Voltage Estimation in Low-Voltage Distribution Grids with Distributed Energy Resources

Marija Markovic, Amirhossein Sajadi, Anthony Florita, Robert Cruickshank, Bri Mathias Hodge

Research output: Contribution to journalArticlepeer-review

19 Scopus Citations

Abstract

Present distribution grids generally have limited sensing capabilities and are therefore characterized by low observability. Improved observability is a prerequisite for increasing the hosting capacity of distributed energy resources such as solar photovoltaics (PV) in distribution grids. In this context, this paper presents learning-aided low-voltage estimation using untapped but readily available and widely distributed sensors from cable television (CATV) networks. The cable broadband sensors offer timely local voltage magnitude sensing with 5-minute resolution and can provide an order of magnitude more data on the time-varying state of a secondary distribution system than currently deployed utility sensors. The proposed solution incorporates voltage readings from neighboring CATV sensors, taking into account spatio-temporal aspects of the observations, and estimates single-phase voltage magnitudes at all non-monitored low-voltage buses using random forests. The effectiveness of the proposed approach was demonstrated using a multi-phase 1572-bus feeder from the SMART-DS data set for two case studies - passive distribution feeder (without PV) and active distribution feeder (with PV). The analysis was conducted on simulated data, and the results show voltage estimates with a high degree of accuracy, even at extremely low percentages of observable nodes.

Original languageAmerican English
Article number9359483
Pages (from-to)1640-1650
Number of pages11
JournalIEEE Transactions on Sustainable Energy
Volume12
Issue number3
DOIs
StatePublished - Jul 2021

Bibliographical note

Publisher Copyright:
© 2010-2012 IEEE.

NREL Publication Number

  • NREL/JA-5D00-79257

Keywords

  • Cable television network
  • distributed photovoltaics
  • low-voltage estimation
  • random forests
  • secondary distribution system

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