Aggregated DER_A Model Parameterization via Online Moving Horizon Estimation
This paper introduces a methodology for parameterizing the DER_A model using a novel smooth mathematical representation, simplifying the process and preserving accuracy in modeling inverter-based generator (IBG). The methodology employs an online parameterization process that can operate in real-tim...
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Published in | IEEE transactions on smart grid Vol. 16; no. 4; pp. 3030 - 3044 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Piscataway
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
01.07.2025
IEEE |
Subjects | |
Online Access | Get full text |
ISSN | 1949-3053 1949-3061 1949-3061 |
DOI | 10.1109/TSG.2025.3556333 |
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Summary: | This paper introduces a methodology for parameterizing the DER_A model using a novel smooth mathematical representation, simplifying the process and preserving accuracy in modeling inverter-based generator (IBG). The methodology employs an online parameterization process that can operate in real-time. The model parameterization process is structured into five sequential steps, each targeting a specific aspect of the DER_A model through moving horizon estimation. This approach adapts to systems with varying voltage and frequency support requirements by selectively applying each step. Simulation results on systems with both known and unknown parameters validate the methodology’s effectiveness. The online moving horizon estimation technique accurately captures the dynamics of the overall system and ensures that the parameterized DER_A model closely mirrors the real system’s voltage, current, and power dynamics. The findings highlight the potential of this methodology to substantially improve and simplify the dynamic modeling of power systems, paving the way for more reliable and robust IBG and grid integration. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 SC0014664 USDOE Office of Science (SC) National Science Foundation (NSF) |
ISSN: | 1949-3053 1949-3061 1949-3061 |
DOI: | 10.1109/TSG.2025.3556333 |