When estimating the capacity of lithium-ion batteries offline or online,it is essential to extract a health feature(HF)that can effectively characterize capacity degradation under both conventional ideal and complex d...When estimating the capacity of lithium-ion batteries offline or online,it is essential to extract a health feature(HF)that can effectively characterize capacity degradation under both conventional ideal and complex dynamic operating conditions.However,the extraction of most HFs relies on complete charge-discharge cycle data,making them less adaptable to complex dynamic operating conditions.Existing mechanism HFs,while capable of characterizing capacity degradation from a mechanism perspective,suffer from limitations such as insufficient physical model expressiveness,high dimension,and redundancy of the mechanism HF.These issues increase the complexity of subsequent modeling of the relationship between HFs and capacity,thereby restricting their promotion in engineering practice.To meet this gap,this paper proposes a novel mechanism-based HF.Firstly,a multi-physical fields coupling model is developed to describe the interactions between electrochemical,thermal,and aging behaviors of the battery.Secondly,based on the aging mechanism,the accumulated charge of lithium lost during the formation of the solid electrolyte interphase(SEI)film is extracted as HF to provide a more intuitive representation of capacity degradation.Then,to reduce estimation errors caused by considering only a single aging mechanism,multiple representative regression models are employed to establish the mapping relationship between the mechanism HF and capacity,further enhancing the accuracy of final results.Finally,the proposed method is implemented and validated using real battery data under three different types of operating conditions.Experimental results demonstrate that,compared to other commonly used HFs,the proposed HF exhibits significant competitive advantages in handling incomplete cycle data,unknown operating conditions,and capacity estimation models.The minimum estimation error under ideal conditions is 0.0074,and the minimum estimation error under complex dynamic conditions is 0.0268.展开更多
Air traffic controllers face challenging initiatives due to uncertainty in air traffic.One way to support their initiatives is to identify similar operation scenes.Based on the operation characteristics of typical bus...Air traffic controllers face challenging initiatives due to uncertainty in air traffic.One way to support their initiatives is to identify similar operation scenes.Based on the operation characteristics of typical busy area control airspace,an complexity measurement indicator system is established.We find that operation in area sector is characterized by aggregation and continuity,and that dimensionality and information redundancy reduction are feasible for dynamic operation data base on principle components.Using principle components,discrete features and time series features are constructed.Based on Gaussian kernel function,Euclidean distance and dynamic time warping(DTW)are used to measure the similarity of the features.Then the matrices of similarity are input in Spectral Clustering.The clustering results show that similar scenes of trend are not ideal and similar scenes of modes are good base on the indicator system.Finally,actual vertical operation decisions for area sector and results of identification are compared,which are visualized by metric multidimensional scaling(MDS)plots.We find that identification results can well reflect the operation at peak hours,but controllers make different decisions under the similar conditions before dawn.The compliance rate of busy operation mode and division decisions at peak hours is 96.7%.The results also show subjectivity of actual operation and objectivity of identification.In most scenes,we observe that similar air traffic activities provide regularity for initiatives,validating the potential of this approach for initiatives and other artificial intelligence support.展开更多
The armored cable used in a deep-sea remotely operated vehicle(ROV) may undergo large displacement motion when subjected to dynamic actions of ship heave motion and ocean current. A novel geometrically exact finite el...The armored cable used in a deep-sea remotely operated vehicle(ROV) may undergo large displacement motion when subjected to dynamic actions of ship heave motion and ocean current. A novel geometrically exact finite element model for two-dimensional dynamic analysis of armored cable is presented. This model accounts for the geometric nonlinearities of large displacement of the armored cable, and effects of axial load and bending stiffness. The governing equations are derived by consistent linearization and finite element discretization of the total weak form of the armored cable system, and solved by the Newmark time integration method. To make the solution procedure avoid falling into the local extreme points, a simple adaptive stepping strategy is proposed. The presented model is validated via actual measured data. Results for dynamic configurations, motion and tension of both ends of the armored cable, and resonance-zone are presented for two numerical cases, including the dynamic analysis under the case of only ship heave motion and the case of joint action of ship heave motion and ocean current. The dynamics analysis can provide important reference for the design or product selection of the armored cable in a deep-sea ROV system so as to improve the safety of its marine operation under the sea state of 4 or above.展开更多
Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-di...Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms.展开更多
In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region,the airframe damage region division method based on the structure tensor dynamic operator is proposed...In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region,the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper.The structure tensor feature space is established to represent the local features of damage images.It makes different damage images have the same feature distribution,and transform varied damage region division into consistent process of feature space division.On this basis,the structure tensor dynamic operator generation method is designed.It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules,in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division.And then the airframe damage region division is realized.The experimental results on different airframe structure damage images show that compared with traditional threshold division method,the proposed method can improve the division quality.The interference of damage adjacent region is eliminated.The information loss caused by over-segmentation is avoided.And it is efficient in operation,and consistent in process.It also has the applicability to different types of structural damage.展开更多
In this paper we introduce the concept of tensor sum semigroups. Also we have given the examples of tensor sum operators which induce dynamical system on weighted locally convex function spaces.
Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has so...Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has some shortcoming s, in this paper, we proposed a new method using tree structure to express the relationship of solutions. Experiments prove that the method can reach the Pare-to front, retain the diversity of the population, and use less time.展开更多
A new dynamic model identification method is developed for continuous-time series analysis and forward prediction applications. The quantum of data is defined over moving time intervals in sliding window coordinates f...A new dynamic model identification method is developed for continuous-time series analysis and forward prediction applications. The quantum of data is defined over moving time intervals in sliding window coordinates for compressing the size of stored data while retaining the resolution of information. Quantum vectors are introduced as the basis of a linear space for defining a Dynamic Quantum Operator (DQO) model of the system defined by its data stream. The transport of the quantum of compressed data is modeled between the time interval bins during the movement of the sliding time window. The DQO model is identified from the samples of the real-time flow of data over the sliding time window. A least-square-fit identification method is used for evaluating the parameters of the quantum operator model, utilizing the repeated use of the sampled data through a number of time steps. The method is tested to analyze, and forward-predict air temperature variations accessed from weather data as well as methane concentration variations obtained from measurements of an operating mine. The results show efficient forward prediction capabilities, surpassing those using neural networks and other methods for the same task.展开更多
A family of array codes with a maximum distance separable（MDS） property, named L codes, is proposed. The greatest strength of L codes is that the number of rows（columns） in a disk array does not be restricted by t...A family of array codes with a maximum distance separable（MDS） property, named L codes, is proposed. The greatest strength of L codes is that the number of rows（columns） in a disk array does not be restricted by the prime number, and more disks can be dynamically appended in a running storage system. L codes can tolerate at least two disk erasures and some sector loss simultaneously, and can tolerate multiple disk erasures（greater than or equal to three） under a certain condition. Because only XOR operations are needed in the process of encoding and decoding, L codes have very high computing efficiency which is roughly equivalent to X codes. Analysis shows that L codes are particularly suitable for large-scale storage systems.展开更多
In this work,the dynamics and operation of the totally reboiled reactive distillation columns are visualized in terms of transfer function based process models.This kind of processes is found to be characterized by un...In this work,the dynamics and operation of the totally reboiled reactive distillation columns are visualized in terms of transfer function based process models.This kind of processes is found to be characterized by underdamped step responses due to the special topological configuration and the intricate interplay between the reaction operation and the separation operation involved.The under-dampness can be substantially alleviated through the tight inventory control of bottom reboiler and this presents beneficial effects to process dynamics and operation.Two totally reboiled reactive distillation columns,separating,respectively,a hypothetical synthesis reaction from reactants A and B to product C,and a real decomposition reaction from 1,4-butanediol to tetrahydrofuran and water,are employed to demonstrate these uncommon behaviors.The results obtained give full support to the above qualitative interpretation.Despite the strong influences of reaction kinetics and thermodynamic properties of the reacting mixtures,the totally reboiled reactive distillation columns are generally considered to present such unique behaviors and require tight inventory control of bottom reboiler to facilitate their control system development.展开更多
The higher-order attraction of pullback attractors for non-autonomous parabolic equations involving Grushin operators is considered. Firstly, the maximum principle is studied.Next, the higher-order integrability of th...The higher-order attraction of pullback attractors for non-autonomous parabolic equations involving Grushin operators is considered. Firstly, the maximum principle is studied.Next, the higher-order integrability of the difference of weak solutions is established. Finally,the higher-order attraction is proved.展开更多
