TY - GEN
T1 - ANN-based Cooperative Frequency Restoration in a Network of Grid-forming and Grid-following Inverters
AU - D'Silva, Silvanus
AU - Hosseinzadehtaher, Mohsen
AU - Zare, Alireza
AU - Shadmand, Mohammad B.
AU - Bayhan, Sertac
AU - Abu-Rub, Haitham
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - An artificial neural network (ANN) inspired cooperative hierarchical control scheme for frequency restoration during sudden source/load variations in a network of grid-forming and grid-following inverter-based resources (IBRs) is proposed. The photovoltaic (PV) sources' regulated power harvesting ability is leveraged for immediate frequency support in response to potential disturbances. The ANN-inspired supervisory controller (SC) estimates the demanded power (ΔP) to regulate the frequency which is then optimally distributed amongst all PV interfaced IBRs by a Power Allocator (PA) module; located in the secondary layer cluster coordinator (CC). The PA module ensures that the interfaced PV's generation limits are not violated while also minimizing system losses. Detailed description of each module in the cluster along with their technical specifications are provided. Finally, simulation results that justify the feasibility and robustness of the proposed control scheme to restore the grid frequency in a timely manner are discussed.
AB - An artificial neural network (ANN) inspired cooperative hierarchical control scheme for frequency restoration during sudden source/load variations in a network of grid-forming and grid-following inverter-based resources (IBRs) is proposed. The photovoltaic (PV) sources' regulated power harvesting ability is leveraged for immediate frequency support in response to potential disturbances. The ANN-inspired supervisory controller (SC) estimates the demanded power (ΔP) to regulate the frequency which is then optimally distributed amongst all PV interfaced IBRs by a Power Allocator (PA) module; located in the secondary layer cluster coordinator (CC). The PA module ensures that the interfaced PV's generation limits are not violated while also minimizing system losses. Detailed description of each module in the cluster along with their technical specifications are provided. Finally, simulation results that justify the feasibility and robustness of the proposed control scheme to restore the grid frequency in a timely manner are discussed.
KW - Artificial neural network
KW - RoCoF
KW - frequency restoration
KW - grid following
KW - grid forming
KW - inverter-based resources
KW - optimization
UR - http://www.scopus.com/inward/record.url?scp=85182942861&partnerID=8YFLogxK
U2 - 10.1109/ECCE53617.2023.10362231
DO - 10.1109/ECCE53617.2023.10362231
M3 - Conference contribution
AN - SCOPUS:85182942861
T3 - 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
SP - 1453
EP - 1460
BT - 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
Y2 - 29 October 2023 through 2 November 2023
ER -