TY - GEN
T1 - Learning Based Capacitor Voltage Ripple Reduction of Modular Multilevel Converters under Unbalanced Grid Conditions with Different Power Factors
AU - Wang, Songda
AU - Dragicevic, Tomislav
AU - Teodorescu, Remus
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/28
Y1 - 2020/9/28
N2 - A fast and non-parameter-dependent grid-current-control method to ride through dangerous unbalanced gird condition is proposed in this paper. The grid-current references are calculated from an artificial intelligence (AI) surrogate model in order to keep the capacitor voltage at a safe level under a two phases short circuit to ground condition. And also, the circulating current reference are determined when the power factor is different when the grid fault is not serious. This machine learning network represents the relation between grid-current references and submodule capacitor voltages. The results show that this method prevents capacitor-overvoltage trips under completely short-circuited grid.
AB - A fast and non-parameter-dependent grid-current-control method to ride through dangerous unbalanced gird condition is proposed in this paper. The grid-current references are calculated from an artificial intelligence (AI) surrogate model in order to keep the capacitor voltage at a safe level under a two phases short circuit to ground condition. And also, the circulating current reference are determined when the power factor is different when the grid fault is not serious. This machine learning network represents the relation between grid-current references and submodule capacitor voltages. The results show that this method prevents capacitor-overvoltage trips under completely short-circuited grid.
KW - grid current control
KW - machine learning
KW - Modular Multilevel Converters
KW - submodule capacitor voltage
UR - http://www.scopus.com/inward/record.url?scp=85097533502&partnerID=8YFLogxK
U2 - 10.1109/PEDG48541.2020.9244470
DO - 10.1109/PEDG48541.2020.9244470
M3 - Article in proceeding
AN - SCOPUS:85097533502
SN - 978-1-7281-6991-0
T3 - IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
SP - 531
EP - 535
BT - 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
PB - IEEE
T2 - 11th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2020
Y2 - 28 September 2020 through 1 October 2020
ER -