Prediction of power output plays a vital role in the installation and operation of photovoltaic modules.In this paper,two photovoltaic module technologies,amorphous silicon and copper indium gallium selenide installed...Prediction of power output plays a vital role in the installation and operation of photovoltaic modules.In this paper,two photovoltaic module technologies,amorphous silicon and copper indium gallium selenide installed outdoors on the rooftop of the University of Dodoma,located at 6.5738°S and 36.2631°E in Tanzania,were used to record the power output during the winter season.The average data of ambient temperature,module temperature,solar irradiance,relative humidity,and wind speed recorded is used to predict the power output using a non-linear autoregressive artificial neural network.We consider the Levenberg-Marquardt optimization,Bayesian regularization,resilient propagation,and scaled conjugate gradient algorithms to understand their abilities in training,testing and validating the data.A comparison with reference to the performance indices:coefficient of determination,root mean square error,mean absolute percentage error,and mean absolute bias error is drawn for both modules.According to the findings of our investigation,the predicted results are in good agreement with the experimental results.All the algorithms performed better,and the predicted power out of both modules using the Bayesian regularization algorithm is observed to exhibit good processing capabilities compared to the other three algorithms that are evident from the measured performance indices.展开更多
In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable...In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.展开更多
Wave energy is an important renewable energy source. Previous studies of wave energy conversion(WEC) have focused on the maximum power take-off(PTO) techniques of a single machine. However, there is a lack of research...Wave energy is an important renewable energy source. Previous studies of wave energy conversion(WEC) have focused on the maximum power take-off(PTO) techniques of a single machine. However, there is a lack of research on the energy and power quality of wave farm systems. Owing to the pulsating nature of ocean waves and popular PTO devices, the generated electrical power suffers from severe fluctuations. Existing solutions require extra energy storage and overrated power converters for wave power integration. In this study, we developed a master-slave wave farm system with rotor inertia energy storage; this system delivers self-smoothed power output to the grid and reduces the number of converters. Two control methods based on the moving average filter(MAF) and energy filter(EF) are proposed to smooth the output power of wave farms. RTDS simulations show that the proposed systems and control methods facilitate simple and smooth grid integration of wave energy.展开更多
The location of wind turbines on a continuous hilly terrain has an influence on its power outputs.A CFDbased approach is developed to investigate the complex aerodynamic interference between two wind turbines and the ...The location of wind turbines on a continuous hilly terrain has an influence on its power outputs.A CFDbased approach is developed to investigate the complex aerodynamic interference between two wind turbines and the hilly terrain.In this approach,a new three-dimensional model of hilly terrain is established to analyze its viscous effect,and a wind shear is modelled through logarithmic function.They are coupled into the aerodynamics of wind turbine based on“FLUENT”software.Then we apply the proposed method to the NREL Phase VI wind turbines and compare with an experiment in the atmospheric boundary layer(ABL)wind tunnel to validate its accuracy.The simulation also investigates the power outputs of wind turbines on the flat ground and the continuous hilly terrain by changing the location of the wind turbine related to the hilly terrain and the shape of the 1st hill.The results show that the wind turbine located on the top of the 2nd hill has the maximum power;and that when the wind turbine is located on the downstream of the hill,the stall zone should be avoided,and the power of the wind turbine located on the side of the hill is higher than that of the wind turbine located on the front and rear of the hilly terrain.展开更多
The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward...The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.展开更多
Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the b...Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the blurred features of defect images,the current defect recognition algorithm has poor fine-grained recognition ability.Visual attention can achieve fine-grained recognition with its abil-ity to model long-range dependencies while introducing extra computational complexity,especially for multi-head attention in vision transformer structures.Under these circumstances,this paper proposes a self-reduction multi-head attention module that can reduce computational complexity and be easily combined with a Convolutional Neural Network(CNN).In this manner,local and global fea-tures can be calculated simultaneously in our proposed structure,aiming to improve the defect recognition performance.Specifically,the proposed self-reduction multi-head attention can reduce redundant parameters,thereby solving the problem of limited computational resources.Experimental results were obtained based on the defect dataset collected from the substation.The results demonstrated the efficiency and superiority of the proposed method over other advanced algorithms.展开更多
