Storage and Analysis of Synchrophasor Data for Event Detection in Indian Power System Using Hadoop Ecosystem

  • Akhilendra Pratap Singh
  • G. Hemant Kumar
  • Subhendu Sekhar Paik
  • Diptendu Sinha Roy
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 847)


Synchrophasor devices commonly referred to as phasor measurement units (PMUs) have been rapidly deployed in power grids to get a clearer picture of the events that take place in power grid at very high sampling rates. Thus PMUs enable event predictions to become more accurate. However, high data-sampling rate of PMUs creates huge volumes of data on a GB scale per PMU per day, which in turn makes the storage and analysis of the collected data difficult; giving rise to a Big Data problem use case. In India, National Load Dispatch Centre (NLDC) uses Synchrowave; a centralized software package to collect, store and process, which runs on a single very high-end system for storage and processing. But the centralized architecture of current system gives no room for scalability, neither in computation nor storage, even with costly hardware upgrades. This paper proposes a system model with all the desired features using open-source frameworks and tools like Apache Hadoop and HBase.


Phasor measurement unit (PMU) Synchrowave Hadoop HBase 



This work has been carried out by financial assistances from SERB-DST (File no. EMR/2017/001508). The authors wish to thank POSOCO, New Delhi for providing necessary synchrophasor data.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Akhilendra Pratap Singh
    • 1
  • G. Hemant Kumar
    • 2
  • Subhendu Sekhar Paik
    • 1
  • Diptendu Sinha Roy
    • 1
  1. 1.National Institute of Technology MeghalayaShillongIndia
  2. 2.ICTS-TIFRBengaluruIndia

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