An Online Event-based Grid Impedance Estimation Technique Using Grid-connected Inverters

Tamas Kerekes, Mihai Cioboratu, Nabil Mohammed

Research output: Contribution to journalJournal articleResearchpeer-review

1 Citation (Scopus)

Abstract

An increasing intake of grid-connected inverters could change the characteristics of low voltage networks including the equivalent grid impedance seen by each inverter at its point of common coupling. This can impact the overall performance of the inverters, and thus it becomes necessary for grid-connected inverters to estimate the grid impedance online. However, there are some challenges when it comes to grid impedance estimation using grid-connected inverters. These include the estimation accuracy and the associated power quality issues that are mainly related to the amplitude, frequency, and time period of the injected disturbance into the grid. To address these challenges, a novel online event-based grid impedance estimation technique for grid-connected inverters is proposed in this article. This technique combines an active grid impedance estimation technique, based on variations of the inverter's output power [active (P) and reactive (Q) power variations], and the continuous monitoring of the positive-sequence amplitude of the PCC voltage. The main advantage is that the estimation technique only performs a deliberate perturbation of P and Q if there is a certain change in voltage magnitude related to grid impedance change. This will significantly reduce the occurrence of required PQ variations, thus minimizing the power losses and the impact on power quality. Simulation and experimental results of a grid-connected inverter system validate the performance of the proposed technique.

Original languageEnglish
Article number9219249
JournalI E E E Transactions on Power Electronics
Volume36
Issue number5
Pages (from-to)6106-6117
Number of pages12
ISSN0885-8993
DOIs
Publication statusPublished - May 2021

Keywords

  • Impedance measurement
  • PQ variations
  • inverters
  • modeling
  • power system identification
  • voltage monitoring

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