Quantum interferometric power(IP), a discordlike measure, plays an important role in quantum metrology. We study the dynamics of IP for two-qubit X-shape states under different noisy environments. Our study shows that...Quantum interferometric power(IP), a discordlike measure, plays an important role in quantum metrology. We study the dynamics of IP for two-qubit X-shape states under different noisy environments. Our study shows that IP exhibits sudden change, and one side quantum channel is enough for the occurrence of a sudden change of IP. In particular, we show that the initial state having no sudden change of quantum discord exhibits a sudden change of IP under the dynamics of amplitude noise, but the converse is not true. Besides, we also investigate the dynamics of IP under two different kinds of composite noises. Our results also confirm that sudden change of IP occurs under such composite noises.展开更多
Aqueous Ni-Zn microbatteries are safe,reliable and inexpensive but notoriously suffer from inadequate energy and power densities.Herein,we present a novel mechanism of superoxide-activated Ni substrate that realizes t...Aqueous Ni-Zn microbatteries are safe,reliable and inexpensive but notoriously suffer from inadequate energy and power densities.Herein,we present a novel mechanism of superoxide-activated Ni substrate that realizes the redox reaction featuring three-electron transfers(Ni↔Ni3+).The superoxide activates the direct redox reaction between Ni substrate and KNiO_(2)by lowering the reaction Gibbs free energy,supported by in-situ Raman and density functional theory simulations.The prepared chronopotentiostatic superoxidation-activated Ni(CPS-Ni)electrodes exhibit an ultrahigh capacity of 3.21 mAh cm^(-2)at the current density of 5 mA cm^(-2),nearly 8 times that of traditional one-electron processes electrodes.Even under the ultrahigh 200 mA cm^(-2)current density,the CPS-Ni electrodes show 86.4%capacity retention with a Columbic efficiency of 99.2%after 10,000 cycles.The CPS-Ni||Zn microbattery achieves an exceptional energy density of 6.88 mWh cm^(-2)and power density of 339.56 mW cm^(-2).Device demonstration shows that the power source can continuously operate for more than 7 days in powering the sensing and computation intensive practical application of photoplethysmographic waveform monitoring.This work paves the way to the development of multi-electron transfer mechanisms for advanced aqueous Ni-Zn batteries with high capacity and long lifetime.展开更多
In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allo...In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allowing user equipment(UE)of terrestrial networks to share frequencies with satellite networks.In order to protect the satellite terminal(ST),the base station(BS)needs to control the transmit power and frequency resources of the UE.The optimization problem involves maximizing the achievable throughput while satisfying the interference protection constraints of the ST and the quality of service(QoS)of the UE.However,this problem is highly nonconvex,and we decompose it into power allocation and frequency resource scheduling subproblems.In the power allocation subproblem,we propose a power allocation algorithm based on interference probability(PAIP)to address channel uncertainty.We obtain the suboptimal power allocation solution through iterative optimization.In the frequency resource scheduling subproblem,we develop a heuristic algorithm to handle the non-convexity of the problem.The simulation results show that the combination of power allocation and frequency resource scheduling algorithms can improve spectrum utilization.展开更多
This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power pro...This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power production to enhance its operational relia-bility.However,stochastic environmental conditions often result in partial shading conditions and nonuniform thermal distribution across the PV-TEG modules,which negatively affect the output characteristics of the system,thus presenting a significant challenge to maintaining their optimal performance.To address these challenges,a novel fitness-distance-balance-based beluga whale optimization(FDBBWO)strategy has been devised for maximizing the power output of the PV-TEG hybrid system under dynamic operation scenar-ios.A broader spectrum of complex and authentic operational contexts has been considered in case studies to examine the effectiveness and feasibility of FDBBWO.For this,real-world datasets collected from different seasons in Hong Kong have been used to validate the practical viability of the proposed strategy.Simulation results reveal that the FDBBWO based maximum power point tracking technique outperforms its competing methods by achieving the highest energy output,with a remarkable increase of up to 134.25%with minimal power fluctuations.For instance,the energy obtained by FDBBWO is 47.45%and 58.34%higher than BWO and perturb and observe methods,respectively,in the winter season.展开更多
