TY - GEN
T1 - Data-driven Modeling of Commercial Photovoltaic Inverter Dynamics Using Power Hardware-in-the-Loop
AU - Guruwacharya, Nischal
AU - Bhandari, Harish
AU - Subedi, Sunil
AU - Vasquez-Plaza, Jesus D.
AU - Stoel, Matthew Lee
AU - Tamrakar, Ujjwol
AU - Wilches-Bernal, Felipe
AU - Andrade, Fabio
AU - Hansen, Timothy M.
AU - Tonkoski, Reinaldo
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Grid technologies connected via power electronic converter (PEC) interfaces increasingly include the grid support functions for voltage and frequency support defined by the IEEE 1547-2018 standard. The shift towards converter-based generation necessitates accurate PEC models for assessing system dynamics that were previously ignored in conventional power systems. In this paper, a method for assessing photovoltaic (PV) inverter dynamics using a data-driven technique with power hardware-in-the-loop is presented. The data-driven modeling technique uses various probing signals to estimate commercial off-the-shelf (COTS) inverter dynamics. The MATLAB system identification toolbox is used to develop a dynamic COTS inverter model from the perturbed grid voltage (i.e., probing signal) and measured current injected to the grid by the inverter. The goodness-of-fit of COTS inverter dynamics in Volt-VAr support mode under each probing signal is compared. The results show that the logarithmic square-chirp probing signal adequately excites the COTS inverter in Volt-VAr mode to fit a data-driven dynamic model.
AB - Grid technologies connected via power electronic converter (PEC) interfaces increasingly include the grid support functions for voltage and frequency support defined by the IEEE 1547-2018 standard. The shift towards converter-based generation necessitates accurate PEC models for assessing system dynamics that were previously ignored in conventional power systems. In this paper, a method for assessing photovoltaic (PV) inverter dynamics using a data-driven technique with power hardware-in-the-loop is presented. The data-driven modeling technique uses various probing signals to estimate commercial off-the-shelf (COTS) inverter dynamics. The MATLAB system identification toolbox is used to develop a dynamic COTS inverter model from the perturbed grid voltage (i.e., probing signal) and measured current injected to the grid by the inverter. The goodness-of-fit of COTS inverter dynamics in Volt-VAr support mode under each probing signal is compared. The results show that the logarithmic square-chirp probing signal adequately excites the COTS inverter in Volt-VAr mode to fit a data-driven dynamic model.
KW - Data-driven modeling
KW - grid support functions
KW - power hardware-in-the-loop
KW - real-time digital simulator
KW - system identification
UR - http://www.scopus.com/inward/record.url?scp=85136224825&partnerID=8YFLogxK
U2 - 10.1109/SPEEDAM53979.2022.9842001
DO - 10.1109/SPEEDAM53979.2022.9842001
M3 - Conference contribution
AN - SCOPUS:85136224825
T3 - 2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2022
SP - 924
EP - 929
BT - 2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2022
Y2 - 22 June 2022 through 24 June 2022
ER -
