done with an efficient change based method in the frequency domain. Experimental results show that our approach can gain about 5× speedup compared with a general TMM, and is efficient in restraining the noise on the P/G plane.
基金supported by the National Natural Science Foundation of China(No.52377109)the Natural Science Foundation of Shandong Province(No.ZR2022ME187)the Taishan Scholar Project of Shandong Province(No.TSQN202306191)。
文摘A day-ahead voltage-stability-constrained network topology optimization(DVNTO)problem is proposed to find the day-ahead topology schemes with the minimum number of operations(including line switching and bus-bar splitting)while ensuring the sufficient hourly voltage stability margin and the engineering operation requirement of power systems.The AC continuation power flow and the uncertainty from both renewable energy sources and loads are incorporated into the formulation.The proposed DVNTO problem is a stochastic,largescale,nonlinear integer programming problem.To solve it tractably,a tailored three-stage solution methodology,including a scenario generation and reduction stage,a dynamic period partition stage,and a topology identification stage,is presented.First,to address the challenges posed by uncertainties,a novel problem-specified scenario reduction process is proposed to obtain the representative scenarios.Then,to obtain the minimum number of necessary operations to alter the network topologies for the next 24-hour horizon,a dynamic period partition strategy is presented to partition the hours into several periods according to the hourly voltage information based on the voltage stability problem.Finally,a topology identification stage is performed to identify the final network topology scheme.The effectiveness and robustness of the proposed three-stage solution methodology under different loading conditions and the effectiveness of the proposed partition strategy are evaluated on the IEEE 118-bus and 3120-bus power systems.