The electromagnetic wave propagations and their coupling characteristics in magnetized plasma near the antenna of ion cyclotron range of frequencies(ICRF)is studied based on self-developed 3DFEM-IA code.This code effe...The electromagnetic wave propagations and their coupling characteristics in magnetized plasma near the antenna of ion cyclotron range of frequencies(ICRF)is studied based on self-developed 3DFEM-IA code.This code effectively resolves the three-dimensional(3D)geometry and the electromagnetic field using the finite element method.Our findings reveal that the distributions of electromagnetic fields and energy flow density significantly depend on the antenna phases,surface current density on the antenna straps,and background plasma density.Notably,the non-uniform surface current density on the antenna straps,resulting from the presence of induced currents,contributes to a reduction in coupling power within the edge plasma.Furthermore,the calculated coupling impedance increases with plasma density,corroborating well with experimental measurements.展开更多
In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route...In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route distribution. However, existing routing algorithms do not take into account the degree of importance of services, thereby leading to load unbalancing and increasing the risks of services and networks. A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems. First, the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices, service load, and service characteristics. Second, service weights are determined with modified relative entropy TOPSIS method, and a balanced service routing determination algorithm is proposed. Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.展开更多
Cognitive radio allows Secondary Users （SUs） to dynamically use the spectrum resource licensed to Prirmry Users （PUs）, and significantly improves the efficiency of spectrum utilization and is viewed as a promising...Cognitive radio allows Secondary Users （SUs） to dynamically use the spectrum resource licensed to Prirmry Users （PUs）, and significantly improves the efficiency of spectrum utilization and is viewed as a promising technology. In cognitive radio networks, the problem of power control is an important issue. In this paper, we mainly focus on the problem of power control for fading channels in cognitive radio networks. The spectrum sharing underlay scenario is considered, where SUs are allowed to coexist with PUs on the condition that the outage probability of PUs is below the maximum outage probability threshold limitation due to the interference caused by SUs. Moreover, besides the outage probability threshold which is defined to protect the performance of PUs, we also consider the maximum transmit power constraints for each SU. With such a setup, we emphasize the problem of power control to minimize the outage probability of each SU in fading channels. Then, based on the statistical information of the fading channel, the closed expression for outage probability is given in fading channels. The Dual-Iteration Power Control （DIPC） algorithm is also proposed to minimize the outage probability based on Perron-Frobenius theory and gradient descent method under the constraint condition. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.展开更多
To predict the performance of multi-direction piezoelectric vibration energy harvester,an equation for calculating its output power is obtained based on elastic mechanics theory and piezoelectricity theory.Experiments...To predict the performance of multi-direction piezoelectric vibration energy harvester,an equation for calculating its output power is obtained based on elastic mechanics theory and piezoelectricity theory.Experiments are performed to verify theoretical analysis.When the excitation direction is along Y direction,a maximal output power about 0.139 mW can be harvested at a resistive load of 65kΩ and an excitation frequency of 136 Hz.Theoretical analysis agrees well with experimental results.Furthermore,the performance of multi-direction vibration energy harvester is experimentally tested.The results show that the multi-direction vibration energy harvester can harvest perfect energy as the excitation direction changes in XY plane,YZ plane,XZ plane and body diagonal plane of the harvester.展开更多
ASEAN is an interesting case study of regional power connectivity in Asia and the Pacific due to its geographic location and ongoing power connectivity within and beyond ASEAN.This paper reviews ASEAN’s power connect...ASEAN is an interesting case study of regional power connectivity in Asia and the Pacific due to its geographic location and ongoing power connectivity within and beyond ASEAN.This paper reviews ASEAN’s power connectivity within ASEAN and between ASEAN and its neighbours(hereafter ASEAN connectivity).Through literature survey,it identifies challenges to the ASEAN connectivity from political,legal,economic and technical perspectives.Based on these analyses,it then explores what,how and when regional cooperation may be able to facilitate ASEAN power connectivity.展开更多
