SPLTRAK Abstract Submission
A Data-Driven Feeder Selection Method for Distribution Hosting Capacity Studies
Alexandre Nassif1& Fernanda C. L. Trindade2
1LUMA Energy, San Juan, PR, United States
/2University of Campinas, Campinas, Brazil

Even though load flow modeling and associated analysis are today’s industry adopted practices, there are many electric utilities that lack such models for their distribution feeders and can benefit from a balance that entails modeling a strategically defined portion of their systems. Additionally, there are niche studies that do not require running individual models of every single distribution feeder and can also rely on sample analysis and subsequent extrapolation. This paper presents a clustering method to derive representative samples of distribution feeders for common distribution planning studies comprising hosting capacity and inverter setting requirements. This work was driven by the needs of a Caribbean electric utility that operates about 1,400 distribution feeders concentrated in an island, but only about 3% of these feeders have a certified load flow model.