In the present paper we study the maximum dissipative extension of Schrodingeroperator.introduce the generalized indefinite metvic space and get the representation ofmaximum dissipative extension of Schrodinger operat...In the present paper we study the maximum dissipative extension of Schrodingeroperator.introduce the generalized indefinite metvic space and get the representation ofmaximum dissipative extension of Schrodinger operator in natural boundary space.make preparation for the further study longtime chaotic behaxior of infinite dimensiondynamics system in nonlinear Schrodinger equation.展开更多
Compressed air energy storage(CAES)is considered as one of the most promising large scale energy storage technologies for the electrical grid with high penetration of renewable energy.CAES systems are required to oper...Compressed air energy storage(CAES)is considered as one of the most promising large scale energy storage technologies for the electrical grid with high penetration of renewable energy.CAES systems are required to operate under complex conditions because of the pressure change in the air storage chamber and input/output power changes considering the fluctuated renewable generation and the mismatch between energy supply and demand.A dynamic operation configuration was proposed to satisfy the adjustment of off-design conditions of CAES systems and frequency management auxiliary service market.To regulate the inlet pressure of turbines and meet the output power demand for better performance,a thermodynamic model of a CAES discharging system with thermal storage and the pressure control unit(SER)was established.The control strategy of setting adjustment width instead of single instruction curve is proposed.Then,the dynamic operation parameters including pressure,mass flow rate,and exergy change during discharging processes were investigated.The superiority of the control accuracy and efficiency was demonstrated over single throttle valve through valve characterization studies.The SER system improves control accuracy by decoupling pressure and flow rate changes in dynamic operation,solving the problem of difficult control and low accuracy of traditional throttle valves.The expansion tank in SER serves as a pressure buffer and heat exchanger with the environment,reducing energy loss during fluid flow.Furthermore,the effect of the expansion tank volume of switch expansion reduction in exergy destruction were assessed.For a 10 MW/60MWh system with dynamic load to meet the requirements of the unit to participate in the frequency modulation auxiliary service market,the optimal added expansion tank volume is about 70m3.The optimization method of control strategy of SER system is also explored.The proposed optimized SER system of volume and control strategy can smoothly regulate the inlet pressure of the expander.When the adjustment width is 3bar,the frequency is 50%decreased,meanwhile,the on–off action time is more evenness,which ensures the stable and efficient operation of the CAES system and improves the comprehensive performance of the system.展开更多
Dynamic operating envelopes(DOEs),as key enablers to facilitate distributed energy resource(DER)integration,have attracted increasing attention in the past years.However,uncertainties,which may come from load forecast...Dynamic operating envelopes(DOEs),as key enablers to facilitate distributed energy resource(DER)integration,have attracted increasing attention in the past years.However,uncertainties,which may come from load forecasting errors or inaccurate network parameters,have been rarely discussed in DOE calculation,leading to compromised quality of the hosting capacity allocation strategy.This letter studies how to calculate DOEs that are immune to such uncertainties based on a linearised unbalanced three-phase optimal power flow(UTOPF)model.With uncertain parameters constrained by norm balls,formulations for calculating robust DOEs(RDOEs)are presented along with discussions on their tractability.Two cases,including a 2-bus illustrative network and a representative Australian network,are tested to demonstrate the effectiveness and efficiency of the proposed approach.展开更多
An analysis of the different types of interaction taking place during a video-class shows thatcommunicative methods stimulate the students’ language learning.Thus video becomes a useful languagelearning tool.
