Optimization-Based Estimation of Microgrid Equivalent Parameters for Voltage and Frequency Dynamics

Niranjan Bhujel, Timothy M. Hansen, Reinaldo Tonkoski, Ujjwol Tamrakar, Raymond H. Byrne

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

Microgrid parameter estimation is essential to enable optimal voltage and frequency control using distributed energy resources (DER). Microgrid parameters vary through time, e.g., when generation is re-dispatched/committed, during microgrid reconfiguration. Furthermore, sensor measurements are noisy and preservation of the fast dynamics measurements is required, which is difficult to achieve with a lowpass filter. In this paper, a moving horizon estimation (MHE) approach is applied to estimate microgrid parameters for voltage and frequency support. The proposed approach estimates the states i.e., frequency, rate of change of frequency, grid voltage and current, and system parameters i.e., inertia, damping, and equivalent impedance. The MHE is formulated as an optimization problem using data over a fixed past horizon and solved online such that the sum of the square of measurement noise and process noise is minimized. Results showed that the proposed approach was able to estimate microgrid states, parameters, and disturbances within 5% for most values, which is sufficient to use in microgrid voltage and frequency control.

Original languageEnglish
Title of host publication2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665435970
DOIs
StatePublished - 28 Jun 2021
Externally publishedYes
Event2021 IEEE Madrid PowerTech, PowerTech 2021 - Madrid, Spain
Duration: 28 Jun 20212 Jul 2021

Publication series

Name2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings

Conference

Conference2021 IEEE Madrid PowerTech, PowerTech 2021
Country/TerritorySpain
CityMadrid
Period28/06/212/07/21

Keywords

  • Energy storage systems
  • microgrids
  • moving horizon estimation
  • optimal state and parameter estimation

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