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Title: UPS: Unified PMU-Data Storage System to Enhance T+D PMU Data Usability

Journal Article · · IEEE Transactions on Smart Grid
 [1];  [2];  [1];  [1];  [2];  [3];  [3];  [3]
  1. Washington State Univ., Vancouver, WA (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  3. Univ. of Tennessee, Knoxville, TN (United States)
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The emerging distribution-level phasor measurement unit (D-PMU) is expected to play an important role in enhancing distribution system observability and situational-awareness. It is a demanding yet challenging task to develop advanced D-PMU data management and analytics tools to improve D-PMU data usability and further promote D-PMU projects deployment. This paper focuses on D-PMU data processing and storage. It presents a brief review of existing D-PMU data storage systems and points out their limitations on high-performance, flexibility, and scalability. To overcome the limitations, a unified PMU-data storage system (UPS) is proposed. Specifically, a unified I/O interface between storage servers and computing jobs is developed to effectively reduce the overhead of managing various computing jobs and data analytics over multiple storage infrastructures; and PMUCache with PMUCache partitioning and PMUCache replacement algorithms are designed to support in-situ data processing and shared distributed data storage and further serve the computing jobs/queries with different Quality of Service (QoS) requirements. Through a series of experiments, it is demonstrated that UPS achieves high performance on fast and big data processing and storage, and efficiently increases the flexibility and scalability of PMU data management systems.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC52-07NA27344; AC05-00OR22725
OSTI ID:
1524299
Alternate ID(s):
OSTI ID: 1712711
Report Number(s):
LLNL-JRN-L-760462; 948347
Journal Information:
IEEE Transactions on Smart Grid, Vol. 11, Issue 1; ISSN 1949-3053
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 7 works
Citation information provided by
Web of Science

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  • Jiang, Jun; Zhao, Xinghui; Wallace, Scott
  • Proceedings of the Fourth IEEE/ACM International Conference on Big Data Computing, Applications and Technologies https://doi.org/10.1145/3148055.3148082
conference December 2017

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