[HTML][HTML] Physics-informed machine learning: a comprehensive review on applications in anomaly detection and condition monitoring

Y Wu, B Sicard, SA Gadsden - Expert Systems with Applications, 2024 - Elsevier
Condition monitoring plays a vital role in ensuring the reliability and optimal performance of
various engineering systems. Traditional methods for condition monitoring rely on physics …

Toward dynamic stability assessment of power grid topologies using graph neural networks

C Nauck, M Lindner, K Schürholt… - … Interdisciplinary Journal of …, 2023 - pubs.aip.org
To mitigate climate change, the share of renewable energies in power production needs to
be increased. Renewables introduce new challenges to power grids regarding the dynamic …

Towards dynamic stability analysis of sustainable power grids using graph neural networks

C Nauck, M Lindner, K Schürholt… - arXiv preprint arXiv …, 2022 - arxiv.org
To mitigate climate change, the share of renewable needs to be increased. Renewable
energies introduce new challenges to power grids due to decentralization, reduced inertia …

Learning Networked Dynamical System Models with Weak Form and Graph Neural Networks

Y Yu, D Huang, S Park, HC Pangborn - arXiv preprint arXiv:2407.16779, 2024 - arxiv.org
This paper presents a sequence of two approaches for the data-driven control-oriented
modeling of networked systems, ie, the systems that involve many interacting dynamical …

Grid-Metaverse: The Path From Digital Twins and Prototype Tests on DC Microgrids

W Ma, M Liu, G Hong, S Yang… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
With the development of cutting-edge technologies and the efforts of business giants,
Metaverse is becoming increasingly reachable. In addition to the fields of healthcare …

[图书][B] Applying modeling, simulation and machine learning for the renewable energy transition

M Lindner - 2023 - search.proquest.com
Mitigating climate change and reducing emissions of greenhouse gases to net-zero by mid-
century is a huge global challenge. The renewable energy transition is one of the key pillars …

Learning Coarse-Grained Dynamics on Graph

Y Yu, J Harlim, D Huang, Y Li - arXiv preprint arXiv:2405.09324, 2024 - arxiv.org
We consider a Graph Neural Network (GNN) non-Markovian modeling framework to identify
coarse-grained dynamical systems on graphs. Our main idea is to systematically determine …