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Research on Digital Twin and Collaborative Cloud and Edge Computing Applied in Operations and Maintenance in Wind Turbines of Wind Power Farm
[chapter]
2021
Advances in Transdisciplinary Engineering
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Data source layer solves acquisition and transmission of wind turbine operation and maintenance data, edge computing node layer is responsible for on-site data cloud computing, storage and data transmission ...
Framework consists of data source layer, edge computing node layer, public or private cloud. ...
based on the huge amount of data collected by
ilar wind turbine equipment, and establish or iterate fault diagnosis expert
wledge. ...
doi:10.3233/atde210263
fatcat:k4mccxxi4zemndkwxbbcnnx43e
Integration of a Heuristic Multi-Agent Protection System into a Distribution Network Interconnected with Distributed Energy Resources
2020
Energies
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The adopted methodology is reliant on real-time simulation of a distribution network interconnected with Doubly-fed Induction Generator (DFIG) wind farms where different fault scenarios are applied to ...
rely on a detailed analysis of fault current contribution and variation in operation conditions under real-world scenarios. ...
We are also immensely grateful to Vitoria University and Professor Stephen Gray, the Director of the Institute of Sustainable Industries and Liveable Cities (ISILC) for approving the on campus access for ...
doi:10.3390/en13205250
fatcat:6tzkzzt5gzfpbb6b5rqzmwtgfu
Wireless Sensors Networks Applications For Micro-Grids Management: State of Art
2020
2020 6th IEEE International Energy Conference (ENERGYCon)
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The complexity and the decentralization of Micro-Grids have led to management and diagnosis issues because of using distributed power sources, especially the renewable energy sources. ...
Wireless Sensor Networks can substitute part of the communication infrastructure of the Micro-Grid, it deploys between its elements in order to ensure data flow in real time. ...
CONCLUSION WSNs consist of hundreds of sensor nodes that may be deployed in a relatively complex environment such as in the MG one. ...
doi:10.1109/energycon48941.2020.9236519
fatcat:j6p6j7eclnaelocpxuzycsadky
Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0
2021
Applied Sciences
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A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning ...
nodes within the energy industry. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app11073186
fatcat:wucysis52zdj3mqpvdz4wluehi
XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations Maintenance of Wind Turbines
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2012.10489v1 fatcat:62r6xltm6zfohfhq7wvgxiuzay
Condition-based monitoring (CBM) has been widely utilised in the wind industry for monitoring operational inconsistencies and failures in turbines, with techniques ranging from signal processing and vibration ...
We propose XAI4Wind, a multimodal knowledge graph for explainable decision support in real-world operational turbines and demonstrate through experiments several use-cases of the proposed KG towards O& ...
wind industry. ...
arXiv:2012.10489v2
fatcat:3n6rfi3twbenhaqfmnyblm7spq
Table of Contents
2020
2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2)
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Impulse Failure Probability Analysis of Lightining Strike Transmission Line Based on Data Mining 4070 Po11-35 Research on Bearing Fault Identification of Wind Turbine Based on Deep Belief Network 4076 ...
Multi-objective Optimal Scheduling of Power Systems Based on Complementary Characteristics of Heterogeneous Energy Sources 1533 Po02-16 The Impact of High-Speed Heavy Electric Railway Load on Wind Farms ...
doi:10.1109/ei250167.2020.9347098
fatcat:uzijufuzb5ab3blgftr5niughe
The Conundrum of Fault Detection in Partially Observable AC-DC Distribution Systems
2020
The Journal of Engineering
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Fault detection in hybrid AC-DC distribution networks is a challenging problem due to various sources of uncertainty and high degrees of complexity. ...
A few well-known sources that instil uncertainty in the system are stochasticity of energy injected by distributed energy resources, noisy or corrupt data, heterogeneity of agents, problems with the automated ...
If the anemometer confirms that there is no wind blowing, its inclusion increases the degree of our belief in the correctness of information received from the wind turbine that its injected power is nil ...
doi:10.1049/joe.2019.1059
fatcat:rtbx7525hvbsdj5xq2r7hvmlmq
Distributed Learning Applications in Power Systems: A Review of Methods, Gaps, and Challenges
2021
Energies
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Distributed learning is a collaboratively decentralized machine learning algorithm designed to handle large data sizes, solve complex learning problems, and increase privacy. ...
Distributed learning is a subfield of machine learning and a descendant of the multi-agent systems field. ...
