Artificial Neural Network Based Identification of Multi-Operating-Point Impedance Model

Mengfan Zhang, Xiongfei Wang (Corresponding author), Dongsheng Yang, Mads Græsbøll Christensen

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

21 Citaten (Scopus)


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.
Originele taal-2Engels
Pagina's (van-tot)1231-1235
Aantal pagina's5
TijdschriftIEEE Transactions on Power Electronics
Nummer van het tijdschrift2
StatusGepubliceerd - feb. 2021


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