Phase-Selection Algorithms to Minimize Cost and Imbalance in U.S. Synthetic Distribution Models

Fernando Postigo, Carlos Mateo, Tomas Gomez, Fernando Cuadra, Pablo Duenas, Tarek Elgindy, Bri-Mathias Hodge, Bryan Palmintier, Venkat Krishnan

Research output: Contribution to journalArticlepeer-review

14 Scopus Citations


The increasing penetration of distributed energy resources (DERs) has driven a push toward new algorithms and tools for distribution system operation and planning; however, there is a lack of publicly available electrical distribution test systems at the large scale—multi-feeder, multi-substation—which are required for realistically evaluating the performance and scalability of these new developments. This paper presents a Reference Network Model (RNM) aimed to plan large-scale, U.S.-style, synthetic distribution systems. Special emphasis is placed on two algorithms that allow multi-phase feeder design: (1) a method to select the most suitable number of phases for each section considering the connected customers, and (2) a method to assign phases to the users to provide near-balanced phasing while maintaining realistic levels of imbalance. The performance of the developed algorithms is verified by comparing the obtained system designs with the original IEEE 8,500-node test feeder and the Electric Power Research Institute (EPRI) J1 feeder.

Original languageAmerican English
Article number106042
Number of pages9
JournalInternational Journal of Electrical Power and Energy Systems
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2020

NREL Publication Number

  • NREL/JA-5D00-73570


  • Phase imbalance
  • Power distribution
  • Reference Network Model
  • Representative networks
  • Synthetic networks
  • System planning


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