Focused on federated machine learning for power user electric energy data acquisition and analysis, this document defines a standardized architectural framework and operational guidelines. It provides a blueprint for collaborative model building across heterogeneous grid devices while supporting privacy, security, and regulatory considerations. Included are role mappings, data preprocessing standards, training workflows, and security mechanisms tailored for power metering scenarios.
- Standard Committee
- CIS/SC - Standards Committee
- Status
- Active PAR
- PAR Approval
- 2025-12-10
Working Group Details
- Society
- IEEE Computational Intelligence Society
- Standard Committee
- CIS/SC - Standards Committee
- Working Group
-
WGFLE2DA2/P3900 - Federated Learning of Power User Electric Energy Data Acquisition and Analysis Working Group
- IEEE Program Manager
- Sandra Maru
Contact Sandra Maru - Working Group Chair
- Yuan Chi
Other Activities From This Working Group
Current projects that have been authorized by the IEEE SA Standards Board to develop a standard.
No Active Projects
Standards approved by the IEEE SA Standards Board that are within the 10-year lifecycle.
No Active Standards
These standards have been replaced with a revised version of the standard, or by a compilation of the original active standard and all its existing amendments, corrigenda, and errata.
No Superseded Standards
These standards have been removed from active status through a ballot where the standard is made inactive as a consensus decision of a balloting group.
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These standards are removed from active status through an administrative process for standards that have not undergone a revision process within 10 years.
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