Post-Event Resiliency-Driven Strategy Dispatching Mobile Power Sources Considering Transportation System Constraints

Erenoğlu, Ayşe Kübra; Erdinç, Ozan; Sancar, Semanur; Catalào, João P. S.

doi:10.1109/iceee52452.2021.9415932

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…Methods Adopted in the References [14,15] Two-stage restoration scheme is designed to facilitate the distribution system restoration following the high-impact low-probability (HILP) seismic disasters.…”

Section: Referencesmentioning

confidence: 99%

Mobile Emergency Power Source Configuration Scheme considering Dynamic Characteristics of a Transportation Network

Huang¹,

Tang²,

Wu³

et al. 2021

Processes

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Recently, with the large scale of power grids and the increase in frequency of extreme weather, the safe and stable operation of power systems is facing great challenges. Therefore, mobile emergency power source (MEPS) are a promising and feasible way to deal with extreme weather and reduce economic losses. However, the current urban power grid and transportation network are closely coupled, and the congested traffic hinders the rapid configuration of MEPSs. Therefore, this paper proposes an MEPS configuration scheme considering real-time traffic conditions. Firstly, the dynamic road traffic index (DRTI) is defined, which can fully describe the dynamic characteristics of traffic. The wavelet neural network (WNN) is used to predict the traffic flow. Then, combined with the knowledge of graph theory, an A-Star algorithm (AS) is used to determine the optimal path. Secondly, the optimal installation location of MEPSs is determined by forward–backward sweep method in distribution network. Finally, the feasibility, accuracy, and time cost of the proposed method are verified by numerical simulations, which can meet the requirements of online application.

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Section: Referencesmentioning

confidence: 99%

Mobile Emergency Power Source Configuration Scheme considering Dynamic Characteristics of a Transportation Network

Huang¹,

Tang²,

Wu³

et al. 2021

Processes

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Microgrids and Resilience: A Review

Hamidieh

Ghassemi

2022

IEEE Access

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Supervised learning methods have been found to exhibit inductive biases favoring simpler features. When such features are spuriously correlated with the label, this can result in suboptimal performance on minority subgroups. Despite the growing popularity of methods which learn from unlabeled data, the extent to which these representations encode spurious features is unclear. In this work, we explore the impact of spurious features on Self-Supervised Learning (SSL) for visual representation learning. We first empirically show that commonly used augmentations in SSL can cause undesired invariances in the image space, and illustrate this with a simple example. We further show that classical approaches in combating spurious correlations, such as dataset re-sampling during SSL, do not consistently lead to invariant representations. Motivated by these findings, we propose LATETVG to remove spurious information from these representations during pretraining, by regularizing later layers of the encoder via pruning. We find that our method produces representations which outperform the baselines on several benchmarks, without the need for group or label information during SSL.

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Modelling Frameworks Applied in Smart Distribution Network Resiliency and Restoration

Alghamdi

Jayaweera

2022

2022 IEEE 16th International Conference on Compatibility, Power Electronics, and Power Engineering (CPE-POWERENG)

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Post-Event Resiliency-Driven Strategy Dispatching Mobile Power Sources Considering Transportation System Constraints

Cited by 5 publications

References 14 publications

Mobile Emergency Power Source Configuration Scheme considering Dynamic Characteristics of a Transportation Network

Mobile Emergency Power Source Configuration Scheme considering Dynamic Characteristics of a Transportation Network

Microgrids and Resilience: A Review

Modelling Frameworks Applied in Smart Distribution Network Resiliency and Restoration

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