Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 3030-3044 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Smart Grid |
| Volume | 16 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2025 |
Funding
This work was supported in part by the National Science Foundation under Award 2316399 “Collaborative Research: RII Track-2 FEC: STORM: Data-Driven Approaches for Secure Electric Grids in Communities Disproportionately Impacted by Climate Change.” This project aims to leverage data-driven methodologies to enhance the resilience and security of electric grids in communities vulnerable to climate change impacts; in part the Department of Defense (DOD) Research Participation Program administered by the Oak Ridge Institute for Science and Education (ORISE) through an Interagency Agreement between the U.S. Department of Energy (DOE) and the DOD. ORISE is managed by ORAU under DOE Contract DE-SC0014664; and in part by the UT-Battelle, LLC with the US Department of Energy (DOE) under Contract DEAC05-00OR22725. All opinions expressed in this paper are the author’s and do not necessarily reflect the policies and views of DOD, DOE, or ORAU/ORISE. Received 24 May 2024; revised 22 October 2024 and 15 January 2025; accepted 23 March 2025. Date of publication 31 March 2025; date of current version 23 June 2025. This work was supported in part by the National Science Foundation under Award 2316399 “Collaborative Research: RII Track-2 FEC: STORM: Data-Driven Approaches for Secure Electric Grids in Communities Disproportionately Impacted by Climate Change.” This project aims to leverage data-driven methodologies to enhance the resilience and security of electric grids in communities vulnerable to climate change impacts; in part the Department of Defense (DOD) Research Participation Program administered by the Oak Ridge Institute for Science and Education (ORISE) through an Interagency Agreement between the U.S. Department of Energy (DOE) and the DOD. ORISE is managed by ORAU under DOE Contract DE-SC0014664; and in part by the UT-Battelle, LLC with the US Department of Energy (DOE) under Contract DEAC05-00OR22725. Paper no. TSG-00918-2024. (Corresponding author: Jesus D. Vasquez-Plaza.) Jesus D. Vasquez-Plaza and Fabio Andrade Rengifo are with the Department of Electrical and Computer Engineering, University of Puerto Rico Mayaguez, Mayagüez, PR 00681 USA (e-mail: [email protected]).
Keywords
- Aggregated inverter-based generation
- DER_A model
- online parameter estimation
- smooth function