Grid-level large-scale electrical energy storage(GLEES) is an essential approach for balancing the supply–demand of electricity generation, distribution, and usage. Compared with conventional energy storage methods, ...Grid-level large-scale electrical energy storage(GLEES) is an essential approach for balancing the supply–demand of electricity generation, distribution, and usage. Compared with conventional energy storage methods, battery technologies are desirable energy storage devices for GLEES due to their easy modularization, rapid response, flexible installation, and short construction cycles. In general, battery energy storage technologies are expected to meet the requirements of GLEES such as peak shaving and load leveling, voltage and frequency regulation, and emergency response, which are highlighted in this perspective. Furthermore, several types of battery technologies, including lead–acid, nickel–cadmium, nickel–metal hydride, sodium–sulfur, lithium-ion, and flow batteries, are discussed in detail for the application of GLEES. Moreover, some possible developing directions to facilitate efforts in this area are presented to establish a perspective on battery technology, provide a road map for guiding future studies, and promote the commercial application of batteries for GLEES.展开更多
The streamflow over the Yellow River basin is simulated using the PRECIS （Providing REgional Climates for Impacts Studies） regional climate model driven by 15-year （1979-1993） ECMWF reanalysis data as the initial ...The streamflow over the Yellow River basin is simulated using the PRECIS （Providing REgional Climates for Impacts Studies） regional climate model driven by 15-year （1979-1993） ECMWF reanalysis data as the initial and lateral boundary conditions and an off-line large-scale routing model （LRM）. The LRM uses physical catchment and river channel information and allows streamflow to be predicted for large continental rivers with a 1°×1° spatial resolution. The results show that the PRECIS model can reproduce the general southeast to northwest gradient distribution of the precipitation over the Yellow River basin, The PRECIS- LRM model combination has the capability to simulate the seasonal and annual streamflow over the Yellow River basin. The simulated streamflow is generally coincident with the naturalized streamflow both in timing and in magnitude.展开更多
A reduction in network energy consumption and the establishment of green networks have become key scientific problems in academic and industrial research.Existing energy efficiency schemes are based on a known traffic...A reduction in network energy consumption and the establishment of green networks have become key scientific problems in academic and industrial research.Existing energy efficiency schemes are based on a known traffic matrix,and acquiring a real-time traffic matrix in current complex networks is difficult.Therefore,this research investigates how to reduce network energy consumption without a real-time traffic matrix.In particular,this paper proposes an intra-domain energy-efficient routing scheme based on multipath routing.It analyzes the relationship between routing availability and energy-efficient routing and integrates the two mechanisms to satisfy the requirements of availability and energy efficiency.The main research focus is as follows:(1)A link criticality model is evaluated to quantitatively measure the importance of links in a network.(2)On the basis of the link criticality model,this paper analyzes an energy-efficient routing technology based on multipath routing to achieve the goals of availability and energy efficiency simultaneously.(3)An energy-efficient routing algorithm based on multipath routing in large-scale networks is proposed.(4)The proposed method does not require a real-time traffic matrix in the network and is thus easy to apply in practice.(5)The proposed algorithm is verified in several network topologies.Experimental results show that the algorithm can not only reduce network energy consumption but can also ensure routing availability.展开更多
The study was carried out to improve farmers’ awareness, enhance the adoption of full package sorghum production technologies. The large-scale demonstration was implemented at Gololcha woreda of Arsi zone for one yea...The study was carried out to improve farmers’ awareness, enhance the adoption of full package sorghum production technologies. The large-scale demonstration was implemented at Gololcha woreda of Arsi zone for one year (2019/2020) using Melkam variety. The demonstration was implemented in three kebeles and a total of 100 hectares of land was covered by participating 117 household heads (farmers) out of which 12 of them were women-headed. In the demonstration farmers contributed a land size of 0.25 hectares (the minimum) and 2 hectares of land (maximum). Totally, from the demonstration 4030 quintals of sorghum were harvested with 42.3 quintals per hectare average productivity. The yield obtained by farmers practices w</span><span style="font-family:Verdana;">as</span><span style="font-family:Verdana;"> 18.23 q</span><span style="font-family:""><span style="font-family:Verdana;">·ha</span><sup><span style="font-family:Verdana;">-1</span></sup><span style="font-family:Verdana;"> which is lower as compared to the average yield obtained by large scale demonstration. The technology gap (TG) was 15.70 q·ha</span><sup><span style="font-family:Verdana;">-1</span></sup><span style="font-family:Verdana;"> which indicated that technologies have not been adopted. Extension gap was 