Zobrazeno 1 - 10
of 322
pro vyhledávání: '"Xiuchen, Jiang"'
Publikováno v:
IET Generation, Transmission & Distribution, Vol 18, Iss 9, Pp 1871-1884 (2024)
Abstract Existing interturn fault detecting methods rely on winding impedance, winding current, and dissolved gases. They are effective only when the insulation is severely damaged. This paper proposes a novel detection method based on fusion analysi
Externí odkaz:
https://doaj.org/article/d84517ac46bf4920b993ca010f1436a2
Publikováno v:
High Voltage, Vol 9, Iss 1, Pp 217-229 (2024)
Abstract Accurate assessment of hot‐spot temperature is essential for the safe operation of power transformers. Existing dynamic thermal models cannot estimate hot‐spot temperature accurately since some input parameters are roughly determined by
Externí odkaz:
https://doaj.org/article/d5f5a3470fa4469cb4d1aa4cf49d5b0a
Publikováno v:
IET Smart Grid, Vol 7, Iss 1, Pp 28-37 (2024)
Abstract In order to improve the accuracy of image‐based transmission line defect detection, while reducing the computational complexity and the high demand on chip performance, an object detection framework is proposed, which aims to improve model
Externí odkaz:
https://doaj.org/article/2c25b08aaa7441b5925c93a9ee7b6f84
Publikováno v:
Global Energy Interconnection, Vol 6, Iss 5, Pp 601-613 (2023)
The reliability of geographic information system (GIS) partial discharge fault diagnosis is crucial for the safe and stable operation of power grids. This study proposed a data enhancement method based on a self-attention mechanism to optimize the VA
Externí odkaz:
https://doaj.org/article/30e1931a68f040cf868cb6d82dcfb199
Publikováno v:
International Transactions on Electrical Energy Systems, Vol 2024 (2024)
The electric vehicle (EV) has been popular in recent years, which also brings huge challenges to the distribution network due to its energy instability. In order to consider the economic factors of dispatching these distributed renewable resources, t
Externí odkaz:
https://doaj.org/article/dd58721ac0544aae8f7e4a6ddb5893ba
Publikováno v:
High Voltage, Vol 8, Iss 3, Pp 538-549 (2023)
Abstract The optical morphology of discharge is the main characteristic parameter describing the physical process of the discharge, and the luminescence behavior is inextricably linked to the motion behavior of charged particles. Since the Trichel di
Externí odkaz:
https://doaj.org/article/abd45b5fbe9243bea0c200b2ae81c193
Publikováno v:
Journal of Modern Power Systems and Clean Energy, Vol 11, Iss 6, Pp 1868-1877 (2023)
Weather-related failures significantly challenge the reliability of distribution systems. To enhance the risk management of weather-related failures, an interpretable extra-trees based weather-related risk prediction model is proposed in this study.
Externí odkaz:
https://doaj.org/article/8ac6ef03fcef45a0b223558599af7682
Publikováno v:
Journal of Modern Power Systems and Clean Energy, Vol 11, Iss 3, Pp 907-916 (2023)
The single-line-to-ground faults with line breaks (SLGFs-LBs) occur more and more frequently in distribution networks and can cause major safety accidents. It is difficult to distinguish the single-line-to-ground faults (SLGFs) in resonant grounding
Externí odkaz:
https://doaj.org/article/6e46341f7583471aa7041ec9d8146662
Publikováno v:
IET Generation, Transmission & Distribution, Vol 16, Iss 21, Pp 4291-4303 (2022)
Abstract Power equipment operation and maintenance (O&M) requires plenty of domain knowledge to improve equipment security and power grid reliability. However, most knowledge is implicitly represented by the semantic text, which is hard to be compreh
Externí odkaz:
https://doaj.org/article/a5ab6240a2d146e1bc90657b906eddcb
Publikováno v:
IET Science, Measurement & Technology, Vol 16, Iss 6, Pp 377-387 (2022)
Abstract Higher time resolution imaging is vital for exploring the microscopic mechanisms of the discharge process. The transient processes of discharge phenomena occur in a short time, and the onset cannot be predicted in advance, thus not providing
Externí odkaz:
https://doaj.org/article/2eb8278c863d4a93ba972db5a4e77bf4