This paper deals with quasilinear elliptic equations of singular growth like-Δu-uΔ(u^(2))=a(x)u^(-1).We establish the existence of positive solutions for general a(x)∈L^(p)(Ω),p>2,whereΩis a bounded domain inℝ...This paper deals with quasilinear elliptic equations of singular growth like-Δu-uΔ(u^(2))=a(x)u^(-1).We establish the existence of positive solutions for general a(x)∈L^(p)(Ω),p>2,whereΩis a bounded domain inℝ^(N)with N≥1.展开更多
Harnessing solar power is essential for addressing the dual challenges of global warming and the depletion of traditional energy sources.However,the fluctuations and intermittency of photovoltaic(PV)power pose challen...Harnessing solar power is essential for addressing the dual challenges of global warming and the depletion of traditional energy sources.However,the fluctuations and intermittency of photovoltaic(PV)power pose challenges for its extensive incorporation into power grids.Thus,enhancing the precision of PV power prediction is particularly important.Although existing studies have made progress in short-term prediction,issues persist,particularly in the underutilization of temporal features and the neglect of correlations between satellite cloud images and PV power data.These factors hinder improvements in PV power prediction performance.To overcome these challenges,this paper proposes a novel PV power prediction method based on multi-stage temporal feature learning.First,the improved LSTMand SA-ConvLSTMare employed to extract the temporal feature of PV power and the spatial-temporal feature of satellite cloud images,respectively.Subsequently,a novel hybrid attention mechanism is proposed to identify the interplay between the two modalities,enhancing the capacity to focus on the most relevant features.Finally,theTransformermodel is applied to further capture the short-termtemporal patterns and long-term dependencies within multi-modal feature information.The paper also compares the proposed method with various competitive methods.The experimental results demonstrate that the proposed method outperforms the competitive methods in terms of accuracy and reliability in short-term PV power prediction.展开更多
Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,th...Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power prediction.To improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant information.The extracted components as well as the weather data are then input into iTransformer for short-term wind power forecast.The final predicted short-term wind power curve is obtained by combining the predicted components.To improve the model accuracy,IAOA is employed to optimize the hyperparameters of iTransformer.The proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been conducted.Furthermore,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for experiments.Thecomparative results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.展开更多
Texas is the largest state by area in the US after Alaska,and one of the top states in the production and consumption of electricity with many coal-fired plants.Coal-fired power plants emit greater than 70% of polluta...Texas is the largest state by area in the US after Alaska,and one of the top states in the production and consumption of electricity with many coal-fired plants.Coal-fired power plants emit greater than 70% of pollutants in the energy sector.When coal is burned to produce electricity,nitrogen oxides(NO_(x))are released into the air,one of the main pollutants that threaten human health and lead to a large number of premature deaths.The key to effective air quality management is the strict compliance of all plants with emission standards.However,not all Texas coal plants have the environmental equipment to lower pollutant emissions.Nitrogen dioxide(NO2)observations from the TROPOspheric Monitoring Instrument(TROPOMI)were used to evaluate the emissions for Texas power plants.Data from both the Emissions and Generation Resource Integrated Database(EGRID)and the Emissions Database for Global Atmospheric Research(EDGAR)were used to examine emissions.It was found that NOx emissions for Texas power plants range from 1.53 kt/year to 10.99 kt/year,with the Martin Lake,Limestone and Fayette Power Project stations being the top emitters.WA Parish and Martin Lake stations have the strongest NOx fluxes,with both exhibiting significant seasonal variability.Comparisons of bottom-up inventories for EDGAR and EGRID show a high correlation(r=0.956)and a low root mean square error(0.766).A more reasonable control policy would lead to much reduced NOx emissions.展开更多
Quality of Service (QoS) is a key factor in Web service advertising, choosing and runtime monitoring. Web service QoS is multi-faceted, fuzzy and dynamic. Current researches focus on implementation level performance a...Quality of Service (QoS) is a key factor in Web service advertising, choosing and runtime monitoring. Web service QoS is multi-faceted, fuzzy and dynamic. Current researches focus on implementation level performance assurance, ignoring domain specific or application level metrics which are also very important to service users. Industry Web service standards lack QoS expression. The support for QoS based service choice-making is very limited. We proposed an extended Web service QoS model based on configurable fuzzy synthetic evaluation system. Web service QoS is evaluated dynamically according to the service context. A QoS requirement description model is also given for service QoS requirement definition. An interactive Web service choice-making process is described, which takes QoS as a key factor when choosing from functionally equivalent services.展开更多
