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NoSQL Data Storage and Clustering Large Volume of Data from Smart Metering Systems with Impact on Electricity Consumption Peak and Tariff Settings

Author

Listed:
  • Simona-Vasilica Oprea

    (Bucharest University of Economic Studies)

  • Adela Bâra

    (Bucharest University of Economic Studies)

  • Dan PreoÈ›escu

    (Romanian Energy Center)

Abstract

Recently, large volumes of electricity consumption data are pouring constantly from smart meters and other sensors that count for millions or even milliards of records. Our purpose in this paper is to handle such data and extract valuable information until it becomes stale. Sometimes, additional data such as meteorological, motion-sensitive, door position data, results from surveys, tariffs, etc. come together with the electricity consumption and increase the number of records. In this case, NoSQL solutions are utilized to process and analyze the entire volume of data. In this paper, we propose a data processing framework for electricity data set that comes from a trial smart metering implementation period that took place from 1st January to 31st December 2010 in Ireland. The main purpose is to cluster the consumers based on similarities regarding theirs 30- minute consumption, show their impact on the electricity consumption peak that could be used as an input in establishing real-time tariffs based on peak coefficient.

Suggested Citation

  • Simona-Vasilica Oprea & Adela Bâra & Dan PreoÈ›escu, 2019. "NoSQL Data Storage and Clustering Large Volume of Data from Smart Metering Systems with Impact on Electricity Consumption Peak and Tariff Settings," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 327-333, December.
    • Handle: RePEc:ovi:oviste:v:xix:y:2019:i:2:p:327-333
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    clustering; big data; NoSQL; electricity consumption; real-time tariff;
    All these keywords.

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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