The performance degradation is a crucial factor affecting the commercialization of proton exchange membrane electrolyzer.However,it is difficult to establish a mechanism model incorporating all degradation categories ...The performance degradation is a crucial factor affecting the commercialization of proton exchange membrane electrolyzer.However,it is difficult to establish a mechanism model incorporating all degradation categories due to their different time and spatial scales.In this paper,the data-driven method is employed to predict the electrolyzer voltage variation over time based on a convolutional neural network-long short term memory(CNNLSTM)model.First,two datasets including constant operation for 1140 h and start-stop load for 660 h are collected from the durability tests.Second,the data-driven models are trained through the experimental data and the model hyper-parameters are optimized.Finally,the electrolyzer degradation in the next few hundred hours is predicted,and the prediction accuracy is compared with other time-series algorithms.The results show that the model can predict the degradation precisely on both datasets,with the R2 higher than 0.98.Compared to con-ventional models,the algorithm shows better fitting characteristic to the experimental data,especially as the prediction time increases.For constant and start-stop operations,the electrolyzers degradate by 4.5%and 2.5%respectively after 1000 h.The proposed method shows great potential for real-time monitoring in the electrolyzer system.展开更多
基金supported by the National Natural Science Foundation of China(NSFC,No.62303031)the Fundamental Research Funds for the Central Universities。
文摘When estimating the capacity of lithium-ion batteries offline or online,it is essential to extract a health feature(HF)that can effectively characterize capacity degradation under both conventional ideal and complex dynamic operating conditions.However,the extraction of most HFs relies on complete charge-discharge cycle data,making them less adaptable to complex dynamic operating conditions.Existing mechanism HFs,while capable of characterizing capacity degradation from a mechanism perspective,suffer from limitations such as insufficient physical model expressiveness,high dimension,and redundancy of the mechanism HF.These issues increase the complexity of subsequent modeling of the relationship between HFs and capacity,thereby restricting their promotion in engineering practice.To meet this gap,this paper proposes a novel mechanism-based HF.Firstly,a multi-physical fields coupling model is developed to describe the interactions between electrochemical,thermal,and aging behaviors of the battery.Secondly,based on the aging mechanism,the accumulated charge of lithium lost during the formation of the solid electrolyte interphase(SEI)film is extracted as HF to provide a more intuitive representation of capacity degradation.Then,to reduce estimation errors caused by considering only a single aging mechanism,multiple representative regression models are employed to establish the mapping relationship between the mechanism HF and capacity,further enhancing the accuracy of final results.Finally,the proposed method is implemented and validated using real battery data under three different types of operating conditions.Experimental results demonstrate that,compared to other commonly used HFs,the proposed HF exhibits significant competitive advantages in handling incomplete cycle data,unknown operating conditions,and capacity estimation models.The minimum estimation error under ideal conditions is 0.0074,and the minimum estimation error under complex dynamic conditions is 0.0268.
基金the National Natural Science Foundation of China(Nos.71731001,61573181,71971114)the Fundamental Research Funds for the Central Universities(No.NS2020045)。
文摘Air traffic controllers face challenging initiatives due to uncertainty in air traffic.One way to support their initiatives is to identify similar operation scenes.Based on the operation characteristics of typical busy area control airspace,an complexity measurement indicator system is established.We find that operation in area sector is characterized by aggregation and continuity,and that dimensionality and information redundancy reduction are feasible for dynamic operation data base on principle components.Using principle components,discrete features and time series features are constructed.Based on Gaussian kernel function,Euclidean distance and dynamic time warping(DTW)are used to measure the similarity of the features.Then the matrices of similarity are input in Spectral Clustering.The clustering results show that similar scenes of trend are not ideal and similar scenes of modes are good base on the indicator system.Finally,actual vertical operation decisions for area sector and results of identification are compared,which are visualized by metric multidimensional scaling(MDS)plots.We find that identification results can well reflect the operation at peak hours,but controllers make different decisions under the similar conditions before dawn.The compliance rate of busy operation mode and division decisions at peak hours is 96.7%.The results also show subjectivity of actual operation and objectivity of identification.In most scenes,we observe that similar air traffic activities provide regularity for initiatives,validating the potential of this approach for initiatives and other artificial intelligence support.
基金Project(2008AA09Z201)supported by the National High Technology Research and Development Program of China
文摘The armored cable used in a deep-sea remotely operated vehicle(ROV) may undergo large displacement motion when subjected to dynamic actions of ship heave motion and ocean current. A novel geometrically exact finite element model for two-dimensional dynamic analysis of armored cable is presented. This model accounts for the geometric nonlinearities of large displacement of the armored cable, and effects of axial load and bending stiffness. The governing equations are derived by consistent linearization and finite element discretization of the total weak form of the armored cable system, and solved by the Newmark time integration method. To make the solution procedure avoid falling into the local extreme points, a simple adaptive stepping strategy is proposed. The presented model is validated via actual measured data. Results for dynamic configurations, motion and tension of both ends of the armored cable, and resonance-zone are presented for two numerical cases, including the dynamic analysis under the case of only ship heave motion and the case of joint action of ship heave motion and ocean current. The dynamics analysis can provide important reference for the design or product selection of the armored cable in a deep-sea ROV system so as to improve the safety of its marine operation under the sea state of 4 or above.
基金Supported by the National Natural Science Foundation of China(61333010,61134007and 21276078)“Shu Guang”project of Shanghai Municipal Education Commission,the Research Talents Startup Foundation of Jiangsu University(15JDG139)China Postdoctoral Science Foundation(2016M591783)
文摘Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms.
