Zobrazeno 1 - 10
of 644
pro vyhledávání: '"SCADA data"'
Publikováno v:
Wind Energy, Vol 27, Iss 11, Pp 1245-1267 (2024)
Abstract The power performance and the wind velocity field of an onshore wind farm are predicted with machine learning models and the pseudo‐2D RANS model, then assessed against SCADA data. The wind farm under investigation is one of the sites invo
Externí odkaz:
https://doaj.org/article/8c53a004e8e840ddb9465257d4d45659
Autor:
Ali Fazli, Javad Poshtan
Publikováno v:
Energy Science & Engineering, Vol 12, Iss 3, Pp 1174-1186 (2024)
Abstract Due to the difficulties of system modeling, nonlinearity effects, uncertainties, and the availability of Wind Turbines (WTs) SCADA system data, data‐driven Fault Detection and Isolation (FDI) methods for WTs have received increasing attent
Externí odkaz:
https://doaj.org/article/d105d5f23ee143ddb9e32f61173ea052
Autor:
Ravi Pandit, Jianlin Wang
Publikováno v:
IET Renewable Power Generation, Vol 18, Iss 4, Pp 722-742 (2024)
Abstract The aim of this study is to explore the potential and economic benefits of utilising Supervisory Control and Data Acquisition (SCADA) data to improve wind turbine operation and maintenance activities. The review identifies a gap in the curre
Externí odkaz:
https://doaj.org/article/c6a35a649ce4405c8518389fc67616e6
Akademický článek
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Akademický článek
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Publikováno v:
IEEE Access, Vol 12, Pp 157587-157598 (2024)
Fault warning and identification are crucial for preventing accidents, enhancing performance and ensuring the reliability of wind turbine (WT). While SCADA systems are widely used for WT fault monitoring, they face inherent challenges including a lac
Externí odkaz:
https://doaj.org/article/9fa99bb16bef4724b0ac248817e225c1
Publikováno v:
IEEE Access, Vol 12, Pp 43948-43957 (2024)
Condition monitoring of wind turbines is critical for increasing the reliability of the turbines and reducing their operation and maintenance costs. Supervisory control and data acquisition (SCADA) systems have been widely regarded as a promising tec
Externí odkaz:
https://doaj.org/article/bd4c596826d9425590895e30872b7186
Autor:
Paweł Knes, Phong B. Dao
Publikováno v:
Energies, Vol 17, Iss 20, p 5055 (2024)
Data-driven models have become powerful tools for structural and condition monitoring of engineering systems, particularly wind turbines. This paper presents a comparative analysis of common machine learning (ML) algorithms (artificial neural network
Externí odkaz:
https://doaj.org/article/5d4c5cf3e3a6474eb20f9ef738d4d51e
Autor:
Joel Torres-Cabrera, Jorge Maldonado-Correa, Marcelo Valdiviezo-Condolo, Estefanía Artigao, Sergio Martín-Martínez, Emilio Gómez-Lázaro
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7458 (2024)
The imminent depletion of oil resources and increasing environmental pollution have driven the use of clean energy, particularly wind energy. However, wind turbines (WTs) face significant challenges, such as critical component failures, which can cau
Externí odkaz:
https://doaj.org/article/c6663c16b3d84247a563f87587b46753
Publikováno v:
Wind Energy, Vol 26, Iss 8, Pp 826-849 (2023)
Abstract Modern utility‐scale wind turbines are equipped with a Supervisory Control And Data Acquisition (SCADA) system gathering vast amounts of operational data that can be used for analysis to improve operation and maintenance of turbines. We an
Externí odkaz:
https://doaj.org/article/fa02b138688347b5b37dbb119cb05765