PONE-D-23-29182Using spatio-temporal graph neural network to estimate fleet-level photovoltaic performance loss ratePLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript entitled, “Using spatio-temporal graph neural network to estimate fleet-level photovoltaic performance loss rate” displays Spatio-Temporal Graph Neural Network for fleet-level PLR estimation (PV-stGNN-PLR) which decomposes the power time series data into aging and fluctuation components, utilizing the aging component to determine PLR. PV-stGNN-PLR exploits spatial and temporal coherence to derive PLR estimation for all systems in a fleet and imposes flatness and smoothness regularization in loss function to ensure the successful disentanglement between aging and fluctuation. There exist a few tribulations stated below that need to be corrected.

1. The authors have mentioned PLR in the ‘Introduction’ section of the manuscript which is supported by reference [5] in the manuscript. The author must express the formula for PLR in the present case as expressed by Deceglie et al. https://doi.org/10.1002/solr.202300196

2. What is POA in 6K model?

3. The authors have used several acronyms in the manuscript which need to be defined in the manuscript.

4. MAPE(%) is found least for PV-stGNN-PLR in all the three discussed cases in the manuscript. However, this loss function of PV-stGNN-PLR consists of a global reconstruction error with additional constraints applied individually to the fluctuation and aging terms. Is this is the reason for achieving low MAPE(%). Please justify!

5. Since your data contains seasonality, did you try Holt-winters exponential smoothing? It will be great to handle the time series data containing a seasonality.

6. Can you please explain why did you choose Euclidean distance and MAPE to evaluate PLR estimation errors? Did you consider any other Time Series Error metrics?

7. The alignment of the text in the manuscript is not justified.

8. Define ‘mqlj’ in the equation (3).

9. There are several grammatical errors in the manuscript.

10. References are randomly collected without any standard format style such as APA, Chicago. MLA, etc.

Reviewer #2: I really appreciate the research carried out in the proposed article and I wish to see it published. The paper is very well written and presented. I would be glad to see your future publications in this field.

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Reviewer #1: Yes: Shalini Tripathi

Reviewer #2: No

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Using spatio-temporal graph neural networks to estimate fleet-wide photovoltaic performance degradation patterns

PONE-D-23-29182R1

Dear Dr. Wieser,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Emanuele Crisostomi, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: (No Response)

Reviewer #4: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: (No Response)

Reviewer #4: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: (No Response)

Reviewer #4: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: (No Response)

Reviewer #4: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: (No Response)

Reviewer #4: The authors have adequately addressed comments of reviewers raised in a previous round of review. I have no issues to raise in this version of the manuscript. The paper is well-written and adequately describe the methods and results. The proposed algorithm can be applied in a wide range of tasks where separating aging and fluctuation is required.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: Yes: Dong Chen

Reviewer #4: No

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