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A Spark (TM) Based Client for Synchrophasor Data Stream Processing
Amrita Vishwa Vidyapeetham, Amrita Sch Engn, Ctr Computat Engn & Networking CEN, Coimbatore, Tamil Nadu, India..
Amrita Vishwa Vidyapeetham, Amrita Sch Engn, Ctr Computat Engn & Networking CEN, Coimbatore, Tamil Nadu, India..
Amrita Vishwa Vidyapeetham, Amrita Sch Engn, Ctr Computat Engn & Networking CEN, Coimbatore, Tamil Nadu, India..
Amrita Vishwa Vidyapeetham, Amrita Sch Engn, Ctr Computat Engn & Networking CEN, Coimbatore, Tamil Nadu, India..
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2018 (English)In: PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE AND UTILITY EXHIBITION ON GREEN ENERGY FOR SUSTAINABLE DEVELOPMENT (ICUE 2018), Institute of Electrical and Electronics Engineers (IEEE), 2018Conference paper, Published paper (Refereed)
Abstract [en]

The SCADA based monitoring systems, having a very low sampling of one reading per 2-4 seconds is known to produce roughly 4.3 Tera Bytes (TiBs) of data annually. With synchrophasor technology, this will go up at least 100 times more as the rate of streaming is as high as 50/100 (60/120) Hz. Phasor data concentrators (PDCs) transmit byte streams encapsulating a comprehensive list of power system parameter including multiple phasor measurements, instantaneous frequency estimates, rate of change of frequency and several analog and digital quantities; this high volume and velocity of data makes it truly 'Big Data'. This helps in making the power grid a lot more observable, enabling real-time monitoring of crucial grid events such as voltage stability, grid stress and transient oscillations. Synchrophasor technology uses the IEEE C37.118.2-2011 (TM) Phasor Measurement Unit (PMU) /PDC communication protocol for data exchange which has no direct interface with any contemporary big data stream APIs or protocols. In this paper we propose a streaming interface in Apache Spark (TM), a popular big data platform, using Scala programming language, implementing a complete IEEE C37.118.2-2011 (TM) client inside a stream receiver so that we can effortlessly receive synchrophasor data directly to Spark (TM) applications for real-time processing and archiving.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018.
Keywords [en]
Apache Spark, Big Data, C37.118.2, PDC, PMU, Smart Grid, Streaming, Synchrophasor
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-249914DOI: 10.23919/ICUE-GESD.2018.8635650ISI: 000462214700014Scopus ID: 2-s2.0-85062358083ISBN: 978-974-8257-99-0 (print)OAI: oai:DiVA.org:kth-249914DiVA, id: diva2:1307794
Conference
International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE),OCT 24-26, 2018, Phuket, THAILAND
Note

QC 20190429

Available from: 2019-04-29 Created: 2019-04-29 Last updated: 2019-05-23Bibliographically approved

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Almas, Muhammad ShoaibNordström, Lars

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