With the continuous development of science and technology and the gradual improvement of modem building technology, people pay more and more attention to the introduction of advanced technology in architectural design...With the continuous development of science and technology and the gradual improvement of modem building technology, people pay more and more attention to the introduction of advanced technology in architectural design, such as the application of intelligent technology. With the increasingly severe environmental situation, people are increasingly demanding the environmental performance and green performance of buildings. The establishment of ultra-low energy consumption passive buildings has become one of the key construction contents of construction projects. This paper mainly analyzes the design points and architectural forms of related buildings from the perspective of intelligent control.展开更多
Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management pl...Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.展开更多
Synaptic nano-devices have powerful capabilities in logic,memory and learning,making them essential compo-nents for constructing brain-like neuromorphic computing systems.Here,we have successfully developed and demons...Synaptic nano-devices have powerful capabilities in logic,memory and learning,making them essential compo-nents for constructing brain-like neuromorphic computing systems.Here,we have successfully developed and demonstrated a synaptic nano-device based on Ga_(2)O_(3) nanowires with low energy consumption.Under 255 nm light stimulation,the biomimetic synaptic nano-device can stimulate various functionalities of biological synapses,including pulse facilitation,peak time-dependent plasticity and memory learning ability.It is found that the artificial synaptic device based on Ga_(2)O_(3) nanowires can achieve an excellent"learning-forgetting-relearning"functionality.The transition from short-term memory to long-term memory and retention of the memory level after the stepwise learning can attribute to the great relearning functionality of Ga_(2)O_(3) nanowires.Furthermore,the energy consumption of the synaptic nano-device can be lower than 2.39×10^(-11) J for a synaptic event.Moreover,our device demonstrates exceptional stability in long-term stimulation and storage.In the applica-tion of neural morphological computation,the accuracy of digit recognition exceeds 90%after 12 training sessions,indicating the strong learning capability of the cognitive system composed of this synaptic nano-device.Therefore,our work paves an effective way for advancing hardware-based neural morphological computation and artificial intelligence systems requiring low power consumption.展开更多
With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)wi...With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)will coexist.In order to examine the effect of CAV on the overall stability and energy consumption of such a heterogeneous traffic system,we first take into account the interrelated perception of distance and speed by CAV to establish a macroscopic dynamic model through utilizing the full velocity difference(FVD)model.Subsequently,adopting the linear stability theory,we propose the linear stability condition for the model through using the small perturbation method,and the validity of the heterogeneous model is verified by comparing with the FVD model.Through nonlinear theoretical analysis,we further derive the KdV-Burgers equation,which captures the propagation characteristics of traffic density waves.Finally,by numerical simulation experiments through utilizing a macroscopic model of heterogeneous traffic flow,the effect of CAV permeability on the stability of density wave in heterogeneous traffic flow and the energy consumption of the traffic system is investigated.Subsequent analysis reveals emergent traffic phenomena.The experimental findings demonstrate that as CAV permeability increases,the ability to dampen the propagation of fluctuations in heterogeneous traffic flow gradually intensifies when giving system perturbation,leading to enhanced stability of the traffic system.Furthermore,higher initial traffic density renders the traffic system more susceptible to congestion,resulting in local clustering effect and stop-and-go traffic phenomenon.Remarkably,the total energy consumption of the heterogeneous traffic system exhibits a gradual decline with CAV permeability increasing.Further evidence has demonstrated the positive influence of CAV on heterogeneous traffic flow.This research contributes to providing theoretical guidance for future CAV applications,aiming to enhance urban road traffic efficiency and alleviate congestion.展开更多
This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China...This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.展开更多
Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this pap...Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus process.According to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious attacks.Additionally,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.展开更多
