Skip to main content
OSTI.GOVU.S. Department of Energy Office of Scientific and Technical Information
U.S. Department of Energy
Office of Scientific and Technical Information
 

Cloud Based Analytical Framework for Synchrophasor Data Analysis

Conference ·
OSTI ID:1562916
 [1];  [1];  [1];  [1];  [1];  [2];  [3];  [3];  [3]
  1. BATTELLE (PACIFIC NW LAB)
  2. UNIVERSITY PROGRAMS
  3. Bonneville Power Administration
+ Show Author Affiliations
The paper presents initial results from the development of a cloud-based, Big Data analysis platform for power systems. The computational pipeline uses the Apache Spark framework running in an OpenStack cloud infrastructure. A real-world phasor measurement unit (PMU) dataset has been used to carry out the analysis. Actual examples of power system events detection using synchrophasor data are presented. It has been shown that applications of the cloud based computing environment and the Apache Spark framework enable a significant increase in the computational efficiency of large-scale PMU data analysis.
Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1562916
Report Number(s):
PNNL-SA-127703
Country of Publication:
France
Language:
English

Similar Records

Machine Learning for Synchrophasor Analysis
Technical Report · Tue Sep 01 00:00:00 EDT 2020 · OSTI ID:1673617
Cyber-Power Co-Simulation for End-to-End Synchrophasor Network Analysis and Applications
Conference · Fri Oct 01 00:00:00 EDT 2021 · OSTI ID:1854485
Open-Source Suite for Advanced Synchrophasor Analysis
Conference · Tue May 01 00:00:00 EDT 2018 · OSTI ID:1492439

Related Subjects

PMU
Machine Learning
Big Data
SPARK
Event Detection