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This paper presents a trusted execution environment (TEE)-enhanced federated learning (FL) framework for condition monitoring of distributed wind systems (DWSs). DWSs have become a topic of interest with the increased energy demand. Technological advancements in wind turbine technology have paved the way for DWSs to make a massive impact on the power grid. Due to underdeveloped security, malicious groups and individuals can target individual turbines, gain control of wind farms, and ultimately threaten the overall power grid. TEE-enhanced FL offers a solution; however, there are some challenges to its implementation. The remainder of this paper will discuss the challenges further and present solutions to their respective challenges. These solutions have been validated through experimentation and confirm an effective FL framework balancing both practicality and security in DWSs.
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This content will become publicly available on July 8, 2026
An Enhanced Federated Learning Framework for Condition Monitoring of Distributed Wind Systems
Abstract This paper presents a trusted execution environment (TEE)-enhanced federated learning (FL) framework for condition monitoring of distributed wind systems (DWSs). DWSs have become a topic of interest with the increased energy demand. Technological advancements in wind turbine technology has paved the way for DWSs to make a massive impact on the power grid. Due to underdeveloped security, malicious groups and individuals can target individual turbines, gain control of wind farms, and ultimately threaten the overall power grid. TEE-enhanced FL offers a solution, however, there are some challenges to their implementation. The remainder of this paper will discuss the challenges further and present solutions to their respective challenges. These solutions have been validated through experimentation and confirm an effective FL framework balancing both practicality and security in DWSs.
more »
« less
- Award ID(s):
- 2429540
- PAR ID:
- 10652864
- Publisher / Repository:
- American Society of Mechanical Engineers
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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