24.07 q·ha</span><sup><span style="font-family:Verdana;">-1</span></sup><span style="font-family:Verdana;"> and this result indicated that the extension approach should be </span></span><span style="font-family:Verdana;">more </span><span style="font-family:Verdana;">strengthen</span><span style="font-family:Verdana;">ed</span><span style="font-family:Verdana;">. It has been ascertained that </span><span style="font-family:Verdana;">“</span><span style="font-family:Verdana;">Melkam</span><span style="font-family:Verdana;">”</span><span style="font-family:Verdana;"> variety is the best fitted variety and promotion of improved sorghum technologies via large scale demonstration has show</span><span style="font-family:Verdana;">n</span><span style="font-family:Verdana;"> a considerable yield increment as compared to farmers practices. According to the farmers’ trait preference, Melkam variety was preferred by farmers because of its high yielding, consumption quality, early maturity, palatability, and drought-tolerant traits respectively. For sustainable production of improved sorghum technologies, the seed system should be taken into consideration to deliver the seed supply for the entire sorghum producers.展开更多
A novel routing architecture named DREAMSCAPE is presented to solve the problem of path computation in multi-layer, multi-domain and multi-constraints scenarios, which includes Group Engine (GE) and Unit Engine (UE). ...A novel routing architecture named DREAMSCAPE is presented to solve the problem of path computation in multi-layer, multi-domain and multi-constraints scenarios, which includes Group Engine (GE) and Unit Engine (UE). GE, UE and their cooperation relationship form the main feature of DREAMSCAPE, i.e. Dual Routing Engine (DRE). Based on DRE, two routing schemes are proposed, which are DRE Forward Path Computation (DRE-FPC) and Hierarchical DRE Backward Recursive PCE-based Computation (HDRE-BRPC). In order to validate various intelligent networking technologies of large-scale heterogeneous optical networks, a DRE-based transport optical networks testbed is built with 1000 GMPLS-based control nodes and 5 optical transport nodes. The two proposed routing schemes, i.e. DRE-FPC and HDRE-BRPC, are validated on the testbed, compared with traditional Hierarchical Routing (HR) scheme. Experimental results show a good performance of DREAMSCAPE.展开更多
This paper discusses the digital application and benefit analysis of building information model(BIM)technology in the large-scale comprehensive development project of the Guangxi headquarters base.The project covers a...This paper discusses the digital application and benefit analysis of building information model(BIM)technology in the large-scale comprehensive development project of the Guangxi headquarters base.The project covers a total area of 92,100 square meters,with a total construction area of 379,700 square meters,including a variety of architectural forms.Through three-dimensional modeling and simulation analysis,BIM technology significantly enhances the design quality and efficiency,shortens the design cycle by about 20%,and promotes the collaboration and integration of project management,improving the management efficiency by about 25%.During the construction phase,the collision detection and four-dimensional visual management functions of BIM technology have improved construction efficiency by about 15%and saved the cost by about 10%.In addition,BIM technology has promoted green building and sustainable development,achieved the dual improvement of technical and economic indicators and social and economic benefits,set an example for enterprises in digital transformation,and opened up new market businesses.展开更多
In order to increase productivity and reduce energy consumption of steelmaking-continuous casting(SCC) production process, especially with complicated technological routes, the cross entropy(CE) method was adopted to ...In order to increase productivity and reduce energy consumption of steelmaking-continuous casting(SCC) production process, especially with complicated technological routes, the cross entropy(CE) method was adopted to optimize the SCC production scheduling(SCCPS) problem. Based on the CE method, a matrix encoding scheme was proposed and a backward decoding method was used to generate a reasonable schedule. To describe the distribution of the solution space, a probability distribution model was built and used to generate individuals. In addition, the probability updating mechanism of the probability distribution model was proposed which helps to find the optimal individual gradually. Because of the poor stability and premature convergence of the standard cross entropy(SCE) algorithm, the improved cross entropy(ICE) algorithm was proposed with the following improvements: individual generation mechanism combined with heuristic rules, retention mechanism of the optimal individual, local search mechanism and dynamic parameters of the algorithm. Simulation experiments validate that the CE method is effective in solving the SCCPS problem with complicated technological routes and the ICE algorithm proposed has superior performance to the SCE algorithm and the genetic algorithm(GA).展开更多