The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind powe...The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind power at each moment;however,they ignore the daily output characteristics and are unable to consider both modeling accuracy and efficiency.To resolve this problem,a wind power time series simulation model based on typical daily output processes and Markov algorithm is proposed.First,a typical daily output process classification method based on time series similarity and modified K-means clustering algorithm is presented.Second,considering the typical daily output processes as status variables,a wind power time series simulation model based on Markov algorithm is constructed.Finally,a case is analyzed based on the measured data of a wind farm in China.The proposed model is then compared with traditional methods to verify its effectiveness and applicability.The comparison results indicate that the statistical characteristics,probability distributions,and autocorrelation characteristics of the wind power time series generated by the proposed model are better than those of the traditional methods.Moreover,modeling efficiency considerably improves.展开更多
The superconducting outsert of the 40 T hybrid-magnet in High Magnetic Field Laboratory （HMFL） of Chinese Academy of Sciences （CAS） requires a highly stabilized power supply. In this paper, two kinds of power supp...The superconducting outsert of the 40 T hybrid-magnet in High Magnetic Field Laboratory （HMFL） of Chinese Academy of Sciences （CAS） requires a highly stabilized power supply. In this paper, two kinds of power supply design are briefly presented and both advantages and disadvantages are analyzed. In order to overcome the drawbacks of switching power supply, a series regulated active filter is adopted and a new design is proposed which ensures cooperative relationship between the feedback control loops of the switching converter and the series regulated active filter. Besides, unlike the traditional switching power supply, which can generate positive voltage only, this new design can also generate negative voltage which is needed in the quench protection for the superconducting magnet. In order to demonstrate the effectiveness of the methodology, a low-power prototype has been accomplished. The simulation and experiment results show that the power supply achieves high precision under the combined action of two feedback control loops. The peak-to-peak amplitude of the output ripple voltage of the prototype is 0.063%, while the peak-to-peak amplitude of the output ripple current is 120 ppm.展开更多
Thermal power plant is one of the important thermodynamic devices, which is very common in all kinds of power generation systems. In this paper, we use a new concept, entransy loss, as well as exergy destruction, to a...Thermal power plant is one of the important thermodynamic devices, which is very common in all kinds of power generation systems. In this paper, we use a new concept, entransy loss, as well as exergy destruction, to analyze the single reheating Rankine cycle unit and the single stage steam extraction regenerative Rankine cycle unit in power plants. This is the first time that the concept of entransy loss is applied to the analysis of the power plant Rankine cycles with reheating and steam extraction regeneration. In order to obtain the maximum output power, the operating conditions under variant vapor mass flow rates are optimized numerically, as well as the combustion temperatures and the off-design flow rates of the flue gas. The relationship between the output power and the exergy destruction rate and that between the output power and the entransy loss rate are discussed. It is found that both the minimum exergy destruction rate and the maximum entransy loss rate lead to the maximum output power when the combustion temperature and heat capacity flow rate of the flue gas are prescribed. Unlike the minimum exergy destruction rate, the maximum entransy loss rate is related to the maximum output power when the highest temperature and heat capacity flow rate of the flue gas are not prescribed.展开更多
基金the University of Dodoma for supporting this work
文摘Prediction of power output plays a vital role in the installation and operation of photovoltaic modules.In this paper,two photovoltaic module technologies,amorphous silicon and copper indium gallium selenide installed outdoors on the rooftop of the University of Dodoma,located at 6.5738°S and 36.2631°E in Tanzania,were used to record the power output during the winter season.The average data of ambient temperature,module temperature,solar irradiance,relative humidity,and wind speed recorded is used to predict the power output using a non-linear autoregressive artificial neural network.We consider the Levenberg-Marquardt optimization,Bayesian regularization,resilient propagation,and scaled conjugate gradient algorithms to understand their abilities in training,testing and validating the data.A comparison with reference to the performance indices:coefficient of determination,root mean square error,mean absolute percentage error,and mean absolute bias error is drawn for both modules.According to the findings of our investigation,the predicted results are in good agreement with the experimental results.All the algorithms performed better,and the predicted power out of both modules using the Bayesian regularization algorithm is observed to exhibit good processing capabilities compared to the other three algorithms that are evident from the measured performance indices.
