Resilience is the ability of a system to withstand and stay operational in the face of an unexpected disturbance or unpredicted changes. Recent studies on air transport system resilience focus on topology characterist...Resilience is the ability of a system to withstand and stay operational in the face of an unexpected disturbance or unpredicted changes. Recent studies on air transport system resilience focus on topology characteristics after the disturbance and measure the robustness of the network with respect to connectivity. The dynamic processes occurring at the node and link levels are often ignored. Here we analyze airport network resilience by considering both structural and dynamical aspects. We develop a simulation model to study the operational performance of the air transport system when airports operate at degraded capacity rather than completely shutting down. Our analyses show that the system deteriorates soon after disruptive events occur but returns to an acceptable level after a period of time. Static resilience of the airport network is captured by a phase transition in which a small change to airport capacity will result in a sharp change in system punctuality. After the phase transition point, decreasing airport capacity has little impact on system performance. Critical airports which have significant influence on the performance of whole system are identified, and we find that some of these cannot be detected based on the analysis of network structural indicators alone. Our work shows that air transport system’s resilience can be well understood by combining network science and operational dynamics.展开更多
To improve the resilience of distribution networks(DNs),a multi-stage dynamic recovery strategy is proposed in this paper,which is designed for post-disaster DN considering an integrated energy system(IES)and transpor...To improve the resilience of distribution networks(DNs),a multi-stage dynamic recovery strategy is proposed in this paper,which is designed for post-disaster DN considering an integrated energy system(IES)and transportation network(TN).First,the emergency response quickly increases the output of gas turbines(GTs)in the natural gas network(NGN),and responsively reconfigures the DN in microgrids,to maximize the amount of loads to be restored.The single-commodity flow model is adopted to construct spanning tree constraints.Then,in the second stage of energy storage recovery,mobile energy storage systems(MESSs)are deployed to cover the shortages of power demands,i.e.,to further restore the loads after evaluating the load recovery situation.The Floyd algorithm based dynamic traffic assignment(DTA)is selected to obtain the optimal path of the MESSs.In the third stage,the outputs of various post-disaster recovery measures are adjusted to achieve an economically optimized operation.Case studies demonstrate the effectiveness of the proposed dynamic post-disaster recovery strategy.展开更多
The power and transportation systems are urban interdependent critical infrastructures(CIs).During the post-disaster restoration process,transportation mobility and power restoration process are interdependent,and the...The power and transportation systems are urban interdependent critical infrastructures(CIs).During the post-disaster restoration process,transportation mobility and power restoration process are interdependent,and their functionalities significantly affect the well-beings of other urban CIs.Therefore,to enhance the resilience of urban CIs,successful recovery strategies should promote CI function cooperatively and synergistically to distribute goods and services efficiently.This paper develops an integrative framework that addresses the challenges of enhancing the recovery efficiency of urban power and transportation systems in short-term recovery period.Specifically,the post-storm recovery process is considered as a scheduling problem with the constraints representingcrew dispatch,equipment and fuel limit.We propose a new framework for co-optimizing the recovery scheduling of power and transportation systems,respecting precedency requirement and network constraints.The advantages and benefits of co-optimized recovery scheduling are validated in a testing system.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 61773203, U1833126, 61304190)the Open Funds of Graduate Innovation Base (Lab) of Nanjing University of Aeronautics and Astronautics of China (No. kfjj20180703)+1 种基金the State Key Laboratory of Air Traffic Management System and Technology of China (No. SKLATM201707)the Hong Kong Research Grant Council General Research Fund of China (No. 11209717)
文摘Resilience is the ability of a system to withstand and stay operational in the face of an unexpected disturbance or unpredicted changes. Recent studies on air transport system resilience focus on topology characteristics after the disturbance and measure the robustness of the network with respect to connectivity. The dynamic processes occurring at the node and link levels are often ignored. Here we analyze airport network resilience by considering both structural and dynamical aspects. We develop a simulation model to study the operational performance of the air transport system when airports operate at degraded capacity rather than completely shutting down. Our analyses show that the system deteriorates soon after disruptive events occur but returns to an acceptable level after a period of time. Static resilience of the airport network is captured by a phase transition in which a small change to airport capacity will result in a sharp change in system punctuality. After the phase transition point, decreasing airport capacity has little impact on system performance. Critical airports which have significant influence on the performance of whole system are identified, and we find that some of these cannot be detected based on the analysis of network structural indicators alone. Our work shows that air transport system’s resilience can be well understood by combining network science and operational dynamics.
基金supported by the Science and Technology Project of the State Grid Corporation of China“Research on resilience technology and application foundation of intelligent distribution network based on integrated energy system”(No.52060019001H).
文摘To improve the resilience of distribution networks(DNs),a multi-stage dynamic recovery strategy is proposed in this paper,which is designed for post-disaster DN considering an integrated energy system(IES)and transportation network(TN).First,the emergency response quickly increases the output of gas turbines(GTs)in the natural gas network(NGN),and responsively reconfigures the DN in microgrids,to maximize the amount of loads to be restored.The single-commodity flow model is adopted to construct spanning tree constraints.Then,in the second stage of energy storage recovery,mobile energy storage systems(MESSs)are deployed to cover the shortages of power demands,i.e.,to further restore the loads after evaluating the load recovery situation.The Floyd algorithm based dynamic traffic assignment(DTA)is selected to obtain the optimal path of the MESSs.In the third stage,the outputs of various post-disaster recovery measures are adjusted to achieve an economically optimized operation.Case studies demonstrate the effectiveness of the proposed dynamic post-disaster recovery strategy.
基金supported by the U.S.National Science Foundation Project(No.ECCS-171121)CARRER Award(No.CMMI-1554559)CSUFRD-IoT Award.
文摘The power and transportation systems are urban interdependent critical infrastructures(CIs).During the post-disaster restoration process,transportation mobility and power restoration process are interdependent,and their functionalities significantly affect the well-beings of other urban CIs.Therefore,to enhance the resilience of urban CIs,successful recovery strategies should promote CI function cooperatively and synergistically to distribute goods and services efficiently.This paper develops an integrative framework that addresses the challenges of enhancing the recovery efficiency of urban power and transportation systems in short-term recovery period.Specifically,the post-storm recovery process is considered as a scheduling problem with the constraints representingcrew dispatch,equipment and fuel limit.We propose a new framework for co-optimizing the recovery scheduling of power and transportation systems,respecting precedency requirement and network constraints.The advantages and benefits of co-optimized recovery scheduling are validated in a testing system.