基金the Aviation Science Foundation of China(No.20151067003)。
文摘In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region,the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper.The structure tensor feature space is established to represent the local features of damage images.It makes different damage images have the same feature distribution,and transform varied damage region division into consistent process of feature space division.On this basis,the structure tensor dynamic operator generation method is designed.It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules,in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division.And then the airframe damage region division is realized.The experimental results on different airframe structure damage images show that compared with traditional threshold division method,the proposed method can improve the division quality.The interference of damage adjacent region is eliminated.The information loss caused by over-segmentation is avoided.And it is efficient in operation,and consistent in process.It also has the applicability to different types of structural damage.
文摘In this paper we introduce the concept of tensor sum semigroups. Also we have given the examples of tensor sum operators which induce dynamical system on weighted locally convex function spaces.
基金Supported by the National Natural Science Foundation of China(60073043,70071042,60133010)
文摘Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has some shortcoming s, in this paper, we proposed a new method using tree structure to express the relationship of solutions. Experiments prove that the method can reach the Pare-to front, retain the diversity of the population, and use less time.
文摘A new dynamic model identification method is developed for continuous-time series analysis and forward prediction applications. The quantum of data is defined over moving time intervals in sliding window coordinates for compressing the size of stored data while retaining the resolution of information. Quantum vectors are introduced as the basis of a linear space for defining a Dynamic Quantum Operator (DQO) model of the system defined by its data stream. The transport of the quantum of compressed data is modeled between the time interval bins during the movement of the sliding time window. The DQO model is identified from the samples of the real-time flow of data over the sliding time window. A least-square-fit identification method is used for evaluating the parameters of the quantum operator model, utilizing the repeated use of the sampled data through a number of time steps. The method is tested to analyze, and forward-predict air temperature variations accessed from weather data as well as methane concentration variations obtained from measurements of an operating mine. The results show efficient forward prediction capabilities, surpassing those using neural networks and other methods for the same task.
基金supported by the National Natural Science Foundation of China under Grant No.61202250
文摘A family of array codes with a maximum distance separable（MDS） property, named L codes, is proposed. The greatest strength of L codes is that the number of rows（columns） in a disk array does not be restricted by the prime number, and more disks can be dynamically appended in a running storage system. L codes can tolerate at least two disk erasures and some sector loss simultaneously, and can tolerate multiple disk erasures（greater than or equal to three） under a certain condition. Because only XOR operations are needed in the process of encoding and decoding, L codes have very high computing efficiency which is roughly equivalent to X codes. Analysis shows that L codes are particularly suitable for large-scale storage systems.
基金Supported by The National Natural Science Foundation of China(21076015,21376018,and 21576014)The Fundamental Research Funds for the Central Universities(ZY1503)
文摘In this work,the dynamics and operation of the totally reboiled reactive distillation columns are visualized in terms of transfer function based process models.This kind of processes is found to be characterized by underdamped step responses due to the special topological configuration and the intricate interplay between the reaction operation and the separation operation involved.The under-dampness can be substantially alleviated through the tight inventory control of bottom reboiler and this presents beneficial effects to process dynamics and operation.Two totally reboiled reactive distillation columns,separating,respectively,a hypothetical synthesis reaction from reactants A and B to product C,and a real decomposition reaction from 1,4-butanediol to tetrahydrofuran and water,are employed to demonstrate these uncommon behaviors.The results obtained give full support to the above qualitative interpretation.Despite the strong influences of reaction kinetics and thermodynamic properties of the reacting mixtures,the totally reboiled reactive distillation columns are generally considered to present such unique behaviors and require tight inventory control of bottom reboiler to facilitate their control system development.
基金Supported by Tian Yuan Fund of Mathematics(Grant No.11326100)the Natural Science Fundation of Gansu Province(Grant No.145RJZA033)
文摘The higher-order attraction of pullback attractors for non-autonomous parabolic equations involving Grushin operators is considered. Firstly, the maximum principle is studied.Next, the higher-order integrability of the difference of weak solutions is established. Finally,the higher-order attraction is proved.
文摘In the present paper we study the maximum dissipative extension of Schrodingeroperator.introduce the generalized indefinite metvic space and get the representation ofmaximum dissipative extension of Schrodinger operator in natural boundary space.make preparation for the further study longtime chaotic behaxior of infinite dimensiondynamics system in nonlinear Schrodinger equation.
