Abstract
This paper outlines a combination of two data-driven approaches leveraging sum-of-squares (SoS) optimization to: i) learn the power-voltage (p-v) characteristic of photovoltaic (PV) arrays, and ii) rapidly regulate operation of the companion PV inverter to a desired power setpoint. Estimation of available headroom in PV systems is critical to the task of providing ancillary services, and the proposed method puts forth a computationally tractable solution with minimal data needs for the same. In addition to providing this key contribution to application, from an algorithmic vantage point, we present an interior-point method to solve a linear regression reformulation of the original polynomial fitting problem with SoS constraints. We validate the proposed algorithms through time-domain numerical simulations (incorporating the PV source and a 15-th order inverter model) for a variety of large-signal disturbances (step changes in real-power demand, rapid changes in irradiance) and demonstrate that the method provides an effective strategy to concomitantly discover the p-v curve and seamlessly regulate operation to a desired setpoint.
Original language | English (US) |
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Title of host publication | 2020 American Control Conference, ACC 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2376-2381 |
Number of pages | 6 |
ISBN (Electronic) | 9781538682661 |
DOIs | |
State | Published - Jul 2020 |
Event | 2020 American Control Conference, ACC 2020 - Denver, United States Duration: Jul 1 2020 → Jul 3 2020 |
Publication series
Name | Proceedings of the American Control Conference |
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Volume | 2020-July |
ISSN (Print) | 0743-1619 |
Conference
Conference | 2020 American Control Conference, ACC 2020 |
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Country/Territory | United States |
City | Denver |
Period | 7/1/20 → 7/3/20 |
Bibliographical note
Funding Information:This work was supported in part by the National Science Foundation through award 1453921.
Publisher Copyright:
© 2020 AACC.