Although train modeling research is vast, most available simulation tools are confined to city-or trip-scale analysis, primarily offering micro-level simulations of network segments. This paper addresses this void by ...Although train modeling research is vast, most available simulation tools are confined to city-or trip-scale analysis, primarily offering micro-level simulations of network segments. This paper addresses this void by developing the Ne Train Sim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. The main objective of this simulator is to enable a comprehensive analysis of energy consumption and the associated carbon footprint for the entire train system. Four case studies were conducted to demonstrate the simulator's performance. The first case study validates the model by comparing Ne Train Sim output to empirical trajectory data. The results demonstrate that the simulated trajectory is precise enough to estimate the train energy consumption and carbon dioxide emissions. The second application demonstrates the train-following model considering six trains following each other. The results showcase the model ability to maintain safefollowing distances between successive trains. The next study highlights the simulator's ability to resolve train conflicts for different scenarios. Finally, the suitability of the Ne Train Sim for modeling realistic railroad networks is verified through the modeling of the entire US network and comparing alternative powertrains on the fleet energy consumption.展开更多
With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable ener...With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.展开更多
Over the last decade, the rapid growth in traffic and the number of network devices has implicitly led to an increase in network energy consumption. In this context, a new paradigm has emerged, Software-Defined Networ...Over the last decade, the rapid growth in traffic and the number of network devices has implicitly led to an increase in network energy consumption. In this context, a new paradigm has emerged, Software-Defined Networking (SDN), which is an emerging technique that separates the control plane and the data plane of the deployed network, enabling centralized control of the network, while offering flexibility in data center network management. Some research work is moving in the direction of optimizing the energy consumption of SD-DCN, but still does not guarantee good performance and quality of service for SDN networks. To solve this problem, we propose a new mathematical model based on the principle of combinatorial optimization to dynamically solve the problem of activating and deactivating switches and unused links that consume energy in SDN networks while guaranteeing quality of service (QoS) and ensuring load balancing in the network.展开更多
This study presents an energy consumption(EC)forecasting method for laser melting manufacturing of metal artifacts based on fusionable transfer learning(FTL).To predict the EC of manufacturing products,particularly fr...This study presents an energy consumption(EC)forecasting method for laser melting manufacturing of metal artifacts based on fusionable transfer learning(FTL).To predict the EC of manufacturing products,particularly from scale-down to scale-up,a general paradigm was first developed by categorizing the overall process into three main sub-steps.The operating electrical power was further formulated as a combinatorial function,based on which an operator learning network was adopted to fit the nonlinear relations between the fabricating arguments and EC.Parallel-arranged networks were constructed to investigate the impacts of fabrication variables and devices on power.Considering the interconnections among these factors,the outputs of the neural networks were blended and fused to jointly predict the electrical power.Most innovatively,large artifacts can be decomposed into timedependent laser-scanning trajectories,which can be further transformed into fusionable information via neural networks,inspired by large language model.Accordingly,transfer learning can deal with either scale-down or scale-up forecasting,namely,FTL with scalability within artifact structures.The effectiveness of the proposed FTL was verified through physical fabrication experiments via laser powder bed fusion.The relative error of the average and overall EC predictions based on FTL was maintained below 0.83%.The melting fusion quality was examined using metallographic diagrams.The proposed FTL framework can forecast the EC of scaled structures,which is particularly helpful in price estimation and quotation of large metal products towards carbon peaking and carbon neutrality.展开更多
Van der Waals(vdW)heterostructures provide a unique opportunity to develop various electronic and optoelectronic devices with specific functions by designing novel device structures,especially for bioinspired neuromor...Van der Waals(vdW)heterostructures provide a unique opportunity to develop various electronic and optoelectronic devices with specific functions by designing novel device structures,especially for bioinspired neuromorphic optoelectronic devices,which require the integration of nonvolatile memory and excellent optical responses.Here,we demonstrate a programmable optoelectronic synaptic floating-gate transistor based on multilayer graphene/h-BN/MoS2 vdW heterostructures,where both plasticity emulation and modulation were successfully realized in a single device.The dynamic tunneling process of photogenerated carriers through the as-fabricated vdW heterostructures contributed to a large memory ratio(105)between program and erase states.Our device can work as a functional or silent synapse by applying a program/erase voltage spike as a modulatory signal to determine the response to light stimulation,leading to a programmable operation in optoelectronic synaptic transistors.Moreover,an ultra-low energy consumption per light spike event(~2.5 fJ)was obtained in the program state owing to a suppressed noise current by program operation in our floating-gate transistor.This study proposes a feasible strategy to improve the functions of optoelectronic synaptic devices with ultra-low energy consumption based on vdW heterostructures designed for highly efficient artificial neural networks.展开更多
