Online Monitoring Technical Basis and Analysis Framework for Large Power Transformers; Interim Report for FY 2012
The Light Water Reactor Sustainability program at Idaho National Laboratory (INL) is actively conducting research to develop and demonstrate online monitoring (OLM) capabilities for active components in existing Nuclear Power Plants. A pilot project is currently underway to apply OLM to Generator Step-Up Transformers (GSUs) and Emergency Diesel Generators (EDGs). INL and the Electric Power Research Institute (EPRI) are working jointly to implement the pilot project. The EPRI Fleet-Wide Prognostic and Health Management (FW-PHM) Software Suite will be used to implement monitoring in conjunction with utility partners: the Shearon Harris Nuclear Generating Station (owned by Duke Energy for GSUs, and Braidwood Generating Station (owned by Exelon Corporation) for EDGs. This report presents monitoring techniques, fault signatures, and diagnostic and prognostic models for GSUs. GSUs are main transformers that are directly connected to generators, stepping up the voltage from the generator output voltage to the highest transmission voltages for supplying electricity to the transmission grid. Technical experts from Shearon Harris are assisting INL and EPRI in identifying critical faults and defining fault signatures associated with each fault. The resulting diagnostic models will be implemented in the FW-PHM Software Suite and tested using data from Shearon-Harris. Parallel research on EDGs is being conducted, and will be reported in an interim report during the first quarter of fiscal year 2013.
- Research Organization:
- Idaho National Lab. (INL), Idaho Falls, ID (United States)
- Sponsoring Organization:
- DOE - NE
- DOE Contract Number:
- DE-AC07-05ID14517
- OSTI ID:
- 1057689
- Report Number(s):
- INL/EXT-12-27181
- Country of Publication:
- United States
- Language:
- English
Similar Records
Online Monitoring Technical Basis and Analysis Framework for Emergency Diesel Generators - Interim Report for FY 2013
Online Monitoring of Induction Motors