基金State Grid Jiangsu Electric Power Co.,Ltd(JF2020001)National Key Technology R&D Program of China(2017YFB0903300)State Grid Corporation of China(521OEF17001C).
文摘In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.
基金supported by EPSRC under Grant EP/ L017725/1 and Grant EP/N032888/1
文摘Wave energy is an important renewable energy source. Previous studies of wave energy conversion(WEC) have focused on the maximum power take-off(PTO) techniques of a single machine. However, there is a lack of research on the energy and power quality of wave farm systems. Owing to the pulsating nature of ocean waves and popular PTO devices, the generated electrical power suffers from severe fluctuations. Existing solutions require extra energy storage and overrated power converters for wave power integration. In this study, we developed a master-slave wave farm system with rotor inertia energy storage; this system delivers self-smoothed power output to the grid and reduces the number of converters. Two control methods based on the moving average filter(MAF) and energy filter(EF) are proposed to smooth the output power of wave farms. RTDS simulations show that the proposed systems and control methods facilitate simple and smooth grid integration of wave energy.
基金supported by the Natural Science Foundation of Jiangsu Province (No. BK20161537)National Science Key Laboratory Foundation(No.6142220180202)+1 种基金Rotor Aerodynamics Key Laboratory Foundation (No.RAL20180303-1)National Natural Science Foundation of China(No.11502105).
文摘The location of wind turbines on a continuous hilly terrain has an influence on its power outputs.A CFDbased approach is developed to investigate the complex aerodynamic interference between two wind turbines and the hilly terrain.In this approach,a new three-dimensional model of hilly terrain is established to analyze its viscous effect,and a wind shear is modelled through logarithmic function.They are coupled into the aerodynamics of wind turbine based on“FLUENT”software.Then we apply the proposed method to the NREL Phase VI wind turbines and compare with an experiment in the atmospheric boundary layer(ABL)wind tunnel to validate its accuracy.The simulation also investigates the power outputs of wind turbines on the flat ground and the continuous hilly terrain by changing the location of the wind turbine related to the hilly terrain and the shape of the 1st hill.The results show that the wind turbine located on the top of the 2nd hill has the maximum power;and that when the wind turbine is located on the downstream of the hill,the stall zone should be avoided,and the power of the wind turbine located on the side of the hill is higher than that of the wind turbine located on the front and rear of the hilly terrain.
基金funded by the State Grid Science and Technology Project“Research on Key Technologies for Prediction and Early Warning of Large-Scale Offshore Wind Power Ramp Events Based on Meteorological Data Enhancement”(4000-202318098A-1-1-ZN).
文摘The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.
基金supported in part by Major Program of the National Natural Science Foundation of China under Grant 62127803.