In the context of constructing Global Energy Interconnection(GEI), energy storage technology, as one of the important basic supporting technologies in power system, will play an important role in the energy configurat...In the context of constructing Global Energy Interconnection(GEI), energy storage technology, as one of the important basic supporting technologies in power system, will play an important role in the energy configuration and optimization. Based on the most promising battery energy storage technology, this paper introduces the current status of the grid technology, the application of large-scale energy storage technology and the supporting role of battery energy storage for GEI. Based on several key technologies of large-scale battery energy storage system, preliminary analysis of the standard system construction of energy storage system is made, and the future prospect is put forward.展开更多
To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,...To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.展开更多
Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for rese...Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.展开更多
In the large-scale logistics distribution of single logistic center,the method based on traditional genetic algorithm is slow in evolution and easy to fall into the local optimal solution.Addressing at this issue,we p...In the large-scale logistics distribution of single logistic center,the method based on traditional genetic algorithm is slow in evolution and easy to fall into the local optimal solution.Addressing at this issue,we propose a novel approach of exploring hybrid genetic algorithm based large-scale logistic distribution for BBG supermarket.We integrate greedy algorithm and hillclimbing algorithm into genetic algorithm.Greedy algorithm is applied to initialize the population,and then hill-climbing algorithm is used to optimize individuals in each generation after selection,crossover and mutation.Our approach is evaluated on the dataset of BBG Supermarket which is one of the top 10 supermarkets in China.Experimental results show that our method outperforms some other methods in the field.展开更多
The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicl...The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.展开更多
Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation o...Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation of intelligent ships,route planning technologies have developed many route planning algorithms that prioritize economy and safety.This paper conducts an in-depth study of algorithm efficiency for a route planning problem,proposing an intelligent ship route planning algorithm based on the adaptive step size Informed-RRT^(*).This algorithm can quickly plan a short route according to automatic obstacle avoidance and is suitable for planning the routes of intelligent ships.Results show that the adaptive step size Informed-RRT^(*) algorithm can shorten the optimal route length by approximately 13.05%while ensuring the running time of the planning algorithm and avoiding approximately 23.64%of redundant sampling nodes.The improved algorithm effectively circumvents unnecessary calculations and reduces a large amount of redundant sampling data,thus improving the efficiency of route planning.In a complex water environment,the unique adaptive step size mechanism enables this algorithm to prevent restricted search tree expansion,showing strong search ability and robustness,which is of practical significance for the development of intelligent ships.展开更多
With the continuous improvement of the scale and complexity of large-scale events,temporary teams,as the core carrier of event execution,their relationship construction quality directly affects the event effectiveness...With the continuous improvement of the scale and complexity of large-scale events,temporary teams,as the core carrier of event execution,their relationship construction quality directly affects the event effectiveness.From the perspective of intelligent collaboration and combined with technological innovation applications,this paper discusses the related issues of relationship construction of temporary teams in large-scale events.It first expounds the research background and significance,then sorts out the theoretical basis of intelligent collaboration and temporary team relationship construction,analyzes the current dilemmas in the relationship construction of temporary teams in large-scale events,and then puts forward the relationship construction path based on technological innovation applications,verifies it with specific cases,and finally summarizes the research conclusions and prospects.The study aims to provide theoretical reference and practical guidance for improving the collaboration efficiency and stability of temporary teams in large-scale events.展开更多
文摘Grid-level large-scale electrical energy storage(GLEES) is an essential approach for balancing the supply–demand of electricity generation, distribution, and usage. Compared with conventional energy storage methods, battery technologies are desirable energy storage devices for GLEES due to their easy modularization, rapid response, flexible installation, and short construction cycles. In general, battery energy storage technologies are expected to meet the requirements of GLEES such as peak shaving and load leveling, voltage and frequency regulation, and emergency response, which are highlighted in this perspective. Furthermore, several types of battery technologies, including lead–acid, nickel–cadmium, nickel–metal hydride, sodium–sulfur, lithium-ion, and flow batteries, are discussed in detail for the application of GLEES. Moreover, some possible developing directions to facilitate efforts in this area are presented to establish a perspective on battery technology, provide a road map for guiding future studies, and promote the commercial application of batteries for GLEES.
