Resilience-Oriented Distribution System Restoration Considering Mobile Emergency Resource Dispatch in Transportation System

Xu, Yin; Wang, Ying; He, Jinghan; Su, Mingyu; Ni, Pinghao

doi:10.1109/access.2019.2921017

Cited by 78 publications

(39 citation statements)

References 32 publications

(42 reference statements)

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“…The scalability of RMPS and MG scheduled islanding has been demonstrated in [16]- [32], for a wide range of power systems aspects, including reliability and resilience improvement [20], [23]- [26], [28]- [30], as well as operational performance enhancement [16]- [19], [21]- [22], [32].…”

Section: Proposed Rmps Allocation Methods For Mgs Support During mentioning

confidence: 99%

“…Prepositioning and allocation of MPS for MG restoration of critical loads in the context of natural disasters are addressed in [24], whereas the economically optimal location during normal operating condition is additionally tackled in [25]. Resilience applications are depicted in [26]- [28] addressing MPS commissioning logistics, including the influence of transportation and repair crews. In [29] a two-stage stochastic recovery framework using MERs reduces the consumers' outage time duration, while the total cost of the system is minimized using transportable energy storage systems (TESSs) [30].…”

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confidence: 99%

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Intelligent RMPS Allocation for Microgrids Support During Scheduled Islanded Operation

et al. 2020

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New opportunities enabled by renewable mobile power stations (RMPSs), in association with microgrids (MGs) ability to operate islanded to the main grid, present a likely solution to ensure power system novel reliability requirements in face of the increasing number of severe disruptive events. In this perspective, this paper proposes a novel intelligent RMPS allocation method to support MGs during scheduled islanded operation. In this mode, the isolated operation of a MG is beforehand planned to mitigate the effects caused by possible predictable contingencies, e.g. weather-related events, as well as programmed maintenance. For this, first a novel energy management strategy (EMS) based on dynamic programming specifically designed for MG scheduled islanded operation is proposed. Next, a particle swarm optimization (PSO) method modified to ensure a continuous search space in the face of discrete load shedding policies is developed to determine the adequate allocation of RMPS. The proposed method is simulated considering different scenarios for a MG system considering local distributed generation capacity, electric vehicles penetration, load shedding based on priority groups, as well as technical and operational limits. The obtained results showcase the proposed approach ability to meaningfully improve MG service capacity during scheduled islanded operation.

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Section: Proposed Rmps Allocation Methods For Mgs Support During mentioning

confidence: 99%

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confidence: 99%

Intelligent RMPS Allocation for Microgrids Support During Scheduled Islanded Operation

et al. 2020

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“…Several proactive planning measures can be applied to enhancing the distribution system resilience. From an operational standpoint, a decision-maker can improve resilience by allocating resources to lessen the average impact (L i ), decrease the damage assessment time (t r -t pe ) to quickly enter the restorative state and/or apply advanced restoration to decrease Algorithm 1: Probabilistic loss for a given HILP event 1 Given: Weather data, Distribution system model 2 Step I: Fragility Modeling 3 Obtain PDF p(I) of the wind-speed profile for a given geographical region using weather data 4 for each distribution lines do 5 Generate fragility curves 6 Obtain component failure probabilities P l (ω) 7 Step II: Monte-Carlo Simulation 8 for each event in I do 9 Component level impact→ System level impact 10 Evaluate system loss for given event U i (I) 11 if enough trials, then 12 Evaluate average loss function 13 else 14 Go to step 9 15 Step III: Probabilistic loss 16 Compute risk-based resilience metrics 17 Output: V aR α , CV aR α impact in restorative state (t ir -t r ). Two specific proactive planning measures and approach to model their impact on resilience curve are discussed in this section.…”

Section: Model the Impacts Of Proactive Planningmentioning

confidence: 99%

“…Furthermore, the proposed resilience metrics were mostly dimensionless quantities making it difficult to associate those to real-world consequences. Numerous optimizationbased restoration methods have also been proposed to quantify the resilience based on the amount and duration of critical loads restored [8]- [12]. Some approaches emphasize on resilience driven, adaptive restoration strategies [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Risk-Based Probabilistic Quantification of Power Distribution System Operational Resilience

Poudel

Dubey

Bose

2020

IEEE Systems Journal

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It is of growing concern to ensure the resilience in electricity infrastructure systems to extreme weather events with the help of appropriate hardening measures and new operational procedures. An effective mitigation strategy requires a quantitative metric for resilience that can not only model the impacts of the unseen catastrophic events for complex electric power distribution networks but also evaluate the potential improvements offered by different planning measures. In this paper, we propose probabilistic metrics to quantify the operational resilience of the electric power distribution systems to highimpact low-probability (HILP) events. Specifically, we define two risk-based measures: Value-at-Risk (V aRα) and Conditional Value-at-Risk (CV aRα) that measure resilience as the maximum loss of energy and conditional expectation of a loss of energy, respectively for the events beyond a prespecified risk threshold, α. Next, we present a simulation-based framework to evaluate the proposed resilience metrics for different weather scenarios with the help of modified IEEE 37-bus and IEEE 123-bus system. The simulation approach is also extended to evaluate the impacts of different planning measures on the proposed resilience metrics. Her research focus is on the analysis, operation, and planning of the modern power distribution systems for enhanced service quality and grid resilience. At WSU, her lab focuses on developing new planning and operational tools for the current and future power distribution systems that help in effective integration of distributed energy resources and responsive loads.Anjan Bose (LF'89) received the B. Tech. (Hons.) degree from the

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“…that year. The rise of active distribution systems opens the way of deploying resilient smart grid via microgrid generation [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Prevention and Survivability for Power Distribution Resilience: A Multi-Criteria Renewables Expansion Model

Wang

Jin

2020

IEEE Access

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Distributed energy resources are capable of enhancing grid resilience through island operations in contingency. This paper proposes a multi-year, multi-criteria generation expansion model to achieve distribution power resilience through renewable energy integration. In cases that distribution circuits or fuel lifeline are destroyed post natural disasters, wind-and solar-based generators form island microgrids to power the critical load. The goal is to determine the sizing, siting and maintenance of distributed energy resources such that system cost and power shortage in contingency are minimized. Moment methods and central limit theorem are used to characterize the spatial climate uncertainty, generation intermittency, and voltage variation. The research contributions are twofold. First, the expansion model achieves triple goals by meeting the annual load growth, reducing the carbon footprint, and enhancing the grid resilience manifested as prevention and survivability. Second, we present an improved direct zigzag algorithm to search for the Pareto solutions. Numerical examples show that the zigzag search outperforms evolutionary-based algorithms as it can identify higher-quality non-dominant solutions by exploring a wider Pareto frontier.

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Resilience-Oriented Distribution System Restoration Considering Mobile Emergency Resource Dispatch in Transportation System

Cited by 78 publications

References 32 publications

Intelligent RMPS Allocation for Microgrids Support During Scheduled Islanded Operation

Intelligent RMPS Allocation for Microgrids Support During Scheduled Islanded Operation

Risk-Based Probabilistic Quantification of Power Distribution System Operational Resilience

Prevention and Survivability for Power Distribution Resilience: A Multi-Criteria Renewables Expansion Model

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