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Full-Text Articles in Engineering
Optimal Sizing Of Energy Storage With Embedded Wind Power Generation, Nicholas Roche, Jane Courtney
Optimal Sizing Of Energy Storage With Embedded Wind Power Generation, Nicholas Roche, Jane Courtney
Articles
Energy storage technologies are key to increased penetration of renewable energies on the distribution system. Not only do they increase availability of energy, but they contribute to the overall reliability of the system. However, the cost of large-scale storage systems can often be prohibitive, and storage needs to be sized appropriately, both to fill the energy gaps inevitable in renewable energies such as wind and to minimize costs. In this work, a Monte Carlo Simulation is performed to optimally size an energy storage system while minimizing overall system cost. 30 years of historical wind speed data are used to model …
Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin
Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin
Electrical & Computer Engineering Faculty Publications
We report on the development of machine learning models for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a continuous-wave recirculating linac utilizing 418 SRF cavities to accelerate electrons up to 12 GeV through five passes. Of these, 96 cavities (12 cryomodules) are designed with a digital low-level rf system configured such that a cavity fault triggers waveform recordings of 17 rf signals for each of the eight cavities in the cryomodule. Subject matter experts are able to analyze the collected time-series data and identify which of the …