A new ground source heat pump system combined with radiant heating/cooling is proposed, and the principles and the advantages of the system are analyzed. A demonstration of the system is applied to a rebuilt building...A new ground source heat pump system combined with radiant heating/cooling is proposed, and the principles and the advantages of the system are analyzed. A demonstration of the system is applied to a rebuilt building： Xijindu exhibition hall, which is located in Zhenjiang city in China. Numerical studies on the thermal comfort and energy consumption of the system are carded out by using TRNSYS software. The results indicate that the system with the radiant floor method or the radiant ceiling method shows good thermal comfort without mechanical ventilation in winter. However, the system with either of the methods should add mechanical ventilation to ensure good comfort in summer. At the same level of thermal comfort, it can also be found that the annual energy consumption of the radiant ceiling system is less than that of the radiant floor system.展开更多
The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors ...The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production plarming and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed small- and large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.展开更多
Papermaking industry is a high-energy-consuming industry with long supply chain.The growth of paper product demand further intensifies the need of energy consumption.Energy saving through the full supply chain has bec...Papermaking industry is a high-energy-consuming industry with long supply chain.The growth of paper product demand further intensifies the need of energy consumption.Energy saving through the full supply chain has become a focal point for long-term sustainable development of the papermaking industry.This paper reviews the advances in life cycle analysis for the papermaking industry in recent years.All the stages from the full supply chain are involved to give a panoramic overview of the papermaking industry.The object of this paper is to provide scientific basis to industry and decision-makers with profound understanding of the energy consumption and energy saving potential in a life cycle perspective.展开更多
China＇s energy consumption experienced rapid growth over the past three decades, raising great concerns for the future adjustment of China＇s energy consumption structure. This paper first presents the historical evi...China＇s energy consumption experienced rapid growth over the past three decades, raising great concerns for the future adjustment of China＇s energy consumption structure. This paper first presents the historical evidence on China＇s energy consumption by the fuel types and sectors. Then, by establishing a bottom-up accounting framework and using long-range energy alternatives plan- ning energy modeling tool, the future of China＇s energy consumption structure under three scenarios is forecast. According to the estimates, China＇s total energy con- sumption will increase from 3014 million tonnes oil equivalent （Mtoe） in 2015 to 4470 Mtoe in 2040 under the current policies scenario, 4040 Mtoe in 2040 under the moderate policies scenario and 3320 Mtoe in 2040 under the strong policies scenario, respectively, lower than those of the IEA＇s estimations. In addition, the clean fuels （gas, nuclear and renewables） could be an effective alternative to the conventional fossil fuels （coal and oil） and offer much more potential. Furthermore, the industry sector has much strong reduction potentials than the other sectors. Finally, this paper suggests that the Chinese government should incorporate consideration of adjustment of the energy consumption structure into existing energy policies and measures in the future.展开更多
From the viewpoint of systems energy conservation, the influences of material flow on its energy consumption in a steel manufacturing process is an important subject. The quantitative analysis of the relationship betw...From the viewpoint of systems energy conservation, the influences of material flow on its energy consumption in a steel manufacturing process is an important subject. The quantitative analysis of the relationship between material flow and the energy intensity is useful to save energy in steel industry. Based on the concept of standard material flow diagram, all possible situations of ferric material flow in steel manufacturing process are analyzed. The expressions of the influence of material flow deviated from standard material flow diagram on energy consumption are put forward.展开更多
In this paper, we conduct research on the dynamic demand response problem in smart grid to control the energy consumption. The objective of the energy consumption control is constructed based on differential game, as ...In this paper, we conduct research on the dynamic demand response problem in smart grid to control the energy consumption. The objective of the energy consumption control is constructed based on differential game, as the dynamic of each users’ energy state in smart gird can be described based on a differential equation. Concept of electricity sharing is introduced to achieve load shift of main users from the high price hours to the low price hours. Nash equilibrium is given based on the Hamilton equation and the effectiveness of the proposed model is verified based on the numerical simulation results.展开更多