After a fault occurrence in the system, the power network was divided into several groups based on rotor speed data using the K-means clustering algorithm. ...
doi:10.3390/en14123654
fatcat:25fv4mw2dfan5c23lhi3l45tte
Fog Computing for Realizing Smart Neighborhoods in Smart Grids
2020
Computers
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Cloud Computing provides on-demand computing services like software, networking, storage, analytics, and intelligence over the Internet ("the cloud"). ...
This is achieved through an extensive literature study, firstly on Fog Computing and its foundation technologies, its applications and the literature review of Fog Computing research in various application ...
It will also help in deciding what appropriate fog nodes locations based on the workload of the area are. 2. ...
doi:10.3390/computers9030076
doaj:56a1bb6fa6584ded977208dc1be1f513
fatcat:tbs4p5paczam3bfoqkcpi7zwyy
Communication Architecture for Grid Integration of Cyber Physical Wind Energy Systems
2017
Applied Sciences
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The architecture of the WF communication network is switch-based, consisting of ethernet switches and communication links in every wind turbine. ...
The network configuration is based on point-to-point communication and a local area network (LAN). ...
We developed a communication network model for the WF based on the OPNET Modeler. The network architecture was modeled based on IEC 61400-25 and IEC 61850 standards. ...
doi:10.3390/app7101034
fatcat:wlddmc2r3vdnfprvdessztlig4
A Review of Graph Neural Networks and Their Applications in Power Systems
[article]
2021
arXiv
pre-print
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The complexity of graph-structured data has brought significant challenges to the existing deep neural networks defined in Euclidean domains. ...
Specifically, several classical paradigms of GNNs structures (e.g., graph convolutional networks) are summarized, and key applications in power systems, such as fault scenario application, time series ...
Fault location Traditional methods of fault location for distribution networks mainly include voltage sag-based methods, impedance-based methods, traveling wave-based methods, and auto-mated outage mapping ...
arXiv:2101.10025v2
fatcat:6sptisxciza45kx67ah3xwww4i
A Review of Information Fusion Methods for Gas Turbine Diagnostics
2019
Sustainability
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Detecting and isolating faults in a system is a complex problem with many uncertainties, including the integrity of available information. ...
The correct and early detection of incipient faults or severe degradation phenomena in gas turbine systems is essential for safe and cost-effective operations. ...
Figure 1 . 1 Outline of a multi-source information fusion tool based on a Bayesian network.
Figure 1 . 1 Outline of a multi-source information fusion tool based on a Bayesian network. ...
doi:10.3390/su11226202
fatcat:kry6gcqnobbtdeuti4kezied7y
A Review of Graph Neural Networks and Their Applications in Power Systems
2022
Journal of Modern Power Systems and Clean Energy
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The complexity of graph-structured data has brought significant challenges to the existing deep neural networks defined in Euclidean domains. ...
and interdependency among nodes. ...
In contrast, spatial-based GCNs perform graph convolutional operations locally on each node, and the weights of networks can be easily shared across different locations. ...
doi:10.35833/mpce.2021.000058
fatcat:nbzvs2tskjgpni53fn4h6k5y3i
Reliability Modeling and Evaluation of Urban Multi-energy Systems: A Review of the State of the Art and Future Challenges
2020
IEEE Access
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such as multi-energy source modeling, complex uncertainty factor modeling, mutual influence of information and physical coupling. ...
Various subsystems involved in the coupling of UMESs, including power grids, gas pipeline networks, cold/heat networks, transportation networks, and energy cyber-physical system, exhibit coupling characteristics ...
The influence of the cascade fault effect was studied based on seepage theory, revealing a detailed mathematical analysis of fault propagation in CPSs. ...
doi:10.1109/access.2020.2996708
fatcat:r44k26kllngvbpptgjyg5lgkk4
A Review of Classification Problems and Algorithms in Renewable Energy Applications
2016
Energies
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The paper also provides a comprehensive literature review and discussion on different classification techniques in specific RE problems, including wind speed/power prediction, fault diagnosis in RE systems ...
Classification problems and their corresponding solving approaches constitute one of the fields of machine learning. ...
Classification Problems and Algorithms in Fault Diagnosis in RE-Related Systems Like other complex and heterogeneous systems, wind turbines are subject to the occurrence of faults that can affect both ...
doi:10.3390/en9080607
fatcat:vnziyrf3d5elbiizh6bfqxsoiy
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