Journal
IEEE TRANSACTIONS ON POWER ELECTRONICS
Volume 36, Issue 2, Pages 1231-1235Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2020.3012136
Keywords
Impedance; Impedance measurement; Data models; Training; Voltage measurement; Predictive models; Current measurement; Artificial neural networks; impedance measurement; multiple operating points; voltage source inverter
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This letter proposes a method for identifying the impedance model of VSI under a wide range of operating points using artificial neural networks. The effectiveness of the ANN-based method is validated with analytical impedance models.
The black-box impedance model of voltage source inverters (VSIs) can be measured at their terminals without access to internal control details, which greatly facilitate the analysis of inverter-grid interactions. However, the impedance model of VSI is dependent on its operating point and can have different profiles when the operating point is changed. This letter proposes a method for identifying the impedance model of VSI under a wide range of operating points. The approach is based on the artificial neural network (ANN), where a general framework for applying the ANN to identify the VSI impedance is established. The effectiveness of the ANN-based method is validated with the analytical impedance models.
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