Autors: Stefan Stoyanov., Kakanakov, N. R.
Title: Big data analytics in electricity distribution systems
Keywords: Advanced Metering Infrastructures | Smart Meters | Privacy Preserving

Abstract: Many problems in power distribution systems affecting today's technological equipment are often generated locally within a facility from any number of situations, such as local construction, heavy loads, faulty distribution components, and even typical background electrical noise. Penetration of advanced sensor systems such as advanced metering infrastructure (AMI), high-frequency overhead and underground current and voltage sensors have been increasing significantly in power distribution systems over the past few years. To manage the massive amounts of data generated from smart meters and other components of the grid, utility companies need a solution models such as e.g. Apache Hadoop ecosystem that operates in a distributed manner rather than using the centralized computing model. The paper aims to discuss a solution for easily discovering of problems with power quality that have local origin which collects data from AMI and implements distributed computing across clusters of comput



    40th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2017, pp. 205-208, 2017, Croatia, Institute of Electrical and Electronics Engineers Inc., DOI 10.23919/MIPRO.2017.7973419

    Цитирания (Citation/s):
    1. Guerrero-Prado, J.S., Alfonso-Morales, W., Caicedo-Bravo, E., Zayas-Pérez, B., Espinosa-Reza, A. The power of big data and data analytics for AMI data: A case study (2020) Sensors (Switzerland), 20 (11), art. no. 3289, pp. 1-27. - 2020 - в издания, индексирани в Scopus или Web of Science
    2. Morrell, T.J., Venkataramanan, V., Srivastava, A., Bose, A., Liu, C.-C. Modeling of Electric Distribution Feeder Using Smart Meter Data (2018) Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, 2018-April, art. no. 8440540, DOI: 10.1109/TDC.2018.8440540 - 2018 - в издания, индексирани в Scopus или Web of Science
    3. Saipol, Hafizah Farhah Saipan, Sulfeeza Mohd Drus, and Marini Othman. "A review of big data analytics on customer complaints in the electricity industry." International Journal of Business Continuity and Risk Management 11, no. 2-3 (2021): 208-223. - 2021 - в издания, индексирани в Scopus или Web of Science
    4. Citations Citations 100% 10 Screen reader support enabled. Guerrero-Prado, J.S., Alfonso-Morales, W., Caicedo-Bravo, E.F., "A data analytics/big data framework for advanced metering infrastructure data," (2021) Sensors, 21 (16), art. no. 5650, DOI: 10.3390/s21165650; PUBLISHER: MDPI AG; ISSN: 14248220 Turn on screen reader support - 2021 - в издания, индексирани в Scopus или Web of Science

    Вид: постер/презентация в международен форум, публикация в реферирано издание