Dynamic Network Clustering for Distribution System Resilience Against Typhoon Events

Cahig, Christian; Villanueva, Jake Jay; Bersano, Rogelio F.; Pacis, Michael C.

doi:10.1109/hnicem.2018.8666431

2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environm 2018

DOI: 10.1109/hnicem.2018.8666431

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Dynamic Network Clustering for Distribution System Resilience Against Typhoon Events

Christian Cahig

Jake Jay Villanueva

Rogelio F. Bersano

et al.

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Cited by 2 publications

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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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Microgrids and Resilience: A Review

Hamidieh

Ghassemi

2022

IEEE Access

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Networked Microgrids: A Review on Configuration, Operation, and Control Strategies

Bordbari,

Nasiri

2024

Energies

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The increasing impact of climate change and rising occurrences of natural disasters pose substantial threats to power systems. Strengthening resilience against these low-probability, high-impact events is crucial. The proposition of reconfiguring traditional power systems into advanced networked microgrids (NMGs) emerges as a promising solution. Consequently, a growing body of research has focused on NMG-based techniques to achieve a more resilient power system. This paper provides an updated, comprehensive review of the literature, particularly emphasizing two main categories: networked microgrids’ configuration and networked microgrids’ control. The study explores key facets of NMG configurations, covering formation, power distribution, and operational considerations. Additionally, it delves into NMG control features, examining their architecture, modes, and schemes. Each aspect is reviewed based on problem modeling/formulation, constraints, and objectives. The review examines findings and highlights the research gaps, focusing on key elements such as frequency and voltage stability, reliability, costs associated with remote switches and communication technologies, and the overall resilience of the network. On that basis, a unified problem-solving approach addressing both the configuration and control aspects of stable and reliable NMGs is proposed. The article concludes by outlining potential future trends, offering valuable insights for researchers in the field.

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Dynamic Network Clustering for Distribution System Resilience Against Typhoon Events

Cited by 2 publications

References 20 publications

Microgrids and Resilience: A Review

Microgrids and Resilience: A Review

Networked Microgrids: A Review on Configuration, Operation, and Control Strategies

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