The Experts below are selected from a list of 2742 Experts worldwide ranked by ideXlab platform

Yunhe Hou - One of the best experts on this subject based on the ideXlab platform.

  • Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
    IEEE Transactions on Smart Grid, 2018
    Co-Authors: Shunbo Lei, Jianhui Wang, Chen Chen, Yunhe Hou
    Abstract:

    Truck-mounted mobile Emergency Generators (MEGs) are critical flexibility resources of distribution systems (DSs) for resilient Emergency response to natural disasters. However, they are currently under-utilized. For better utilization, this paper proposes dispatching MEGs as distributed Generators in DSs to restore critical loads by forming multiple microgrids (MGs). As the travel time of MEGs on road networks (RNs) can greatly influence the outage duration of critical loads, a two-stage dispatch framework consisting of pre-positioning and real-time allocation is introduced, and the traffic issue is considered via the vehicle routing problem. Pre-positioning places MEGs in staging locations prior to a natural disaster, while real-time allocation sends MEGs from staging locations to restore critical loads by forming MGs in DSs after the natural disaster strikes. Specifically, with the objective of minimizing the expected outage duration of loads considering their priorities and demand sizes, pre-positioning is done via a scenario-based two-stage stochastic optimization problem, in which the first-stage pre-positioning decisions are evaluated by numbers of second-stage real-time allocation problems corresponding to considered scenarios of DS damage and RN damage/congestion. A scenario decomposition algorithm is applied to solve this problem. Illustrative cases demonstrate the effectiveness of the proposed dispatch scheme and algorithm.

  • Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Shunbo Lei, Jianhui Wang, Chen Chen, Yunhe Hou
    Abstract:

    postprin

Shunbo Lei - One of the best experts on this subject based on the ideXlab platform.

  • Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
    IEEE Transactions on Smart Grid, 2018
    Co-Authors: Shunbo Lei, Jianhui Wang, Chen Chen, Yunhe Hou
    Abstract:

    Truck-mounted mobile Emergency Generators (MEGs) are critical flexibility resources of distribution systems (DSs) for resilient Emergency response to natural disasters. However, they are currently under-utilized. For better utilization, this paper proposes dispatching MEGs as distributed Generators in DSs to restore critical loads by forming multiple microgrids (MGs). As the travel time of MEGs on road networks (RNs) can greatly influence the outage duration of critical loads, a two-stage dispatch framework consisting of pre-positioning and real-time allocation is introduced, and the traffic issue is considered via the vehicle routing problem. Pre-positioning places MEGs in staging locations prior to a natural disaster, while real-time allocation sends MEGs from staging locations to restore critical loads by forming MGs in DSs after the natural disaster strikes. Specifically, with the objective of minimizing the expected outage duration of loads considering their priorities and demand sizes, pre-positioning is done via a scenario-based two-stage stochastic optimization problem, in which the first-stage pre-positioning decisions are evaluated by numbers of second-stage real-time allocation problems corresponding to considered scenarios of DS damage and RN damage/congestion. A scenario decomposition algorithm is applied to solve this problem. Illustrative cases demonstrate the effectiveness of the proposed dispatch scheme and algorithm.

  • Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Shunbo Lei, Jianhui Wang, Chen Chen, Yunhe Hou
    Abstract:

    postprin

Daniel S. Kirschen - One of the best experts on this subject based on the ideXlab platform.

  • ISGT - 1 Real-Time Digital Simulation of Microgrid Control Strategies
    2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2020
    Co-Authors: Chanaka Keerthisinghe, Daniel S. Kirschen
    Abstract:

    This paper evaluates microgrid control strategies prior to actual implementation using a real-time digital simulator. The microgrid model includes photovoltaic generation, a battery, an Emergency Generator, loads and a vehicle-to-grid enabled electric vehicle charging station. Three operational scenarios are studied: grid-connected operation; seamless transition to islanded mode with the battery inverter operating in grid-forming mode; and islanded operation using the Emergency Generator when the battery is discharged.

Chen Chen - One of the best experts on this subject based on the ideXlab platform.

  • Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
    IEEE Transactions on Smart Grid, 2018
    Co-Authors: Shunbo Lei, Jianhui Wang, Chen Chen, Yunhe Hou
    Abstract:

    Truck-mounted mobile Emergency Generators (MEGs) are critical flexibility resources of distribution systems (DSs) for resilient Emergency response to natural disasters. However, they are currently under-utilized. For better utilization, this paper proposes dispatching MEGs as distributed Generators in DSs to restore critical loads by forming multiple microgrids (MGs). As the travel time of MEGs on road networks (RNs) can greatly influence the outage duration of critical loads, a two-stage dispatch framework consisting of pre-positioning and real-time allocation is introduced, and the traffic issue is considered via the vehicle routing problem. Pre-positioning places MEGs in staging locations prior to a natural disaster, while real-time allocation sends MEGs from staging locations to restore critical loads by forming MGs in DSs after the natural disaster strikes. Specifically, with the objective of minimizing the expected outage duration of loads considering their priorities and demand sizes, pre-positioning is done via a scenario-based two-stage stochastic optimization problem, in which the first-stage pre-positioning decisions are evaluated by numbers of second-stage real-time allocation problems corresponding to considered scenarios of DS damage and RN damage/congestion. A scenario decomposition algorithm is applied to solve this problem. Illustrative cases demonstrate the effectiveness of the proposed dispatch scheme and algorithm.

  • Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Shunbo Lei, Jianhui Wang, Chen Chen, Yunhe Hou
    Abstract:

    postprin

Jianhui Wang - One of the best experts on this subject based on the ideXlab platform.

  • Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
    IEEE Transactions on Smart Grid, 2018
    Co-Authors: Shunbo Lei, Jianhui Wang, Chen Chen, Yunhe Hou
    Abstract:

    Truck-mounted mobile Emergency Generators (MEGs) are critical flexibility resources of distribution systems (DSs) for resilient Emergency response to natural disasters. However, they are currently under-utilized. For better utilization, this paper proposes dispatching MEGs as distributed Generators in DSs to restore critical loads by forming multiple microgrids (MGs). As the travel time of MEGs on road networks (RNs) can greatly influence the outage duration of critical loads, a two-stage dispatch framework consisting of pre-positioning and real-time allocation is introduced, and the traffic issue is considered via the vehicle routing problem. Pre-positioning places MEGs in staging locations prior to a natural disaster, while real-time allocation sends MEGs from staging locations to restore critical loads by forming MGs in DSs after the natural disaster strikes. Specifically, with the objective of minimizing the expected outage duration of loads considering their priorities and demand sizes, pre-positioning is done via a scenario-based two-stage stochastic optimization problem, in which the first-stage pre-positioning decisions are evaluated by numbers of second-stage real-time allocation problems corresponding to considered scenarios of DS damage and RN damage/congestion. A scenario decomposition algorithm is applied to solve this problem. Illustrative cases demonstrate the effectiveness of the proposed dispatch scheme and algorithm.

  • Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Shunbo Lei, Jianhui Wang, Chen Chen, Yunhe Hou
    Abstract:

    postprin