With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these...With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.展开更多
As a clean and renewable form of energy,photovoltaic(PV)power generation converts solar energy into electrical energy,reducing the consumption of fossil fuels and significantly lowering greenhouse gas emissions.Amidst...As a clean and renewable form of energy,photovoltaic(PV)power generation converts solar energy into electrical energy,reducing the consumption of fossil fuels and significantly lowering greenhouse gas emissions.Amidst the global transition towards cleaner forms of energy,countries all around the world are vigorously developing PV technology.展开更多
Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified ...Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.展开更多
Microwave-assisted mechanical excavation has great application prospects in mines and tunnels,but there are few field experiments on microwave-assisted rock breaking.This paper takes the Sishanling iron mine as the re...Microwave-assisted mechanical excavation has great application prospects in mines and tunnels,but there are few field experiments on microwave-assisted rock breaking.This paper takes the Sishanling iron mine as the research object and adopts the self-developed high-power microwave-induced fracturing test system for hard rock to conduct field experiments of microwave-induced fracturing of iron ore.The heating and reflection evolution characteristics of ore under different microwave parameters(antenna type,power,and working distance)were studied,and the optimal microwave parameters were obtained.Subsequently,the ore was irradiated with the optimal microwave parameters,and the cracking effect of the ore under the action of the high-power open microwave was analyzed.The results show that the reflection coefficient(standing wave ratio)can be rapidly(<5 s)and automatically adjusted below the preset threshold value(1.6)as microwave irradiation is performed.When using a right-angle horn antenna with a working distance of 5 cm,the effect of automatic reflection adjustment reaches the best among other antenna types and working distances.When the working distance is the same,the average temperature of the irradiation surface and the area of the high-temperature area under the action of the two antennas(right-angled and equal-angled horn antenna)are basically the same and decrease with the increase of working distance.The optimal microwave parameters are:a right-angle horn antenna with a working distance of 5 cm.Subsequently,in further experiments,the optimal parameters were used to irradiate for 20 s and 40 s at a microwave power of 60 kW,respectively.The surface damage extended 38 cm×30 cm and 53 cm×30 cm,respectively,and the damage extended to a depth of about 50 cm.The drilling speed was increased by 56.2%and 66.5%,respectively,compared to the case when microwaves were not used.展开更多
Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple stake...Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.展开更多
The supercritical CO_(2)(sCO_(2))power cycle could improve efficiencies for a wide range of thermal power plants.The sCO_(2)turbine generator plays an important role in the sCO_(2)power cycle by directly converting th...The supercritical CO_(2)(sCO_(2))power cycle could improve efficiencies for a wide range of thermal power plants.The sCO_(2)turbine generator plays an important role in the sCO_(2)power cycle by directly converting thermal energy into mechanical work and electric power.The operation of the generator encounters challenges,including high temperature,high pressure,high rotational speed,and other engineering problems,such as leakage.Experimental studies of sCO_(2)turbines are insufficient because of the significant difficulties in turbine manufacturing and system construction.Unlike most experimental investigations that primarily focus on 100 kW‐or MW‐scale power generation systems,we consider,for the first time,a small‐scale power generator using sCO_(2).A partial admission axial turbine was designed and manufactured with a rated rotational speed of 40,000 rpm,and a CO_(2)transcritical power cycle test loop was constructed to validate the performance of our manufactured generator.A resistant gas was proposed in the constructed turbine expander to solve the leakage issue.Both dynamic and steady performances were investigated.The results indicated that a peak electric power of 11.55 kW was achieved at 29,369 rpm.The maximum total efficiency of the turbo‐generator was 58.98%,which was affected by both the turbine rotational speed and pressure ratio,according to the proposed performance map.展开更多
基金Supported by National Science Foundation of China(11971027,12171497)。
文摘This paper deals with quasilinear elliptic equations of singular growth like-Δu-uΔ(u^(2))=a(x)u^(-1).We establish the existence of positive solutions for general a(x)∈L^(p)(Ω),p>2,whereΩis a bounded domain inℝ^(N)with N≥1.
