Sampling density and frequency as data quality determinants in smart grids

Rachel Abo, Adir Even

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


The integration of smart devices and sensors together with extensive data processing capabilities into the electrical power grid is a fundamental infrastructure of Smart Grid's environments. Such capabilities introduce major Data Quality challenges: The optimization of electricity production and consumption in such environments relies on collecting and analyzing vast amounts of sensor-based data samples in real time. Degradation in the quality of such data might hinder its analysis and result in sub-optimal Smart Grid configuration. This study aims at exploring the effect of two Data Quality determinants in Smart Grid's environments - sampling frequency, reflecting the temporal distribution, and sampling density, reflecting spatial distribution. Beyond technical aspects, sampling density and frequency have economic implications, which must affect their optimal configuration. This study contributes to further conceptualization of these Data Quality determinants and assessing their impact in Smart Grid's environments, by developing an analytical model that links their configuration to cost-benefit tradeoffs. This manuscript presents the model development, and its preliminary evaluation with a large-scale datasets that reflects energy consumption in a real-world environment.

Original languageEnglish
Title of host publication2017 Smart Cities Symposium Prague, SCSP 2017
Subtitle of host publicationIEEE Proceedings
EditorsJiri Ruzicka
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781538638255
StatePublished - 10 Jul 2017
Event2017 Smart Cities Symposium Prague, SCSP 2017 - Prague, Czech Republic
Duration: 25 May 201726 May 2017


Conference2017 Smart Cities Symposium Prague, SCSP 2017
Country/TerritoryCzech Republic

ASJC Scopus subject areas

  • Safety Research
  • Transportation
  • Urban Studies
  • Geography, Planning and Development


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