Parameter Identification for Grid Voltage Support Function of Aggregated DER_A Model
System dynamic models for hundreds of inverter-based generators are necessary to represent the whole behavior and to perform stability analysis at the transmission and distribution level in the electric power system. Some aggregated models, like DER_A and PVD1, have been suggested in the literature. However, these models include a considerable number of parameters, and so far, there is a lack of a formalized online method for parameterizing them. Several parameterization strategies for this particular model require the use of smooth functions. The parameters of these aggregated models may experience fluctuations and changes in the foreseeable future as the power system becomes more reliant on inverter-based generation. Consequently, an online parameter estimation will be necessary. This research proposes a way for parameter identification via online moving horizon estimation (MHE) for the grid voltage support function of the DER_A model by using a smooth mathematical representation. MATLAB/Simulink simulation shows that the proposed approach using MHE with a smooth representation of the DER_A model closely estimates the grid voltage support function parameters in the presence or absence of measurement noise. This study establishes the groundwork for the potential use in a detailed system including several inverter-based generators, with a primary focus on grid voltage support.
Authors
- Fabio Andrade (ORCID: https://orcid.org/0000-0001-5599-8080)
- Reinaldo Tonkoski (ORCID: https://orcid.org/0000-0003-3057-1085)
- Jesus D. Vasquez‐Plaza (ORCID: https://orcid.org/0000-0001-9514-3124)
- Niranjan Bhujel
Institutions
- University of Puerto Rico-Mayaguez (PR)
- University of Maine (US)
Publication Details
- Published
- 2024-11-03
- DOI
- https://doi.org/10.1109/iecon55916.2024.10905890
- Citations
- 3
- Primary Topic
- Power Quality and Harmonics
- Type
- article
- Field-Weighted Citation Impact
- 0.63
Funders
- National Science Foundation