In 2023, a blackout occurred in the National Interconnected System (SIN), resulting in the interruption of approximately 23,368 MW of load. Despite the requirement for the operating agents to provide the National Electric System Operator (ONS) with validated mathematical models for their components, the disturbance analysis report concluded that the discrepancy between these models and the actual performance of certain power plants was one of the main causes of the event. Motivated by this finding, this work proposes the application of an optimization routine for the parameters identification for automatic voltage regulators (AVR) of synchronous generators. The optimization utilized a metaheuristic algorithm with the objective of minimizing the root mean square error (RMSE) between the curve derived from commissioning tests, and the computationally simulated curve. The gains and time constants of the regulator were used as decision variables. The optimization was implemented by integrating a routine programmed in Python with the Anatem computational program. Twenty tests were conducted, achieving an average RMSE of 0.00061186, with a dispersion equal or inferior than 16% for the decision variables.