Application-Driven Data Management Framework for Wind Farms by Cloud-Edge-End Collaboration
Author:
Affiliation:
1. Tongji University,Department of Electrical Engineering,Shanghai,China
2. State Grid Jibei Electric Power Research Institute,Department of Smart Grid and New Energy,Beijing,China
Funder
State Grid Corporation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10115460/10115466/10117434.pdf?arnumber=10117434
Reference8 articles.
1. Data center server energy consumption optimization algorithm combining XGBoost and Multi-GRU;shen;Journal of Computer Applications,2022
2. A Combined Algorithm for Cleaning Abnormal Data of Wind Turbine Power Curve Based on Change Point Grouping Algorithm and Quartile Algorithm
3. Machine Learning-Based Digital Twin for Predictive Modeling in Wind Turbines
4. A Novel Wind Speed-Sensing Methodology for Wind Turbines Based on Digital Twin Technology;li;IEEE Transactions on Instrumentation and Measurement,2021
5. Energy-Efficient Anomaly Detection With Primary and Secondary Attributes in Edge-Cloud Collaboration Networks
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