Considerations for AMI-Based Operations for Distribution Feeders: Preprint

Santosh Veda, Harsha Vardhana Padullaparti, Murali Baggu, Martha Symko-Davies, Surya Dhulipala, Tom Bialik

Research output: Contribution to conferencePaper


More than $5 billion in investments in advanced metering infrastructure (AMI) technologies, AMI deployments, as pervasive secondary network voltage monitoring systems, provide opportunities for utility operations and controls. This paper focuses on the considerations for AMI-based tools and techniques as the industry moves toward operationalizing such large data sets. Phase identification is a first such tool. Numerous distribution network analysis, monitoring, and control applications - including volt/volt-ampere reactive control, state estimation, and distribution automation - require accurate phase connectivity information in the system models. The phase connectivity database maintained by utilities is inaccurate because of a significant amount of missing data, restoration activities, and network reconfiguration. Existing phase identification techniques that estimate phase connectivity work well in distribution feeders that have low or no photovoltaic (PV) generation; however, they fail to identify the phases accurately when considerable PV generation is present. This work addresses the phase identification problem in the presence of high PV generation using statistical analysis methods. Further, insights into the AMI data requirements for this application in terms of data window length and resolution are provided using sensitivity analysis performed on an actual distribution feeder model of San Diego Gas & Electric Company. The results of this study show that the phase connectivity, even in the presence of high PV generation, can be accurately identified using statistical analysis of AMI data of 1 day.
Original languageAmerican English
Number of pages8
StatePublished - 2019
Event2019 IEEE Power & Energy Society General Meeting (IEEE PES GM) - Atlanta, Georgia
Duration: 4 Aug 20198 Aug 2019


Conference2019 IEEE Power & Energy Society General Meeting (IEEE PES GM)
CityAtlanta, Georgia

Bibliographical note

See NREL/CP-5D00-76228 for paper as published in IEEE proceedings

NREL Publication Number

  • NREL/CP-5D00-72773


  • advanced metering infrastructure
  • correlation coefficient
  • phase identification
  • power distribution lines
  • regression analysis


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