文摘The streamflow over the Yellow River basin is simulated using the PRECIS （Providing REgional Climates for Impacts Studies） regional climate model driven by 15-year （1979-1993） ECMWF reanalysis data as the initial and lateral boundary conditions and an off-line large-scale routing model （LRM）. The LRM uses physical catchment and river channel information and allows streamflow to be predicted for large continental rivers with a 1°×1° spatial resolution. The results show that the PRECIS model can reproduce the general southeast to northwest gradient distribution of the precipitation over the Yellow River basin, The PRECIS- LRM model combination has the capability to simulate the seasonal and annual streamflow over the Yellow River basin. The simulated streamflow is generally coincident with the naturalized streamflow both in timing and in magnitude.
基金supported by the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation(QCXM201910)the National Natural Science Foundation of China(Nos.61702315,61802092)+1 种基金the Applied Basic Research Plan of Shanxi Province(No.2201901D211168)the Key R&D Program(International Science and Technology Cooperation Project)of Shanxi Province China(No.201903D421003).
文摘A reduction in network energy consumption and the establishment of green networks have become key scientific problems in academic and industrial research.Existing energy efficiency schemes are based on a known traffic matrix,and acquiring a real-time traffic matrix in current complex networks is difficult.Therefore,this research investigates how to reduce network energy consumption without a real-time traffic matrix.In particular,this paper proposes an intra-domain energy-efficient routing scheme based on multipath routing.It analyzes the relationship between routing availability and energy-efficient routing and integrates the two mechanisms to satisfy the requirements of availability and energy efficiency.The main research focus is as follows:(1)A link criticality model is evaluated to quantitatively measure the importance of links in a network.(2)On the basis of the link criticality model,this paper analyzes an energy-efficient routing technology based on multipath routing to achieve the goals of availability and energy efficiency simultaneously.(3)An energy-efficient routing algorithm based on multipath routing in large-scale networks is proposed.(4)The proposed method does not require a real-time traffic matrix in the network and is thus easy to apply in practice.(5)The proposed algorithm is verified in several network topologies.Experimental results show that the algorithm can not only reduce network energy consumption but can also ensure routing availability.
文摘The study was carried out to improve farmers’ awareness, enhance the adoption of full package sorghum production technologies. The large-scale demonstration was implemented at Gololcha woreda of Arsi zone for one year (2019/2020) using Melkam variety. The demonstration was implemented in three kebeles and a total of 100 hectares of land was covered by participating 117 household heads (farmers) out of which 12 of them were women-headed. In the demonstration farmers contributed a land size of 0.25 hectares (the minimum) and 2 hectares of land (maximum). Totally, from the demonstration 4030 quintals of sorghum were harvested with 42.3 quintals per hectare average productivity. The yield obtained by farmers practices w</span><span style="font-family:Verdana;">as</span><span style="font-family:Verdana;"> 18.23 q</span><span style="font-family:""><span style="font-family:Verdana;">·ha</span><sup><span style="font-family:Verdana;">-1</span></sup><span style="font-family:Verdana;"> which is lower as compared to the average yield obtained by large scale demonstration. The technology gap (TG) was 15.70 q·ha</span><sup><span style="font-family:Verdana;">-1</span></sup><span style="font-family:Verdana;"> which indicated that technologies have not been adopted. Extension gap was 24.07 q·ha</span><sup><span style="font-family:Verdana;">-1</span></sup><span style="font-family:Verdana;"> and this result indicated that the extension approach should be </span></span><span style="font-family:Verdana;">more </span><span style="font-family:Verdana;">strengthen</span><span style="font-family:Verdana;">ed</span><span style="font-family:Verdana;">. It has been ascertained that </span><span style="font-family:Verdana;">“</span><span style="font-family:Verdana;">Melkam</span><span style="font-family:Verdana;">”</span><span style="font-family:Verdana;"> variety is the best fitted variety and promotion of improved sorghum technologies via large scale demonstration has show</span><span style="font-family:Verdana;">n</span><span style="font-family:Verdana;"> a considerable yield increment as compared to farmers practices. According to the farmers’ trait preference, Melkam variety was preferred by farmers because of its high yielding, consumption quality, early maturity, palatability, and drought-tolerant traits respectively. For sustainable production of improved sorghum technologies, the seed system should be taken into consideration to deliver the seed supply for the entire sorghum producers.
