Abstract
With the increasing penetration level of renewable sources and power electronics loads in modern power systems, accurate and computationally efficient models are needed. Black-box model (BBM) could be a useful method in such systems. However, not very extensive research efforts have been made for power electronics BBM so far, and existing works mostly focus on steady-state operation, neglecting the important transient behaviors such as load transients, voltage transients, and faults. This paper presents a comparative study of three commonly used nonlinear BBM approaches for transient behaviors of power electronics converters. Comparison methods are proposed, and the evaluations are conducted under different transients using a grid-connected single-phase photovoltaic inverter. The findings of this study provide valuable references for further feasibility investigations on implementing BBMs in large-scale power electronics-rich power systems.
Original language | English |
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Title of host publication | 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1446-1452 |
Number of pages | 7 |
ISBN (Electronic) | 9798350316445 |
DOIs | |
State | Published - 2023 |
Event | 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023 - Nashville, United States Duration: Oct 29 2023 → Nov 2 2023 |
Publication series
Name | 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023 |
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Conference
Conference | 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023 |
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Country/Territory | United States |
City | Nashville |
Period | 10/29/23 → 11/2/23 |
Funding
This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/doe-public-access-plan). ACKNOWLEDGMENT This material is based upon work supported by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technologies Office Award Number 38453. This work also made use of Engineering Research Center Shared Facilities provided by the Engineering Research Center Program of the National Science Foundation and the Department of Energy under NSF Award Number EEC1041877 and the CURENT Industry Partnership Program.
Keywords
- black-box model
- data-driven
- power electronics
- system identification