Research on the Division of Vibration Zone Limits for Giant Francis Units Based on Big Data

At present, the division of vibration zones for the operation of hydropower units by various hydropower plants, research and testing institutes mainly refers to the vibration limits specified in the standards. The value of limits is mainly based on the long-term vibration data of over 7000 units worldwide, without considering unit capacity, operating conditions, manufacturing level, and development difficulty. This article focuses on the stable operation data and previous variable load test data of the state monitoring system for 86 giant hydropower units in five hydropower stations. Big data mining, sorting and analysis and identification of operating conditions are carried out to explore the root causes of unit stability problems, and to establish vibration zone limits for various parameters of giant hydropower units. Practical applications have shown that the vibration zone limit division results based on big data mining of cascaded giant hydropower stations are more accurate than the vibration zone division limit values commonly used in regulations, and have important guiding significance for the safe and stable operation of giant hydropower units.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/epee63731.2024.10875145
Primary Topic
Water Systems and Optimization
Type
article
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Research on the Division of Vibration Zone Limits for Giant Francis Units Based on Big Data

Yun Tan, Youping Li, Ling Li, Bo Xu et al.
Water Systems and Optimization
article

Research on the Division of Vibration Zone Limits for Giant Francis Units Based on Big Data

Yun Tan, Youping Li, Ling Li, Bo Xu, Hansong Si
article en

Abstract

At present, the division of vibration zones for the operation of hydropower units by various hydropower plants, research and testing institutes mainly refers to the vibration limits specified in the standards. The value of limits is mainly based on the long-term vibration data of over 7000 units worldwide, without considering unit capacity, operating conditions, manufacturing level, and development difficulty. This article focuses on the stable operation data and previous variable load test data of the state monitoring system for 86 giant hydropower units in five hydropower stations. Big data mining, sorting and analysis and identification of operating conditions are carried out to explore the root causes of unit stability problems, and to establish vibration zone limits for various parameters of giant hydropower units. Practical applications have shown that the vibration zone limit division results based on big data mining of cascaded giant hydropower stations are more accurate than the vibration zone division limit values commonly used in regulations, and have important guiding significance for the safe and stable operation of giant hydropower units.

Yangtze River Pharmaceutical Group (China) (CN)
Climate action
Openalex Percentile: Top 69%
Water Systems and Optimization
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