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Collection and Analysis of Electricity Consumption Data: The Case of POSTECH Campus

In: AI and Analytics for Public Health

Author

Listed:
  • Do-Hyeon Ryu

    (Pohang University of Science and Technology)

  • Young Myoung Ko

    (Pohang University of Science and Technology
    Pohang University of Science and Technology)

  • Young-Jin Kim

    (Pohang University of Science and Technology
    Open Innovation Big Data Center, Pohang University of Science and Technology)

  • Minseok Song

    (Pohang University of Science and Technology
    Pohang University of Science and Technology)

  • Kwang-Jae Kim

    (Pohang University of Science and Technology
    Pohang University of Science and Technology)

Abstract

Advanced metering infrastructure (AMI) is an integrated system of smart meters, communication networks, and data management systems. The AMI allows the automatic and remote measurement and monitoring of energy consumption. It also provides important information for the management of peak demand and energy consumption and costs. Pohang University of Science Technology (POSTECH) has developed its own AMI and an IT platform called Open Innovation Big Data Center (OIBC) to store and share various data collected in the campus. In this work, we describe the AMI and the OIBC platform equipped with various sensors and systems for measuring, storing, calling, and monitoring data. Data are collected from seven buildings with different characteristics. We installed 266 sensors at the buildings, including 188 EnerTalk and Biz, 18 plugin, and 60 high-sampling sensors. The sensors collect electricity consumption data in real time, and users can visualize and download the data through the OIBC platform. In this work, we present analysis results of the collected data. The results show that the amounts of electricity consumed by campus buildings are different depending on various factors, including building size, occupant type and their behaviors, and building use. We also compare the amounts of electricity consumed before and after the COVID-19 outbreak. The information extracted can be used to improve the satisfaction of students and faculty as well as the efficiency of electricity management.

Suggested Citation

  • Do-Hyeon Ryu & Young Myoung Ko & Young-Jin Kim & Minseok Song & Kwang-Jae Kim, 2022. "Collection and Analysis of Electricity Consumption Data: The Case of POSTECH Campus," Springer Proceedings in Business and Economics, in: Hui Yang & Robin Qiu & Weiwei Chen (ed.), AI and Analytics for Public Health, pages 329-342, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-75166-1_24
    DOI: 10.1007/978-3-030-75166-1_24
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