In modern giant buildings,in order to improve energy utilization efficiency, cooling systems have developed from conventional chillers alone to smart energy net which includes chillers,ice storage,ground-source heat p...In modern giant buildings,in order to improve energy utilization efficiency, cooling systems have developed from conventional chillers alone to smart energy net which includes chillers,ice storage,ground-source heat pump,combined cooling heating and power( CCHP) and so on. The reasonable distribution of load is the key to guarantee such system in economical operation.Based on typical multi-type cooling system,economic models of different devices are presented and real-time intelligent economic scheduling with the approach of mixed integer programming is carried out. This algorithm has been applied in a certain building of Shanghai and results of simulation show that it is able to provide guidance on intelligent economic scheduling for multi-type cooling system.展开更多
A genetic algorithm (GA) and a hybrid genetic algorithm (HGA) were used for optimal scheduling of public vehicles based on their actual operational environments. The performance for three kinds of vehicular levels...A genetic algorithm (GA) and a hybrid genetic algorithm (HGA) were used for optimal scheduling of public vehicles based on their actual operational environments. The performance for three kinds of vehicular levels were compared using one-point and two-point crossover operations. The vehicle scheduling times are improved by the intelligent characteristics of the GA. The HGA, which integrates the genetic algorithm with a tabu search, further improves the convergence performance and the optimization by avoiding the premature convergence of the GA. The results show that intelligent scheduling of public vehicles based on the HGA overcomes the shortcomings of traditional scheduling methods. The vehicle operation management efficiency is improved by this essential technology for intelligent scheduling of public vehicles.展开更多
In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,e...In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.展开更多
With the application of various information technologies in smart manufacturing,new intelligent production mode puts forward higher demands for real-time and robustness of production scheduling.For the production sche...With the application of various information technologies in smart manufacturing,new intelligent production mode puts forward higher demands for real-time and robustness of production scheduling.For the production scheduling problem in large-scale manufacturing environment,digital twin(DT)places high demand on data processing capability of the terminals.It requires both global prediction and real-time response abilities.In order to solve the above problem,a DT-based edge-cloud collaborative intelligent production scheduling(DTECCS)system was proposed,and the scheduling model and method were introduced.DT-based edge-cloud collaboration(ECC)can predict the production capacity of each workshop,reassemble customer orders,optimize the allocation of global manufacturing resources in the cloud,and carry out distributed scheduling on the edge-side to improve scheduling and tasks processing efficiency.In the production process,the DTECCS system adjusts scheduling strategies in real-time,responding to changes in production conditions and order fluctuations.Finally,simulation results show the effectiveness of DTECCS system.展开更多
The growing integration of renewable energy generation manifests as an effective strategy for reducing carbon emissions.This paper strives to efficiently approximate the set of optimal scheduling plans(OSPs)to enhance...The growing integration of renewable energy generation manifests as an effective strategy for reducing carbon emissions.This paper strives to efficiently approximate the set of optimal scheduling plans(OSPs)to enhance the performance of the steady-state adaptive cruise method(SACM)of power grid,improving the ability of dealing with operational uncertainties.Initially,we provide a mathematical definition of the exact box-constrained economic operating region(EBC-EOR)for the power grid and its dispatchable components.Following this,we introduce an EBC-EOR formulation algorithm and the corresponding bi-level optimization models designed to explore the economic operating boundaries.In addition,we propose an enhanced big-M method to expedite the computation of the EBC-EOR.Finally,the effectiveness of the EBC-EOR formulation,its economic attributes,correlation with the scheduling plan underpinned by model predictive control,and the significant improvement in computational efficiency(over twelvefold)are verified through case studies conducted on two test systems..展开更多
基金the Project of Science and Technology Commission of Shanghai Municipality,China(No.12dz1200203)the Chongming Smart Grid National Sci-Tech Support Plan of China(No.2013BAA01B04)
文摘In modern giant buildings,in order to improve energy utilization efficiency, cooling systems have developed from conventional chillers alone to smart energy net which includes chillers,ice storage,ground-source heat pump,combined cooling heating and power( CCHP) and so on. The reasonable distribution of load is the key to guarantee such system in economical operation.Based on typical multi-type cooling system,economic models of different devices are presented and real-time intelligent economic scheduling with the approach of mixed integer programming is carried out. This algorithm has been applied in a certain building of Shanghai and results of simulation show that it is able to provide guidance on intelligent economic scheduling for multi-type cooling system.
基金the National High-Tech Research and Development (863) Program of China (No. 2004AA133020)
文摘A genetic algorithm (GA) and a hybrid genetic algorithm (HGA) were used for optimal scheduling of public vehicles based on their actual operational environments. The performance for three kinds of vehicular levels were compared using one-point and two-point crossover operations. The vehicle scheduling times are improved by the intelligent characteristics of the GA. The HGA, which integrates the genetic algorithm with a tabu search, further improves the convergence performance and the optimization by avoiding the premature convergence of the GA. The results show that intelligent scheduling of public vehicles based on the HGA overcomes the shortcomings of traditional scheduling methods. The vehicle operation management efficiency is improved by this essential technology for intelligent scheduling of public vehicles.
基金supported by the National Natural Science Foundation of China(62172033).
文摘In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.
基金supported by the 2020 Industrial Internet Innovation Development Project of Ministry of Industry and Information Technology of P.R.Chinathe State Grid Liaoning Electric Power Supply Co.,Ltd.,Comprehensive Security Defense Platform Project for Industrial/Enterprise Networks。
文摘With the application of various information technologies in smart manufacturing,new intelligent production mode puts forward higher demands for real-time and robustness of production scheduling.For the production scheduling problem in large-scale manufacturing environment,digital twin(DT)places high demand on data processing capability of the terminals.It requires both global prediction and real-time response abilities.In order to solve the above problem,a DT-based edge-cloud collaborative intelligent production scheduling(DTECCS)system was proposed,and the scheduling model and method were introduced.DT-based edge-cloud collaboration(ECC)can predict the production capacity of each workshop,reassemble customer orders,optimize the allocation of global manufacturing resources in the cloud,and carry out distributed scheduling on the edge-side to improve scheduling and tasks processing efficiency.In the production process,the DTECCS system adjusts scheduling strategies in real-time,responding to changes in production conditions and order fluctuations.Finally,simulation results show the effectiveness of DTECCS system.
基金supported by the Science and Technology Project of State Grid Corporation(No.5400-202099286A-0-0-00).
文摘The growing integration of renewable energy generation manifests as an effective strategy for reducing carbon emissions.This paper strives to efficiently approximate the set of optimal scheduling plans(OSPs)to enhance the performance of the steady-state adaptive cruise method(SACM)of power grid,improving the ability of dealing with operational uncertainties.Initially,we provide a mathematical definition of the exact box-constrained economic operating region(EBC-EOR)for the power grid and its dispatchable components.Following this,we introduce an EBC-EOR formulation algorithm and the corresponding bi-level optimization models designed to explore the economic operating boundaries.In addition,we propose an enhanced big-M method to expedite the computation of the EBC-EOR.Finally,the effectiveness of the EBC-EOR formulation,its economic attributes,correlation with the scheduling plan underpinned by model predictive control,and the significant improvement in computational efficiency(over twelvefold)are verified through case studies conducted on two test systems..