文摘Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the blurred features of defect images,the current defect recognition algorithm has poor fine-grained recognition ability.Visual attention can achieve fine-grained recognition with its abil-ity to model long-range dependencies while introducing extra computational complexity,especially for multi-head attention in vision transformer structures.Under these circumstances,this paper proposes a self-reduction multi-head attention module that can reduce computational complexity and be easily combined with a Convolutional Neural Network(CNN).In this manner,local and global fea-tures can be calculated simultaneously in our proposed structure,aiming to improve the defect recognition performance.Specifically,the proposed self-reduction multi-head attention can reduce redundant parameters,thereby solving the problem of limited computational resources.Experimental results were obtained based on the defect dataset collected from the substation.The results demonstrated the efficiency and superiority of the proposed method over other advanced algorithms.
基金Project supported by the National Natural Science Foundations of China (Grant Nos. 11675119,12275136,and 12075001)the Nankai Zhide Foundations。
文摘Quantum interferometric power(IP), a discordlike measure, plays an important role in quantum metrology. We study the dynamics of IP for two-qubit X-shape states under different noisy environments. Our study shows that IP exhibits sudden change, and one side quantum channel is enough for the occurrence of a sudden change of IP. In particular, we show that the initial state having no sudden change of quantum discord exhibits a sudden change of IP under the dynamics of amplitude noise, but the converse is not true. Besides, we also investigate the dynamics of IP under two different kinds of composite noises. Our results also confirm that sudden change of IP occurs under such composite noises.
基金supported by InnoHK Project at Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE)City University of Hong Kong (7006108)。
文摘Aqueous Ni-Zn microbatteries are safe,reliable and inexpensive but notoriously suffer from inadequate energy and power densities.Herein,we present a novel mechanism of superoxide-activated Ni substrate that realizes the redox reaction featuring three-electron transfers(Ni↔Ni3+).The superoxide activates the direct redox reaction between Ni substrate and KNiO_(2)by lowering the reaction Gibbs free energy,supported by in-situ Raman and density functional theory simulations.The prepared chronopotentiostatic superoxidation-activated Ni(CPS-Ni)electrodes exhibit an ultrahigh capacity of 3.21 mAh cm^(-2)at the current density of 5 mA cm^(-2),nearly 8 times that of traditional one-electron processes electrodes.Even under the ultrahigh 200 mA cm^(-2)current density,the CPS-Ni electrodes show 86.4%capacity retention with a Columbic efficiency of 99.2%after 10,000 cycles.The CPS-Ni||Zn microbattery achieves an exceptional energy density of 6.88 mWh cm^(-2)and power density of 339.56 mW cm^(-2).Device demonstration shows that the power source can continuously operate for more than 7 days in powering the sensing and computation intensive practical application of photoplethysmographic waveform monitoring.This work paves the way to the development of multi-electron transfer mechanisms for advanced aqueous Ni-Zn batteries with high capacity and long lifetime.
基金funded by State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster under Grant MS01240103the National Natural Science Foundation of China under Grant 62071146National 2011 Collaborative Innovation Center of Wireless Communication Technologies under Grant 2242022k60006.
文摘In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allowing user equipment(UE)of terrestrial networks to share frequencies with satellite networks.In order to protect the satellite terminal(ST),the base station(BS)needs to control the transmit power and frequency resources of the UE.The optimization problem involves maximizing the achievable throughput while satisfying the interference protection constraints of the ST and the quality of service(QoS)of the UE.However,this problem is highly nonconvex,and we decompose it into power allocation and frequency resource scheduling subproblems.In the power allocation subproblem,we propose a power allocation algorithm based on interference probability(PAIP)to address channel uncertainty.We obtain the suboptimal power allocation solution through iterative optimization.In the frequency resource scheduling subproblem,we develop a heuristic algorithm to handle the non-convexity of the problem.The simulation results show that the combination of power allocation and frequency resource scheduling algorithms can improve spectrum utilization.
基金supported by National Natural Science Foundation of China(62263014)Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443).
