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An approach for parameterization of equivalent dynamic models of microgrids

Grant number: 25/04071-7
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Start date: May 01, 2025
End date: April 30, 2026
Field of knowledge:Engineering - Electrical Engineering - Power Systems
Principal Investigator:Tatiane Cristina da Costa Fernandes
Grantee:Gustavo Pinto Eustáquio
Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

The integration of distributed generation into distribution systems, mainly composed of renewable energy sources, has driven the development of equivalent models that enable the representation of the active dynamic behavior of these systems for stability studies. However, obtaining a simplified model capable of capturing the main dynamics of the microgrid under different operating scenarios remains a challenge. One of the difficulties in this process lies in the presence of collinearity among the model parameters, which can compromise estimation accuracy and lead to inconsistent models.In this context, this work proposes an approach to estimate the key parameters of a dynamic equivalent model based on signals measured at the point of common coupling between the microgrid and the transmission system. In the first stage of this approach, trajectory sensitivity analysis is applied to identify the most influential parameters. Then, to ensure robustness in the estimation process, a collinearity analysis is performed to identify parameters with strong linear dependence. After selecting the estimable parameters, the parameterization step is conducted using a metaheuristic algorithm, aiming to minimize the difference between the dynamic response of the full system and that of the equivalent model. The proposed approach is expected to contribute to obtaining a set of parameters that adequately represent the microgrid's behavior under specific operating conditions, enabling more reliable stability and control studies for interconnected systems.

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