Automated Parameter Identification and Calibration for the Itaipu Power Generation System using Modelica, FMI, and RaPId

Podlaski, Meaghan; Vanfretti, Luigi; Pesente, Jonas; Galassi, Paulo Henrique

doi:10.1109/mscpes.2019.8738793

Cited by 2 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model was calibrated using both user-defined AVR, PSS, and TG models and IEEE generic AVR and PSS models (M. Podlaski, L. Vanfretti, J. Pesente and P. H. Galassi, 2019). Figure 12 shows the results of the AVR and PSS calibration for the data set using the generic and user-defined control system models.…”

Section: Results -Case 2: November 2 2016mentioning

confidence: 99%

“…Limited opportunities exist to test the physical power system because the existing system cannot be compromised for experimentation; building a new system for testing is not be a viable option, as it would be too costly (L. Vanfretti, W. Li, T. Bogodorova and P. Panciatici, 2013). The results of this paper expand upon (M. Podlaski, L. Vanfretti, J. Pesente and P. H. Galassi, 2019), to show alternate ways to model power systems and derive user-defined model parameters with accuracy using Modelica and FMI. Previously, the IEEE standard models were used to represent the system.…”

Section: Motivationmentioning

confidence: 89%

“…The optimization process used in this paper for the comparison with the generic IEEE power system models is described in (M. Podlaski, L. Vanfretti, J. Pesente and P. H. Galassi, 2019). Both the user-defined and generic models are calibrated using the same process.…”

Section: Parameter Identification and Calibration Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Parameter Estimation of User-Defined Control System Models forItaipú Power Plant using Modelica and OpenIPSL

Podlaski¹,

Fernandes²,

Pesente³

et al. 2020

Linköping Electronic Conference Proceedings

Self Cite

View full text Add to dashboard Cite

The power industry heavily relies on power system modeling to understand system operations, perform system planning studies, and identify and correct problems that arise within the system. By minimizing the error between the models and actual physical system, it can be ensured that the models provide representation of both the existing and future the power system. Many of these models in the system are user-defined, i.e. they are specialized representations of a specific system component in the system. It is important that these customized models produce an accurate response. However, maintaining such models is costly, so it is of value to determine if those models can be replaced with a generic model. Phasor measurement data can be used to calibrate model parameters and reduce error. In this paper, this process is automated for a generator in the Itaipu power plant using RaPId, a MATLAB toolbox that integrates measurements, models using Modelica/FMI standards, and optimization routines. This is achieved by using a combination of particle swarm optimization (PSO) algorithm and classical gradient optimization routines to calibrate the model parameters. In this paper, the calibration of a generic model of a synchronous generator, automatic voltage regulator, and power system stabilizer are estimated and compared to the user-defined models for an automatic voltage regulator, power system stabilizer, and turbine governor.

show abstract

Section: Results -Case 2: November 2 2016mentioning

confidence: 99%

Section: Motivationmentioning

confidence: 89%

See 1 more Smart Citation

Parameter Estimation of User-Defined Control System Models forItaipú Power Plant using Modelica and OpenIPSL

Podlaski¹,

Fernandes²,

Pesente³

et al. 2020

Linköping Electronic Conference Proceedings

Self Cite

View full text Add to dashboard Cite

show abstract

“…This work builds off of the work in [2] and [3], which focuses on parameter estimation for the Itaipù hydroelectric plant. Itaipuìs about 20 times larger than Mostarsko, using PMU data from various faults and system disturbances.…”

Section: Related Workmentioning

confidence: 99%

Validation of power plant models using field data with application to the Mostar hydroelectric plant

Podlaski¹,

Bombois²,

Vanfretti³

2022

International Journal of Electrical Power & Energy Systems

Self Cite

View full text Add to dashboard Cite

Automated Parameter Identification and Calibration for the Itaipu Power Generation System using Modelica, FMI, and RaPId

Cited by 2 publications

References 7 publications

Parameter Estimation of User-Defined Control System Models forItaipú Power Plant using Modelica and OpenIPSL

Parameter Estimation of User-Defined Control System Models forItaipú Power Plant using Modelica and OpenIPSL

Validation of power plant models using field data with application to the Mostar hydroelectric plant

Contact Info

Product

Resources

About