Fossil energy is the material basis of human survival, economic development and social progress. The relationship between energy consumption and economic growth is becoming increasingly close. However, energy consumpt...Fossil energy is the material basis of human survival, economic development and social progress. The relationship between energy consumption and economic growth is becoming increasingly close. However, energy consumption is the major source of greenhouse gases, which can significantly affect the balance of the global ecosystem. It has become the common goal of countries worldwide to address climate change, reduce carbon dioxide emissions, and implement sustainable development strategies. In this study, we applied an approximate relationship analysis, a decoupling relationship analysis, and a trend analysis to explore the relationship between energy consumption and economic growth using data from Kazakhstan for the period of 1993-2010. The results demonstrated： （1） the total energy consumption and GDP in Kazakhstan showed a ＂U＂-type curve from 1993 to 2010. This curve was observed because 1993-1999 was a period during which Kazakhstan transitioned from a republic to an independent country and experienced a difficult transition from a planned to a market economy. Then, the economic system became more stable and the industrial production increased rapidly because of the effective financial, monetary and industrial policy support from 2000 to 2010. （2） The relationships between energy con- sumption and carbon emissions, economic growth and energy exports were linked; the carbon emissions were mainly derived from energy consumption, and the dependence of economic growth on energy exports gradually increased from 1993 to 2010. Before 2000, the relationship between energy consumption and economic growth was in a recessional decoupling state because of the economic recession. After 2000, this relationship was in strong and weak decoupling states because the international crude oil prices rose and energy exports increased greatly year by year. （3） It is forecasted that Kazakhstan cannot achieve its goal of energy consumption by 2020. Therefore, a low-carbon economy is the best strategic choice to address climate change from a global perspective in Kazakhstan. Thus, we proposed strategies including the improvement of the energy consumption structure, the development of new energy and renewable energy, the use of cleaner production technologies, the adjustment and optimization of the industrial structure, and the expansion of forest areas.展开更多
In order to improve prediction accuracy of the grey prediction model and forecast China energy consumption and production in a short term, this paper proposes a novel com- prehensively optimized GM（1,1） model, also ...In order to improve prediction accuracy of the grey prediction model and forecast China energy consumption and production in a short term, this paper proposes a novel com- prehensively optimized GM（1,1） model, also named COGM（1,1）, based on the grey modeling mechanism. First, the relationship of the background value formula and its whitenization equation is analyzed and a new method optimizing background values is proposed to eliminate systemic errors in the modeling process. Second, the solving process of the new model is derived. For parameter estimation, a set of auxiliary parameters are used to change grey equation＇s form. Then, original parameters are re- stored by an equations system. After solving the whitenization equation, initial value in time response function is established by least errors criteria. Finally, a numerical case and comparison with other grey prediction models are made to testify the new model＇s effectiveness, and the computational results show that the COGM（1,1） model has a better property and achieves higher precision. The new model is used to forecast China energy con- sumption and production, and the ability of energy self-sufficiency is further analyzed. Results indicate that gaps between consump- tion and production in future are predicted to decline.展开更多
This paper analyzes Chinese household CO_2 emissions in 1994-2012 based on the Logarithmic Mean Divisia Index(LMDI) structure decomposition model, and discusses the relationship between household CO_2 emissions and ec...This paper analyzes Chinese household CO_2 emissions in 1994-2012 based on the Logarithmic Mean Divisia Index(LMDI) structure decomposition model, and discusses the relationship between household CO_2 emissions and economic growth based on a decoupling indicator.The results show that in 1994-2012, household CO_2 emissions grew in general and displayed an accelerated growth trend during the early 21 st century. Economic growth leading to an increase in energy consumption is the main driving factor of CO_2 emission growth(an increase of 1.078 Gt CO_2) with cumulative contribution rate of 55.92%, while the decline in energy intensity is the main cause of CO_2 emission growth inhibition(0.723 Gt CO_2 emission reduction) with cumulative contribution rate of 38.27%. Meanwhile, household CO_2 emissions are in a weak state of decoupling in general. The change in CO_2 emissions caused by population and economic growth shows a weak decoupling and expansive decoupling state, respectively. The CO_2 emission change caused by energy intensity is in a state of strong decoupling, and the change caused by energy consumption structure ?uctuates between a weak and a strong decoupling state.展开更多
文摘With the continuous development of science and technology and the gradual improvement of modem building technology, people pay more and more attention to the introduction of advanced technology in architectural design, such as the application of intelligent technology. With the increasingly severe environmental situation, people are increasingly demanding the environmental performance and green performance of buildings. The establishment of ultra-low energy consumption passive buildings has become one of the key construction contents of construction projects. This paper mainly analyzes the design points and architectural forms of related buildings from the perspective of intelligent control.
