Abstract
For power grids predominantly featuring large synchronous generators (SGs), there exists a significant body of work bridging optimization and control tasks. A generic workflow in such efforts entails: characterizing the steady state of control algorithms and SG dynamics; assessing the optimality of the resulting operating point with respect to an optimal dispatch task; and prescribing control parameters to ensure that (under reasonable ambient perturbations) the considered control nudges the system steady state to optimality. Well studied instances of the aforementioned approach include designing: i) automatic generation control (AGC) participation factors to ensure economic optimality, and ii) governor frequency-droop slopes to ensure power sharing. Recognizing that future power grids will feature a diverse mix of SGs and inverter-based resources (IBRs) with varying control structures, this work examines the different steps of the optimization-control workflow for this context. Considering a representative model of active power-frequency dynamics of IBRs and SGs, a characterization of steady state is put forth (with and without secondary frequency control). Conditions on active-power droop slopes and AGC participation factors are then derived to ascertain desired power sharing and ensure economically optimal operation under varying power demands.
Original language | English (US) |
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Title of host publication | 2022 58th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798350399981 |
DOIs | |
State | Published - 2022 |
Event | 58th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2022 - Monticello, United States Duration: Sep 27 2022 → Sep 30 2022 |
Publication series
Name | 2022 58th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2022 |
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Conference
Conference | 58th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2022 |
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Country/Territory | United States |
City | Monticello |
Period | 9/27/22 → 9/30/22 |
Bibliographical note
Funding Information:This work was supported by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy under Solar Energy Technologies Office (SETO) through the award numbers EE0009025 and 38637 (UNIFI consortium), respectively.
Publisher Copyright:
© 2022 IEEE.