文摘This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power production to enhance its operational relia-bility.However,stochastic environmental conditions often result in partial shading conditions and nonuniform thermal distribution across the PV-TEG modules,which negatively affect the output characteristics of the system,thus presenting a significant challenge to maintaining their optimal performance.To address these challenges,a novel fitness-distance-balance-based beluga whale optimization(FDBBWO)strategy has been devised for maximizing the power output of the PV-TEG hybrid system under dynamic operation scenar-ios.A broader spectrum of complex and authentic operational contexts has been considered in case studies to examine the effectiveness and feasibility of FDBBWO.For this,real-world datasets collected from different seasons in Hong Kong have been used to validate the practical viability of the proposed strategy.Simulation results reveal that the FDBBWO based maximum power point tracking technique outperforms its competing methods by achieving the highest energy output,with a remarkable increase of up to 134.25%with minimal power fluctuations.For instance,the energy obtained by FDBBWO is 47.45%and 58.34%higher than BWO and perturb and observe methods,respectively,in the winter season.
基金Project supported by the National MCF Energy Research and Development Program(Grant No.2022YFE03190100)the National Natural Science Foundation of China(Grant Nos.12422513,12105035,and U21A20438)the Xiaomi Young Talents Program。
文摘The electromagnetic wave propagations and their coupling characteristics in magnetized plasma near the antenna of ion cyclotron range of frequencies(ICRF)is studied based on self-developed 3DFEM-IA code.This code effectively resolves the three-dimensional(3D)geometry and the electromagnetic field using the finite element method.Our findings reveal that the distributions of electromagnetic fields and energy flow density significantly depend on the antenna phases,surface current density on the antenna straps,and background plasma density.Notably,the non-uniform surface current density on the antenna straps,resulting from the presence of induced currents,contributes to a reduction in coupling power within the edge plasma.Furthermore,the calculated coupling impedance increases with plasma density,corroborating well with experimental measurements.
基金supported by the State Grid project which names the simulation and service quality evaluation technology research of power communication network(No.XX71-14-046)
文摘In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route distribution. However, existing routing algorithms do not take into account the degree of importance of services, thereby leading to load unbalancing and increasing the risks of services and networks. A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems. First, the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices, service load, and service characteristics. Second, service weights are determined with modified relative entropy TOPSIS method, and a balanced service routing determination algorithm is proposed. Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.
文摘Cognitive radio allows Secondary Users （SUs） to dynamically use the spectrum resource licensed to Prirmry Users （PUs）, and significantly improves the efficiency of spectrum utilization and is viewed as a promising technology. In cognitive radio networks, the problem of power control is an important issue. In this paper, we mainly focus on the problem of power control for fading channels in cognitive radio networks. The spectrum sharing underlay scenario is considered, where SUs are allowed to coexist with PUs on the condition that the outage probability of PUs is below the maximum outage probability threshold limitation due to the interference caused by SUs. Moreover, besides the outage probability threshold which is defined to protect the performance of PUs, we also consider the maximum transmit power constraints for each SU. With such a setup, we emphasize the problem of power control to minimize the outage probability of each SU in fading channels. Then, based on the statistical information of the fading channel, the closed expression for outage probability is given in fading channels. The Dual-Iteration Power Control （DIPC） algorithm is also proposed to minimize the outage probability based on Perron-Frobenius theory and gradient descent method under the constraint condition. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.
基金Supported by the National Natural Science Foundation of China(51305183)the Qing Lan Project of Jiangsu Provincethe Doctoral Start-up Foundation of Jinling Institute of Technology(jit-b-201412)
文摘To predict the performance of multi-direction piezoelectric vibration energy harvester,an equation for calculating its output power is obtained based on elastic mechanics theory and piezoelectricity theory.Experiments are performed to verify theoretical analysis.When the excitation direction is along Y direction,a maximal output power about 0.139 mW can be harvested at a resistive load of 65kΩ and an excitation frequency of 136 Hz.Theoretical analysis agrees well with experimental results.Furthermore,the performance of multi-direction vibration energy harvester is experimentally tested.The results show that the multi-direction vibration energy harvester can harvest perfect energy as the excitation direction changes in XY plane,YZ plane,XZ plane and body diagonal plane of the harvester.