基金funded by NARI Group’s Independent Project of China(Grant No.524609230125)the Foundation of NARI-TECH Nanjing Control System Ltd.of China(Grant No.0914202403120020).
文摘Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.
基金financially supported by the Key Research Program of Frontier Sciences,CAS (No. ZDBS-LYJSC034)National Natural Science Foundation of China (No.62174172)+2 种基金China Postdoctoral Science Foundation (Nos.2023TQ0238 and 2023M742560)Basic Research Pilot Project of Suzhou (No. SSD2024003)Jiangsu Key Disciplines of the Fourteenth Five-Year Plan (No. 2021135)
文摘Synaptic nano-devices have powerful capabilities in logic,memory and learning,making them essential compo-nents for constructing brain-like neuromorphic computing systems.Here,we have successfully developed and demonstrated a synaptic nano-device based on Ga_(2)O_(3) nanowires with low energy consumption.Under 255 nm light stimulation,the biomimetic synaptic nano-device can stimulate various functionalities of biological synapses,including pulse facilitation,peak time-dependent plasticity and memory learning ability.It is found that the artificial synaptic device based on Ga_(2)O_(3) nanowires can achieve an excellent"learning-forgetting-relearning"functionality.The transition from short-term memory to long-term memory and retention of the memory level after the stepwise learning can attribute to the great relearning functionality of Ga_(2)O_(3) nanowires.Furthermore,the energy consumption of the synaptic nano-device can be lower than 2.39×10^(-11) J for a synaptic event.Moreover,our device demonstrates exceptional stability in long-term stimulation and storage.In the applica-tion of neural morphological computation,the accuracy of digit recognition exceeds 90%after 12 training sessions,indicating the strong learning capability of the cognitive system composed of this synaptic nano-device.Therefore,our work paves an effective way for advancing hardware-based neural morphological computation and artificial intelligence systems requiring low power consumption.
基金Project supported by the Fundamental Research Funds for Central Universities,China(Grant No.2022YJS065)the National Natural Science Foundation of China(Grant Nos.72288101 and 72371019).
文摘With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)will coexist.In order to examine the effect of CAV on the overall stability and energy consumption of such a heterogeneous traffic system,we first take into account the interrelated perception of distance and speed by CAV to establish a macroscopic dynamic model through utilizing the full velocity difference(FVD)model.Subsequently,adopting the linear stability theory,we propose the linear stability condition for the model through using the small perturbation method,and the validity of the heterogeneous model is verified by comparing with the FVD model.Through nonlinear theoretical analysis,we further derive the KdV-Burgers equation,which captures the propagation characteristics of traffic density waves.Finally,by numerical simulation experiments through utilizing a macroscopic model of heterogeneous traffic flow,the effect of CAV permeability on the stability of density wave in heterogeneous traffic flow and the energy consumption of the traffic system is investigated.Subsequent analysis reveals emergent traffic phenomena.The experimental findings demonstrate that as CAV permeability increases,the ability to dampen the propagation of fluctuations in heterogeneous traffic flow gradually intensifies when giving system perturbation,leading to enhanced stability of the traffic system.Furthermore,higher initial traffic density renders the traffic system more susceptible to congestion,resulting in local clustering effect and stop-and-go traffic phenomenon.Remarkably,the total energy consumption of the heterogeneous traffic system exhibits a gradual decline with CAV permeability increasing.Further evidence has demonstrated the positive influence of CAV on heterogeneous traffic flow.This research contributes to providing theoretical guidance for future CAV applications,aiming to enhance urban road traffic efficiency and alleviate congestion.
文摘This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant 62371082 and 62001076in part by the National Key R&D Program of China under Grant 2021YFB1714100in part by the Natural Science Foundation of Chongqing under Grant CSTB2023NSCQ-MSX0726 and cstc2020jcyjmsxmX0878.
文摘Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus process.According to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious attacks.Additionally,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.