基金supported by the Science and Technology Project of Jiangsu Coastal Power Infrastructure Intelligent Engineering Research Center“Photovoltaic Power Prediction System Driven by Deep Learning and Multi-Source Data Fusion”(F2024-5044).
文摘Harnessing solar power is essential for addressing the dual challenges of global warming and the depletion of traditional energy sources.However,the fluctuations and intermittency of photovoltaic(PV)power pose challenges for its extensive incorporation into power grids.Thus,enhancing the precision of PV power prediction is particularly important.Although existing studies have made progress in short-term prediction,issues persist,particularly in the underutilization of temporal features and the neglect of correlations between satellite cloud images and PV power data.These factors hinder improvements in PV power prediction performance.To overcome these challenges,this paper proposes a novel PV power prediction method based on multi-stage temporal feature learning.First,the improved LSTMand SA-ConvLSTMare employed to extract the temporal feature of PV power and the spatial-temporal feature of satellite cloud images,respectively.Subsequently,a novel hybrid attention mechanism is proposed to identify the interplay between the two modalities,enhancing the capacity to focus on the most relevant features.Finally,theTransformermodel is applied to further capture the short-termtemporal patterns and long-term dependencies within multi-modal feature information.The paper also compares the proposed method with various competitive methods.The experimental results demonstrate that the proposed method outperforms the competitive methods in terms of accuracy and reliability in short-term PV power prediction.
基金supported by Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443)National Natural Science Foundation of China(62263014,52207105)+1 种基金Yunnan Lancang-Mekong International Electric Power Technology Joint Laboratory(202203AP140001)Major Science and Technology Projects in Yunnan Province(202402AG050006).
文摘Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power prediction.To improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant information.The extracted components as well as the weather data are then input into iTransformer for short-term wind power forecast.The final predicted short-term wind power curve is obtained by combining the predicted components.To improve the model accuracy,IAOA is employed to optimize the hyperparameters of iTransformer.The proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been conducted.Furthermore,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for experiments.Thecomparative results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.
基金This work was supported by the Basic Research Top Talent Plan of Lanzhou Jiaotong University(2022JC05).
文摘Texas is the largest state by area in the US after Alaska,and one of the top states in the production and consumption of electricity with many coal-fired plants.Coal-fired power plants emit greater than 70% of pollutants in the energy sector.When coal is burned to produce electricity,nitrogen oxides(NO_(x))are released into the air,one of the main pollutants that threaten human health and lead to a large number of premature deaths.The key to effective air quality management is the strict compliance of all plants with emission standards.However,not all Texas coal plants have the environmental equipment to lower pollutant emissions.Nitrogen dioxide(NO2)observations from the TROPOspheric Monitoring Instrument(TROPOMI)were used to evaluate the emissions for Texas power plants.Data from both the Emissions and Generation Resource Integrated Database(EGRID)and the Emissions Database for Global Atmospheric Research(EDGAR)were used to examine emissions.It was found that NOx emissions for Texas power plants range from 1.53 kt/year to 10.99 kt/year,with the Martin Lake,Limestone and Fayette Power Project stations being the top emitters.WA Parish and Martin Lake stations have the strongest NOx fluxes,with both exhibiting significant seasonal variability.Comparisons of bottom-up inventories for EDGAR and EGRID show a high correlation(r=0.956)and a low root mean square error(0.766).A more reasonable control policy would lead to much reduced NOx emissions.
基金Project supported by the National Natural Science Foundation of China (No. 60503041), the Hi-Tech Research and DevelopmentProgram (863) of China (No. 2004AA104340), the Chinese SemanticGrid Project, and the Science and Technology Commission ofShanghai Municipality (No. 03dz15027), China
文摘Quality of Service (QoS) is a key factor in Web service advertising, choosing and runtime monitoring. Web service QoS is multi-faceted, fuzzy and dynamic. Current researches focus on implementation level performance assurance, ignoring domain specific or application level metrics which are also very important to service users. Industry Web service standards lack QoS expression. The support for QoS based service choice-making is very limited. We proposed an extended Web service QoS model based on configurable fuzzy synthetic evaluation system. Web service QoS is evaluated dynamically according to the service context. A QoS requirement description model is also given for service QoS requirement definition. An interactive Web service choice-making process is described, which takes QoS as a key factor when choosing from functionally equivalent services.
