A Hybrid Algorithm for Parameter Estimation (HAPE) for Diesel Generator Sets

Matthew R. Overlin, James MacOmber, Christopher L. Smith, Luca Daniel, Edward G. Corbett, James L. Kirtley

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

In order to simulate the dynamic phenomena of devices within a microgrid, suitable simulation models are needed. Historically, parameterization approaches have been explored for large generator sets rather than for smaller generator sets, which would be more suitable in a microgrid. Additionally, non-invasive experimental methods are often preferred over invasive methods when collecting data. Further, if there are many uncertain parameters, then it is more imperative to employ a larger computing platform. In this work, a hybrid algorithm for parameter estimation (HAPE) is utilized to find a fitting simulation model for a diesel genset. A Sobol parameter sensitivity analysis is conducted to inform the HAPE of the more influential parameters. Finally, the HAPE is developed for a supercomputing platform so that the HAPE can be executed in a massively parallel fashion.

Original languageEnglish
Pages (from-to)1704-1714
Number of pages11
JournalIEEE Transactions on Energy Conversion
Volume37
Issue number3
Early online dateFeb 23 2022
DOIs
StatePublished - Feb 23 2022
Externally publishedYes

Keywords

  • Time-domain simulation
  • high-fidelity simulations
  • parameter estimation

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