基金funded in part by the Advanced Research Projects AgencyEnergy (ARPA-E), U.S. Department of Energy, under award number DE-AR0001471。
文摘Although train modeling research is vast, most available simulation tools are confined to city-or trip-scale analysis, primarily offering micro-level simulations of network segments. This paper addresses this void by developing the Ne Train Sim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. The main objective of this simulator is to enable a comprehensive analysis of energy consumption and the associated carbon footprint for the entire train system. Four case studies were conducted to demonstrate the simulator's performance. The first case study validates the model by comparing Ne Train Sim output to empirical trajectory data. The results demonstrate that the simulated trajectory is precise enough to estimate the train energy consumption and carbon dioxide emissions. The second application demonstrates the train-following model considering six trains following each other. The results showcase the model ability to maintain safefollowing distances between successive trains. The next study highlights the simulator's ability to resolve train conflicts for different scenarios. Finally, the suitability of the Ne Train Sim for modeling realistic railroad networks is verified through the modeling of the entire US network and comparing alternative powertrains on the fleet energy consumption.
基金supported by State Grid Corporation of China Project“Research and Application of Key Technologies for Active Power Control in Regional Power Grid with High Penetration of Distributed Renewable Generation”(5108-202316044A-1-1-ZN).
文摘With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.
文摘Over the last decade, the rapid growth in traffic and the number of network devices has implicitly led to an increase in network energy consumption. In this context, a new paradigm has emerged, Software-Defined Networking (SDN), which is an emerging technique that separates the control plane and the data plane of the deployed network, enabling centralized control of the network, while offering flexibility in data center network management. Some research work is moving in the direction of optimizing the energy consumption of SD-DCN, but still does not guarantee good performance and quality of service for SDN networks. To solve this problem, we propose a new mathematical model based on the principle of combinatorial optimization to dynamically solve the problem of activating and deactivating switches and unused links that consume energy in SDN networks while guaranteeing quality of service (QoS) and ensuring load balancing in the network.
基金funded by the National Key Research and Development Program of China,No.2022YFB3303303Key Open Fund of State Key Lab of Materials Processing and Die&Mould Technology of China,No.P2024-001Zhejiang Provincial Research and Development Project of China,No.LGG22E050010。
文摘This study presents an energy consumption(EC)forecasting method for laser melting manufacturing of metal artifacts based on fusionable transfer learning(FTL).To predict the EC of manufacturing products,particularly from scale-down to scale-up,a general paradigm was first developed by categorizing the overall process into three main sub-steps.The operating electrical power was further formulated as a combinatorial function,based on which an operator learning network was adopted to fit the nonlinear relations between the fabricating arguments and EC.Parallel-arranged networks were constructed to investigate the impacts of fabrication variables and devices on power.Considering the interconnections among these factors,the outputs of the neural networks were blended and fused to jointly predict the electrical power.Most innovatively,large artifacts can be decomposed into timedependent laser-scanning trajectories,which can be further transformed into fusionable information via neural networks,inspired by large language model.Accordingly,transfer learning can deal with either scale-down or scale-up forecasting,namely,FTL with scalability within artifact structures.The effectiveness of the proposed FTL was verified through physical fabrication experiments via laser powder bed fusion.The relative error of the average and overall EC predictions based on FTL was maintained below 0.83%.The melting fusion quality was examined using metallographic diagrams.The proposed FTL framework can forecast the EC of scaled structures,which is particularly helpful in price estimation and quotation of large metal products towards carbon peaking and carbon neutrality.
基金National Natural Science Foundation of China,Grant/Award Numbers:62104017,52072204,62074015National Postdoctoral Program for Innovative Talents of China,Grant/Award Number:BX20200049China Postdoctoral Science Foundation,Grant/Award Number:2021M690013。
文摘Van der Waals(vdW)heterostructures provide a unique opportunity to develop various electronic and optoelectronic devices with specific functions by designing novel device structures,especially for bioinspired neuromorphic optoelectronic devices,which require the integration of nonvolatile memory and excellent optical responses.Here,we demonstrate a programmable optoelectronic synaptic floating-gate transistor based on multilayer graphene/h-BN/MoS2 vdW heterostructures,where both plasticity emulation and modulation were successfully realized in a single device.The dynamic tunneling process of photogenerated carriers through the as-fabricated vdW heterostructures contributed to a large memory ratio(105)between program and erase states.Our device can work as a functional or silent synapse by applying a program/erase voltage spike as a modulatory signal to determine the response to light stimulation,leading to a programmable operation in optoelectronic synaptic transistors.Moreover,an ultra-low energy consumption per light spike event(~2.5 fJ)was obtained in the program state owing to a suppressed noise current by program operation in our floating-gate transistor.This study proposes a feasible strategy to improve the functions of optoelectronic synaptic devices with ultra-low energy consumption based on vdW heterostructures designed for highly efficient artificial neural networks.
