Big Data Processing for Power Grid Event Detection
In this paper we present the application of big data processing for the development of machine learning (ML) models to detect relevant events in power grid operations. This is based on almost 20TB of phasor measurement unit data corresponding to up to two years of operation of three grid interconnections which provide power to most of the United States. A significant aspect of the work consists in having all data processing performed on a single standard GPU server, from pre-processing to ML model training and testing. We describe the data and computational infrastructure, challenges faced and methods used in data processing, main findings and results. The ML approach employed for best utilization of the big data is also discussed, including sample results.
- Research Organization:
- Siemens Corporation (Princeton, NJ)
- Sponsoring Organization:
- USDOE Office of Electricity (OE)
- DOE Contract Number:
- OE0000917
- OSTI ID:
- 1764611
- Report Number(s):
- DOE-SIEMENS-00917-1
- Resource Relation:
- Conference: Second Workshop on Big Data Predictive Maintenance Using Artificial Intelligence (BDPM-AI 2020) @ IEEE Big Data Conference 2020, Virtual Event, December 10-13 2020
- Country of Publication:
- United States
- Language:
- English
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