基金The National Natural Science Foundation of China(52376040)Nanjing New Research and Development Institutions Joint Technology Research Project(202304008)+2 种基金Beijing Nova Program(2023048447),National Key R&D Program of China(2023YFB2406500)The International Partnership Program of Chinese Academy of Sciences(Grant No.117GJHZ2023093MI,117GJHZ2024010MI)“Transformational Technologies for Clean Energy and Demonstration”,Strategic Priority Research Program of the Chinese Academy of Sciences,Grant No.XDAXDA0400100.
文摘Compressed air energy storage(CAES)is considered as one of the most promising large scale energy storage technologies for the electrical grid with high penetration of renewable energy.CAES systems are required to operate under complex conditions because of the pressure change in the air storage chamber and input/output power changes considering the fluctuated renewable generation and the mismatch between energy supply and demand.A dynamic operation configuration was proposed to satisfy the adjustment of off-design conditions of CAES systems and frequency management auxiliary service market.To regulate the inlet pressure of turbines and meet the output power demand for better performance,a thermodynamic model of a CAES discharging system with thermal storage and the pressure control unit(SER)was established.The control strategy of setting adjustment width instead of single instruction curve is proposed.Then,the dynamic operation parameters including pressure,mass flow rate,and exergy change during discharging processes were investigated.The superiority of the control accuracy and efficiency was demonstrated over single throttle valve through valve characterization studies.The SER system improves control accuracy by decoupling pressure and flow rate changes in dynamic operation,solving the problem of difficult control and low accuracy of traditional throttle valves.The expansion tank in SER serves as a pressure buffer and heat exchanger with the environment,reducing energy loss during fluid flow.Furthermore,the effect of the expansion tank volume of switch expansion reduction in exergy destruction were assessed.For a 10 MW/60MWh system with dynamic load to meet the requirements of the unit to participate in the frequency modulation auxiliary service market,the optimal added expansion tank volume is about 70m3.The optimization method of control strategy of SER system is also explored.The proposed optimized SER system of volume and control strategy can smoothly regulate the inlet pressure of the expander.When the adjustment width is 3bar,the frequency is 50%decreased,meanwhile,the on–off action time is more evenness,which ensures the stable and efficient operation of the CAES system and improves the comprehensive performance of the system.
基金supported by the CSIRO Strategic Project on Network Optimisation&Decarbonisation(No.OD-107890).
文摘Dynamic operating envelopes(DOEs),as key enablers to facilitate distributed energy resource(DER)integration,have attracted increasing attention in the past years.However,uncertainties,which may come from load forecasting errors or inaccurate network parameters,have been rarely discussed in DOE calculation,leading to compromised quality of the hosting capacity allocation strategy.This letter studies how to calculate DOEs that are immune to such uncertainties based on a linearised unbalanced three-phase optimal power flow(UTOPF)model.With uncertain parameters constrained by norm balls,formulations for calculating robust DOEs(RDOEs)are presented along with discussions on their tractability.Two cases,including a 2-bus illustrative network and a representative Australian network,are tested to demonstrate the effectiveness and efficiency of the proposed approach.
文摘An analysis of the different types of interaction taking place during a video-class shows thatcommunicative methods stimulate the students’ language learning.Thus video becomes a useful languagelearning tool.
基金financial supports of National Key Research and Development Program of China(No.2021YFB4000100)National Natural Science Foundation of China(No.52322604).
文摘The performance degradation is a crucial factor affecting the commercialization of proton exchange membrane electrolyzer.However,it is difficult to establish a mechanism model incorporating all degradation categories due to their different time and spatial scales.In this paper,the data-driven method is employed to predict the electrolyzer voltage variation over time based on a convolutional neural network-long short term memory(CNNLSTM)model.First,two datasets including constant operation for 1140 h and start-stop load for 660 h are collected from the durability tests.Second,the data-driven models are trained through the experimental data and the model hyper-parameters are optimized.Finally,the electrolyzer degradation in the next few hundred hours is predicted,and the prediction accuracy is compared with other time-series algorithms.The results show that the model can predict the degradation precisely on both datasets,with the R2 higher than 0.98.Compared to con-ventional models,the algorithm shows better fitting characteristic to the experimental data,especially as the prediction time increases.For constant and start-stop operations,the electrolyzers degradate by 4.5%and 2.5%respectively after 1000 h.The proposed method shows great potential for real-time monitoring in the electrolyzer system.
