TY - GEN
T1 - Inertia estimation in power systems using energy storage and system identification techniques
AU - Tamrakar, Ujjwol
AU - Guruwacharya, Nischal
AU - Bhujel, Niranjan
AU - Wilches-Bernal, Felipe
AU - Hansen, Timothy M.
AU - Tonkoski, Reinaldo
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - Fast-frequency control strategies have been proposed in the literature to maintain inertial response of electric generation and help with the frequency regulation of the system. However, it is challenging to deploy such strategies when the inertia constant of the system is unknown and time-varying. In this paper, we present a data-driven system identification approach for an energy storage system (ESS) operator to identify the inertial response of the system (and consequently the inertia constant). The method is first tested and validated with a simulated genset model using small changes in the system load as the excitation signal and measuring the corresponding change in frequency. The validated method is then used to experimentally identify the inertia constant of a genset. The inertia constant of the simulated genset model was estimated with an error of less than 5% which provides a reasonable estimate for the ESS operator to properly tune the parameters of a fast-frequency controller.
AB - Fast-frequency control strategies have been proposed in the literature to maintain inertial response of electric generation and help with the frequency regulation of the system. However, it is challenging to deploy such strategies when the inertia constant of the system is unknown and time-varying. In this paper, we present a data-driven system identification approach for an energy storage system (ESS) operator to identify the inertial response of the system (and consequently the inertia constant). The method is first tested and validated with a simulated genset model using small changes in the system load as the excitation signal and measuring the corresponding change in frequency. The validated method is then used to experimentally identify the inertia constant of a genset. The inertia constant of the simulated genset model was estimated with an error of less than 5% which provides a reasonable estimate for the ESS operator to properly tune the parameters of a fast-frequency controller.
KW - Energy storage systems
KW - Fast-frequency control
KW - Inertia
KW - System identification
KW - Virtual inertia
UR - http://www.scopus.com/inward/record.url?scp=85091177224&partnerID=8YFLogxK
U2 - 10.1109/SPEEDAM48782.2020.9161919
DO - 10.1109/SPEEDAM48782.2020.9161919
M3 - Conference contribution
AN - SCOPUS:85091177224
T3 - 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2020
SP - 577
EP - 582
BT - 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2020
Y2 - 24 June 2020 through 26 June 2020
ER -