基金supported by the National Science Foundation of China (71828401,71873029)
文摘ASEAN is an interesting case study of regional power connectivity in Asia and the Pacific due to its geographic location and ongoing power connectivity within and beyond ASEAN.This paper reviews ASEAN’s power connectivity within ASEAN and between ASEAN and its neighbours(hereafter ASEAN connectivity).Through literature survey,it identifies challenges to the ASEAN connectivity from political,legal,economic and technical perspectives.Based on these analyses,it then explores what,how and when regional cooperation may be able to facilitate ASEAN power connectivity.
基金supported by the China Datang Corporation project“Study on the performance improvement scheme of in-service wind farms”,the Fundamental Research Funds for the Central Universities(2020MS021)the Foundation of State Key Laboratory“Real-time prediction of offshore wind power and load reduction control method”(LAPS2020-07).
文摘The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind power at each moment;however,they ignore the daily output characteristics and are unable to consider both modeling accuracy and efficiency.To resolve this problem,a wind power time series simulation model based on typical daily output processes and Markov algorithm is proposed.First,a typical daily output process classification method based on time series similarity and modified K-means clustering algorithm is presented.Second,considering the typical daily output processes as status variables,a wind power time series simulation model based on Markov algorithm is constructed.Finally,a case is analyzed based on the measured data of a wind farm in China.The proposed model is then compared with traditional methods to verify its effectiveness and applicability.The comparison results indicate that the statistical characteristics,probability distributions,and autocorrelation characteristics of the wind power time series generated by the proposed model are better than those of the traditional methods.Moreover,modeling efficiency considerably improves.
基金supported by National Natural Science Foundation of China(No.50977086)
文摘The superconducting outsert of the 40 T hybrid-magnet in High Magnetic Field Laboratory （HMFL） of Chinese Academy of Sciences （CAS） requires a highly stabilized power supply. In this paper, two kinds of power supply design are briefly presented and both advantages and disadvantages are analyzed. In order to overcome the drawbacks of switching power supply, a series regulated active filter is adopted and a new design is proposed which ensures cooperative relationship between the feedback control loops of the switching converter and the series regulated active filter. Besides, unlike the traditional switching power supply, which can generate positive voltage only, this new design can also generate negative voltage which is needed in the quench protection for the superconducting magnet. In order to demonstrate the effectiveness of the methodology, a low-power prototype has been accomplished. The simulation and experiment results show that the power supply achieves high precision under the combined action of two feedback control loops. The peak-to-peak amplitude of the output ripple voltage of the prototype is 0.063%, while the peak-to-peak amplitude of the output ripple current is 120 ppm.
基金Project supported by the National Natural Science Foundation of China(Grant No.51376101)
文摘Thermal power plant is one of the important thermodynamic devices, which is very common in all kinds of power generation systems. In this paper, we use a new concept, entransy loss, as well as exergy destruction, to analyze the single reheating Rankine cycle unit and the single stage steam extraction regenerative Rankine cycle unit in power plants. This is the first time that the concept of entransy loss is applied to the analysis of the power plant Rankine cycles with reheating and steam extraction regeneration. In order to obtain the maximum output power, the operating conditions under variant vapor mass flow rates are optimized numerically, as well as the combustion temperatures and the off-design flow rates of the flue gas. The relationship between the output power and the exergy destruction rate and that between the output power and the entransy loss rate are discussed. It is found that both the minimum exergy destruction rate and the maximum entransy loss rate lead to the maximum output power when the combustion temperature and heat capacity flow rate of the flue gas are prescribed. Unlike the minimum exergy destruction rate, the maximum entransy loss rate is related to the maximum output power when the highest temperature and heat capacity flow rate of the flue gas are not prescribed.
