Load Model Identification Through a Hybrid Approach

Gomes, Gabriel J. N.; Lemes, Francisco R.; Cari, Elmer P. T.

doi:10.1109/ccece.2019.8861787

Cited by 1 publication

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The hybrid approach proposed was able to estimate the parameters of this system and the comparison between real and modeled behaviour with the parameters obtained can be seen in the Figure 42. Source: (GOMES et al, 2019) The application of the hybrid approach on Linearized Z-IM Load Model is subject of a paper presented by the author on the 2019 IEEE Canadian Conference on Electrical and Computer Engineering entitled "Load Model Identification Through a Hybrid Approach".…”

Section: Appendix Appendix a -Parameter Estimation Of Linearized Z-im...mentioning

confidence: 99%

Development of software for parameter estimation and its application on wind power plant equivalent model

Gomes¹

View full text Add to dashboard Cite

This project focused on the development of a software for parameter estimation of non-linear dynamic models and its application on wind power plant equivalent model. To achieve this goal, a parameter estimation package was developed in Python 3 containing the estimation methods applied alongside the models used during the study. To represent wind power plants, a generic model well-known in the literature was chosen, based on its ability of representing said plants during transients. The method applied for estimation of the model parameters is composed of two optimization algorithms. At first, Mean-Variance Mapping Optimization, an heuristic approach, is used in order to reduce the search region around a feasible solution. Afterwards, a non-linear algorithm based on Trajectory Sensitivity is used to determine the local minimum, thus estimating the parameters of the model. The method validation was made using data from simulated systems. Also, a guided user interface was developed for this application, aiding new users and improving its usability. Both the package and interface projects are hosted on the author's GitHub page.

show abstract

Section: Appendix Appendix a -Parameter Estimation Of Linearized Z-im...mentioning

confidence: 99%

Development of software for parameter estimation and its application on wind power plant equivalent model

Gomes¹

View full text Add to dashboard Cite

show abstract

Load Model Identification Through a Hybrid Approach

Cited by 1 publication

References 6 publications

Development of software for parameter estimation and its application on wind power plant equivalent model

Development of software for parameter estimation and its application on wind power plant equivalent model

Contact Info

Product

Resources

About