A hierarchical optimization method for parameter estimation of diesel generators

Chao Ming Huang, Yann Chang Huang, Shin Ju Chen, Sung Pei Yang

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Diesel generators (DGs) are used to provide electrical power to consumers because their power outputs can be scheduled, and they offer stable operating characteristics in a standalone or microgrid system. The parameters for DGs are set to ensure reliable and accurate simulation for distributed energy resources (DERs), which increases system reliability, maintains power supply quality and reduces operational costs. There are many parameters that must be estimated for a DG. These parameter settings such as system gains and time constants may vary, as facilities are run for a few days. Parameters for a DG must then be re-estimated to ensure accurate simulation in a microgrid system. The proposed method uses a sensitivity analysis to classify parameters into three different categories. A hierarchical optimization method combined with an enhanced whale optimization algorithm (EWOA) is then used to estimate the parameter settings for a DG using actual measurement data. The proposed method is applied to a practical microgrid system, and the results show that the proposed method determines the optimal parameter settings for a DG that enables accurate simulation and robust implementation for a microgrid system.

Original languageEnglish
Pages (from-to)176467-176479
Number of pages13
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Materials Science
  • General Engineering

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