Machine Learning Guided Operational Intelligence from Synchrophasors (Final Report)
- Schweitzer Engineering Laboratories, Inc., Pullman, WA (United States)
Schweitzer Engineering Laboratories (SEL) and Oregon State University (OSU) received over 27 terabytes of electrical power system phasor measurement unit (PMU) data for the Eastern, Western, and ERCOT interconnections. The dataset includes measurements spread across 446 PMUs from early 2016 to mid 2018 depending on the interconnect. The full dataset was split into a training and test (holdout) dataset by PNNL. All data was received in the Apache Parquet format. The overarching goal of this project is to develop and execute a strategy to mitigate data anomalies, perform analysis on the dataset, and detect anomalous events in the data.
- Research Organization:
- Schweitzer Engineering Laboratories, Inc., Pullman, WA (United States)
- Sponsoring Organization:
- USDOE Office of Electricity (OE)
- DOE Contract Number:
- OE0000912
- OSTI ID:
- 1828371
- Report Number(s):
- DOE-SEL-1861
- Country of Publication:
- United States
- Language:
- English
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