• DocumentCode
    1417316
  • Title

    Spatiotemporal Load-Analysis Model for Electric Power Distribution Facilities Using Consumer Meter-Reading Data

  • Author

    Shin, Jin-Ho ; Yi, Bong-Jae ; Kim, Young-Il ; Lee, Heon-Gyu ; Ryu, Keun Ho

  • Author_Institution
    Korea Electr. Power Re search Inst. (KEPRI), Daejeon, South Korea
  • Volume
    26
  • Issue
    2
  • fYear
    2011
  • fDate
    4/1/2011 12:00:00 AM
  • Firstpage
    736
  • Lastpage
    743
  • Abstract
    The load analysis for the distribution system and facilities has relied on measurement equipment. Moreover, load monitoring incurs huge costs in terms of installation and maintenance. This paper presents a new model to analyze wherein facilities load under a feeder every 15 min using meter-reading data that can be obtained from a power consumer every 15 min or a month even without setting up any measuring equipment. After the data warehouse is constructed by interfacing the legacy system required for the load calculation, the relationship between the distribution system and the power consumer is established. Once the load pattern is forecasted by applying a clustering and classification algorithm of temporal data-mining techniques for the power customer who is not involved in automatic meter reading, a single-line diagram per feeder is created, and power-flow calculation is executed. The calculation result is analyzed by using various temporal and spatial analysis methods, such as the Internet geographic information system, single-line diagram, and online analytical processing.
  • Keywords
    distribution networks; load forecasting; power system measurement; consumer meter-reading data; electric power distribution facilities; load forecasting; load monitoring; measurement equipment; spatiotemporal load-analysis model; Automatic meter reading (AMR); data mining; geographic information system (GIS); meter reading data; power load analysis; spatiotemporal;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2010.2091973
  • Filename
    5678827