基金The National Natural Science Foundation of China(No. 51036001 )the Natural Science Foundation of Jiangsu Province(No. BK2010043)
文摘A new ground source heat pump system combined with radiant heating/cooling is proposed, and the principles and the advantages of the system are analyzed. A demonstration of the system is applied to a rebuilt building： Xijindu exhibition hall, which is located in Zhenjiang city in China. Numerical studies on the thermal comfort and energy consumption of the system are carded out by using TRNSYS software. The results indicate that the system with the radiant floor method or the radiant ceiling method shows good thermal comfort without mechanical ventilation in winter. However, the system with either of the methods should add mechanical ventilation to ensure good comfort in summer. At the same level of thermal comfort, it can also be found that the annual energy consumption of the radiant ceiling system is less than that of the radiant floor system.
基金Supported by a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Program(Grant No.294931)National Science Foundation of China(Grant No.51175262)+1 种基金Jiangsu Provincial Science Foundation for Excellent Youths of China(Grant No.BK2012032)Jiangsu Provincial Industry-Academy-Research Grant of China(Grant No.BY201220116)
文摘The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production plarming and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed small- and large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.
基金Supported by the State Key Laboratory of Pulp and Paper Engineering(201830)the Research Fund Program of Guangdong Provincial Key Lab of Green Chemical Product Technology(GC201809)+1 种基金Fundamental Research Funds for the Central Universities(2017BQ023)the Science and Technology Project of Guangdong Province(2015B010110004,2015A010104004,2013B010406002)
文摘Papermaking industry is a high-energy-consuming industry with long supply chain.The growth of paper product demand further intensifies the need of energy consumption.Energy saving through the full supply chain has become a focal point for long-term sustainable development of the papermaking industry.This paper reviews the advances in life cycle analysis for the papermaking industry in recent years.All the stages from the full supply chain are involved to give a panoramic overview of the papermaking industry.The object of this paper is to provide scientific basis to industry and decision-makers with profound understanding of the energy consumption and energy saving potential in a life cycle perspective.
基金supported by National Natural Science Foundation (No. 71273277)National Social Science Foundation (No. 13&ZD159)
文摘China＇s energy consumption experienced rapid growth over the past three decades, raising great concerns for the future adjustment of China＇s energy consumption structure. This paper first presents the historical evidence on China＇s energy consumption by the fuel types and sectors. Then, by establishing a bottom-up accounting framework and using long-range energy alternatives plan- ning energy modeling tool, the future of China＇s energy consumption structure under three scenarios is forecast. According to the estimates, China＇s total energy con- sumption will increase from 3014 million tonnes oil equivalent （Mtoe） in 2015 to 4470 Mtoe in 2040 under the current policies scenario, 4040 Mtoe in 2040 under the moderate policies scenario and 3320 Mtoe in 2040 under the strong policies scenario, respectively, lower than those of the IEA＇s estimations. In addition, the clean fuels （gas, nuclear and renewables） could be an effective alternative to the conventional fossil fuels （coal and oil） and offer much more potential. Furthermore, the industry sector has much strong reduction potentials than the other sectors. Finally, this paper suggests that the Chinese government should incorporate consideration of adjustment of the energy consumption structure into existing energy policies and measures in the future.
基金Item Sponsored by National Basic Research Programof China (200002600)
文摘From the viewpoint of systems energy conservation, the influences of material flow on its energy consumption in a steel manufacturing process is an important subject. The quantitative analysis of the relationship between material flow and the energy intensity is useful to save energy in steel industry. Based on the concept of standard material flow diagram, all possible situations of ferric material flow in steel manufacturing process are analyzed. The expressions of the influence of material flow deviated from standard material flow diagram on energy consumption are put forward.
基金supported by National Key R&D Program of China, No.2018YFB1003905the Fundamental Research Funds for the Central Universities, No.FRF-TP-18-008A3
文摘In this paper, we conduct research on the dynamic demand response problem in smart grid to control the energy consumption. The objective of the energy consumption control is constructed based on differential game, as the dynamic of each users’ energy state in smart gird can be described based on a differential equation. Concept of electricity sharing is introduced to achieve load shift of main users from the high price hours to the low price hours. Nash equilibrium is given based on the Hamilton equation and the effectiveness of the proposed model is verified based on the numerical simulation results.
