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Communication
Peer-Review Record

Estimation of the Equivalent Circuit Parameters in Transformers Using Evolutionary Algorithms

Math. Comput. Appl. 2023, 28(2), 36; https://doi.org/10.3390/mca28020036
by Hector Ascencion-Mestiza 1, Serguei Maximov 1, Efrén Mezura-Montes 2, Juan Carlos Olivares-Galvan 3,*, Rodrigo Ocon-Valdez 4 and Rafael Escarela-Perez 3
Math. Comput. Appl. 2023, 28(2), 36; https://doi.org/10.3390/mca28020036
Submission received: 25 January 2023 / Revised: 22 February 2023 / Accepted: 28 February 2023 / Published: 3 March 2023
(This article belongs to the Special Issue New Trends in Computational Intelligence and Applications 2022)

Round 1

Reviewer 1 Report

1. Add (GSA) in the abstract or define it in the Introduction.

2. It is not clear in the abstract when the authors refer to previously published results or "compared with the previous ones". What previous results or methodologies are they referring? Please improve abstract.

3. In the introduction it is mentioned that the methodology "only requires knowing the transformer capacity, voltages and currents on its primary and secondary windings" nominal or measured since they comment that the proposed methodology is for when the transformer is in operation, please clarify.

4. please specify with more detail the contribution of your work and how innovative or improved compared with [4].

5. The results showed that the estimation of its parameters has a greater error in Distribution Transformers than in Power Transformers, could the authors explain something more about this or was it just a coincidence that the error was greater in small transformers.

6. Please improve the conclusions, perhaps the answer to the previous point can be added to the conclusions.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Please see the attached document.

Comments for author File: Comments.pdf

Author Response

Please, see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thank you for the revised version of the article. The article now looks much better and can be recommended for publication. 

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