Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.

Original languageAmerican English
Number of pages5
DOIs
StatePublished - Aug 2019
Event2019 IEEE Power and Energy Society General Meeting, PESGM 2019 - Atlanta, United States
Duration: 4 Aug 20198 Aug 2019

Conference

Conference2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Country/TerritoryUnited States
CityAtlanta
Period4/08/198/08/19

Bibliographical note

See NREL/CP-5D00-72754 for preprint

NREL Publication Number

  • NREL/CP-5D00-76224

Keywords

  • clustering
  • convex hull
  • DB-scan
  • piece-wise linear models
  • system model
  • vanadium redox flow battery

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