基金supported by International Science & Technology Cooperation Program of China (2010DFA92720-07)
文摘Fossil energy is the material basis of human survival, economic development and social progress. The relationship between energy consumption and economic growth is becoming increasingly close. However, energy consumption is the major source of greenhouse gases, which can significantly affect the balance of the global ecosystem. It has become the common goal of countries worldwide to address climate change, reduce carbon dioxide emissions, and implement sustainable development strategies. In this study, we applied an approximate relationship analysis, a decoupling relationship analysis, and a trend analysis to explore the relationship between energy consumption and economic growth using data from Kazakhstan for the period of 1993-2010. The results demonstrated： （1） the total energy consumption and GDP in Kazakhstan showed a ＂U＂-type curve from 1993 to 2010. This curve was observed because 1993-1999 was a period during which Kazakhstan transitioned from a republic to an independent country and experienced a difficult transition from a planned to a market economy. Then, the economic system became more stable and the industrial production increased rapidly because of the effective financial, monetary and industrial policy support from 2000 to 2010. （2） The relationships between energy con- sumption and carbon emissions, economic growth and energy exports were linked; the carbon emissions were mainly derived from energy consumption, and the dependence of economic growth on energy exports gradually increased from 1993 to 2010. Before 2000, the relationship between energy consumption and economic growth was in a recessional decoupling state because of the economic recession. After 2000, this relationship was in strong and weak decoupling states because the international crude oil prices rose and energy exports increased greatly year by year. （3） It is forecasted that Kazakhstan cannot achieve its goal of energy consumption by 2020. Therefore, a low-carbon economy is the best strategic choice to address climate change from a global perspective in Kazakhstan. Thus, we proposed strategies including the improvement of the energy consumption structure, the development of new energy and renewable energy, the use of cleaner production technologies, the adjustment and optimization of the industrial structure, and the expansion of forest areas.
基金supported by the National Natural Science Foundation of China(710710777130106071371098)
文摘In order to improve prediction accuracy of the grey prediction model and forecast China energy consumption and production in a short term, this paper proposes a novel com- prehensively optimized GM（1,1） model, also named COGM（1,1）, based on the grey modeling mechanism. First, the relationship of the background value formula and its whitenization equation is analyzed and a new method optimizing background values is proposed to eliminate systemic errors in the modeling process. Second, the solving process of the new model is derived. For parameter estimation, a set of auxiliary parameters are used to change grey equation＇s form. Then, original parameters are re- stored by an equations system. After solving the whitenization equation, initial value in time response function is established by least errors criteria. Finally, a numerical case and comparison with other grey prediction models are made to testify the new model＇s effectiveness, and the computational results show that the COGM（1,1） model has a better property and achieves higher precision. The new model is used to forecast China energy con- sumption and production, and the ability of energy self-sufficiency is further analyzed. Results indicate that gaps between consump- tion and production in future are predicted to decline.
基金supported by the National Natural Science Foundation of China (NSFC) under Grant No. 71573015, 71303019, 71173206, and 71521002
文摘This paper analyzes Chinese household CO_2 emissions in 1994-2012 based on the Logarithmic Mean Divisia Index(LMDI) structure decomposition model, and discusses the relationship between household CO_2 emissions and economic growth based on a decoupling indicator.The results show that in 1994-2012, household CO_2 emissions grew in general and displayed an accelerated growth trend during the early 21 st century. Economic growth leading to an increase in energy consumption is the main driving factor of CO_2 emission growth(an increase of 1.078 Gt CO_2) with cumulative contribution rate of 55.92%, while the decline in energy intensity is the main cause of CO_2 emission growth inhibition(0.723 Gt CO_2 emission reduction) with cumulative contribution rate of 38.27%. Meanwhile, household CO_2 emissions are in a weak state of decoupling in general. The change in CO_2 emissions caused by population and economic growth shows a weak decoupling and expansive decoupling state, respectively. The CO_2 emission change caused by energy intensity is in a state of strong decoupling, and the change caused by energy consumption structure ?uctuates between a weak and a strong decoupling state.