基金supported in part by National Key Basic Research Program of China (973 program) under Grant No.2010CB328204National High Technology Research and Development Program of China (863 program) under Grant No.2009AA01Z255+3 种基金National Natural Science Foundation of China under Grant No. 60932004RFDP Project under Grant No.20090005110013111 Project of China under Grant No.B07005China Fundamental Research Funds for the Central Universities
文摘A novel routing architecture named DREAMSCAPE is presented to solve the problem of path computation in multi-layer, multi-domain and multi-constraints scenarios, which includes Group Engine (GE) and Unit Engine (UE). GE, UE and their cooperation relationship form the main feature of DREAMSCAPE, i.e. Dual Routing Engine (DRE). Based on DRE, two routing schemes are proposed, which are DRE Forward Path Computation (DRE-FPC) and Hierarchical DRE Backward Recursive PCE-based Computation (HDRE-BRPC). In order to validate various intelligent networking technologies of large-scale heterogeneous optical networks, a DRE-based transport optical networks testbed is built with 1000 GMPLS-based control nodes and 5 optical transport nodes. The two proposed routing schemes, i.e. DRE-FPC and HDRE-BRPC, are validated on the testbed, compared with traditional Hierarchical Routing (HR) scheme. Experimental results show a good performance of DREAMSCAPE.
基金The 2023 Guangxi University Young and Middle-Aged Teachers’Scientific Research Basic Ability Improvement Project“Research on Seismic Performance of Prefabricated CFST Column-SRC Beam Composite Joints”(2023KY1204)The 2023 Guangxi Vocational Education Teaching Reform Research Project“Research and Practice on the Cultivation of Digital Talents in Prefabricated Buildings in the Context of Deepening the Integration of Industry and Education”(GXGZJG2023B052)The 2022 Guangxi Polytechnic of Construction School-Level Teaching Innovation Team Project“Prefabricated and Intelligent Teaching Innovation Team”(Gui Jian Yuan Ren[2022]No.15)。
文摘This paper discusses the digital application and benefit analysis of building information model(BIM)technology in the large-scale comprehensive development project of the Guangxi headquarters base.The project covers a total area of 92,100 square meters,with a total construction area of 379,700 square meters,including a variety of architectural forms.Through three-dimensional modeling and simulation analysis,BIM technology significantly enhances the design quality and efficiency,shortens the design cycle by about 20%,and promotes the collaboration and integration of project management,improving the management efficiency by about 25%.During the construction phase,the collision detection and four-dimensional visual management functions of BIM technology have improved construction efficiency by about 15%and saved the cost by about 10%.In addition,BIM technology has promoted green building and sustainable development,achieved the dual improvement of technical and economic indicators and social and economic benefits,set an example for enterprises in digital transformation,and opened up new market businesses.
基金Project(ZR2014FM036)supported by Shandong Provincial Natural Science Foundation of ChinaProject(ZR2010FZ001)supported by the Key Program of Shandong Provincial Natural Science Foundation of China
文摘In order to increase productivity and reduce energy consumption of steelmaking-continuous casting(SCC) production process, especially with complicated technological routes, the cross entropy(CE) method was adopted to optimize the SCC production scheduling(SCCPS) problem. Based on the CE method, a matrix encoding scheme was proposed and a backward decoding method was used to generate a reasonable schedule. To describe the distribution of the solution space, a probability distribution model was built and used to generate individuals. In addition, the probability updating mechanism of the probability distribution model was proposed which helps to find the optimal individual gradually. Because of the poor stability and premature convergence of the standard cross entropy(SCE) algorithm, the improved cross entropy(ICE) algorithm was proposed with the following improvements: individual generation mechanism combined with heuristic rules, retention mechanism of the optimal individual, local search mechanism and dynamic parameters of the algorithm. Simulation experiments validate that the CE method is effective in solving the SCCPS problem with complicated technological routes and the ICE algorithm proposed has superior performance to the SCE algorithm and the genetic algorithm(GA).