基金supported by the National Science Foundation of China under Grant 62271062 and 62071063by the Zhijiang Laboratory Open Project Fund 2020LCOAB01。
文摘With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.
文摘As a clean and renewable form of energy,photovoltaic(PV)power generation converts solar energy into electrical energy,reducing the consumption of fossil fuels and significantly lowering greenhouse gas emissions.Amidst the global transition towards cleaner forms of energy,countries all around the world are vigorously developing PV technology.
基金supported in part by the Scientific Foundation for Outstanding Young Scientists of Sichuan under Grant No.2021JDJQ0032in part by the National Natural Science Foundation of China under Grant No.52107128in part by the Natural Science Foundation of Sichuan Province under Grant No.2022NSFSC0436.
文摘Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.
基金financial support from the National Natural Science Foundation of China(Grant No.41827806)the Liaoning Provincial Science and Technology Program of China(Grant No.2022JH2/101300109).
文摘Microwave-assisted mechanical excavation has great application prospects in mines and tunnels,but there are few field experiments on microwave-assisted rock breaking.This paper takes the Sishanling iron mine as the research object and adopts the self-developed high-power microwave-induced fracturing test system for hard rock to conduct field experiments of microwave-induced fracturing of iron ore.The heating and reflection evolution characteristics of ore under different microwave parameters(antenna type,power,and working distance)were studied,and the optimal microwave parameters were obtained.Subsequently,the ore was irradiated with the optimal microwave parameters,and the cracking effect of the ore under the action of the high-power open microwave was analyzed.The results show that the reflection coefficient(standing wave ratio)can be rapidly(<5 s)and automatically adjusted below the preset threshold value(1.6)as microwave irradiation is performed.When using a right-angle horn antenna with a working distance of 5 cm,the effect of automatic reflection adjustment reaches the best among other antenna types and working distances.When the working distance is the same,the average temperature of the irradiation surface and the area of the high-temperature area under the action of the two antennas(right-angled and equal-angled horn antenna)are basically the same and decrease with the increase of working distance.The optimal microwave parameters are:a right-angle horn antenna with a working distance of 5 cm.Subsequently,in further experiments,the optimal parameters were used to irradiate for 20 s and 40 s at a microwave power of 60 kW,respectively.The surface damage extended 38 cm×30 cm and 53 cm×30 cm,respectively,and the damage extended to a depth of about 50 cm.The drilling speed was increased by 56.2%and 66.5%,respectively,compared to the case when microwaves were not used.
基金supported in part by National Key R&D Program of China (2021YFB2500600)CAS Youth multi-discipline project (JCTD-2021-09)Strategic Piority Research Program of Chinese Academy of Sciences (XDA28040100)。
文摘Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.
基金National Science Fund for Excellent Young Scholars,Grant/Award Number:52022066。
文摘The supercritical CO_(2)(sCO_(2))power cycle could improve efficiencies for a wide range of thermal power plants.The sCO_(2)turbine generator plays an important role in the sCO_(2)power cycle by directly converting thermal energy into mechanical work and electric power.The operation of the generator encounters challenges,including high temperature,high pressure,high rotational speed,and other engineering problems,such as leakage.Experimental studies of sCO_(2)turbines are insufficient because of the significant difficulties in turbine manufacturing and system construction.Unlike most experimental investigations that primarily focus on 100 kW‐or MW‐scale power generation systems,we consider,for the first time,a small‐scale power generator using sCO_(2).A partial admission axial turbine was designed and manufactured with a rated rotational speed of 40,000 rpm,and a CO_(2)transcritical power cycle test loop was constructed to validate the performance of our manufactured generator.A resistant gas was proposed in the constructed turbine expander to solve the leakage issue.Both dynamic and steady performances were investigated.The results indicated that a peak electric power of 11.55 kW was achieved at 29,369 rpm.The maximum total efficiency of the turbo‐generator was 58.98%,which was affected by both the turbine rotational speed and pressure ratio,according to the proposed performance map.