基金supported by National Key R&D Program of China(2017YFB0903504)
文摘In the context of constructing Global Energy Interconnection(GEI), energy storage technology, as one of the important basic supporting technologies in power system, will play an important role in the energy configuration and optimization. Based on the most promising battery energy storage technology, this paper introduces the current status of the grid technology, the application of large-scale energy storage technology and the supporting role of battery energy storage for GEI. Based on several key technologies of large-scale battery energy storage system, preliminary analysis of the standard system construction of energy storage system is made, and the future prospect is put forward.
基金supported by Natural Science Foundation Project of Gansu Provincial Science and Technology Department(No.1506RJZA084)Gansu Provincial Education Department Scientific Research Fund Grant Project(No.1204-13).
文摘To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.
文摘Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.
基金This project was funded by the National Natural Science Foundation of China(41871320,61872139)the Provincial and Municipal Joint Fund of Hunan Provincial Natural Science Foundation of China(2018JJ4052)+2 种基金Hunan Provincial Natural Science Foundation of China(2017JJ2081)the Key Project of Hunan Provincial Education Department(19A172)the Scientific Research Fund of Hunan Provincial Education Department(18K060).
文摘In the large-scale logistics distribution of single logistic center,the method based on traditional genetic algorithm is slow in evolution and easy to fall into the local optimal solution.Addressing at this issue,we propose a novel approach of exploring hybrid genetic algorithm based large-scale logistic distribution for BBG supermarket.We integrate greedy algorithm and hillclimbing algorithm into genetic algorithm.Greedy algorithm is applied to initialize the population,and then hill-climbing algorithm is used to optimize individuals in each generation after selection,crossover and mutation.Our approach is evaluated on the dataset of BBG Supermarket which is one of the top 10 supermarkets in China.Experimental results show that our method outperforms some other methods in the field.
基金funded by the National Key Research and Development Program Project 2022YFB4300404.
文摘The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.
文摘Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation of intelligent ships,route planning technologies have developed many route planning algorithms that prioritize economy and safety.This paper conducts an in-depth study of algorithm efficiency for a route planning problem,proposing an intelligent ship route planning algorithm based on the adaptive step size Informed-RRT^(*).This algorithm can quickly plan a short route according to automatic obstacle avoidance and is suitable for planning the routes of intelligent ships.Results show that the adaptive step size Informed-RRT^(*) algorithm can shorten the optimal route length by approximately 13.05%while ensuring the running time of the planning algorithm and avoiding approximately 23.64%of redundant sampling nodes.The improved algorithm effectively circumvents unnecessary calculations and reduces a large amount of redundant sampling data,thus improving the efficiency of route planning.In a complex water environment,the unique adaptive step size mechanism enables this algorithm to prevent restricted search tree expansion,showing strong search ability and robustness,which is of practical significance for the development of intelligent ships.
文摘With the continuous improvement of the scale and complexity of large-scale events,temporary teams,as the core carrier of event execution,their relationship construction quality directly affects the event effectiveness.From the perspective of intelligent collaboration and combined with technological innovation applications,this paper discusses the related issues of relationship construction of temporary teams in large-scale events.It first expounds the research background and significance,then sorts out the theoretical basis of intelligent collaboration and temporary team relationship construction,analyzes the current dilemmas in the relationship construction of temporary teams in large-scale events,and then puts forward the relationship construction path based on technological innovation applications,verifies it with specific cases,and finally summarizes the research conclusions and prospects.The study aims to provide theoretical reference and practical guidance for improving the collaboration efficiency and stability of temporary teams in large-scale events.
