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Article
Peer-Review Record

Statistical Comparison of Time Series Models for Forecasting Brazilian Monthly Energy Demand Using Economic, Industrial, and Climatic Exogenous Variables

Appl. Sci. 2024, 14(13), 5846; https://doi.org/10.3390/app14135846
by André Luiz Marques Serrano 1,†, Gabriel Arquelau Pimenta Rodrigues 1,†, Patricia Helena dos Santos Martins 2,†, Gabriela Mayumi Saiki 1,†, Geraldo Pereira Rocha Filho 1,3,†, Vinícius Pereira Gonçalves 1,† and Robson de Oliveira Albuquerque 1,*,†
Reviewer 1: Anonymous
Reviewer 2:
Reviewer 3:
Appl. Sci. 2024, 14(13), 5846; https://doi.org/10.3390/app14135846
Submission received: 24 May 2024 / Revised: 26 June 2024 / Accepted: 27 June 2024 / Published: 4 July 2024
(This article belongs to the Special Issue Advanced Forecasting Techniques and Methods for Energy Systems)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors This manuscript reports the evaluation of some methods in terms of their ability to predict electricity demand in Brazil.    The authors explain the importance and originality of their work. Although they do not introduce new methods or suggest improvements, they provide a comprehensive overview and overall evaluation of the models considered within their scope. Overall, this is a well-written manuscript, which in my opinion is consistent with the content of the journal.   Apart from one important question, I have made some minors recommendations that I think will improve the quality of the manuscript.   Main question -row 510: I cannot understand where in the Figure 7 we conclude that air temperature and energy consumption have a strong positive correlation. Can you explain this?   Minor recommendations/ questions -row 43: What are (7.A,7.B) at the of the sentence?  -row 275: It is common to quote the whole phrase the first time we use an abbreviation, i.e., "... Gross Domestic Product (GDP) ...". -row 473: I think it is appropriate to cite the original paper, when presenting the Granger Casuality test. (confirm to be sure, I think this is it; https://doi.org/10.2307/1912791). -row 491: A bracket is missing after "(Figure 6b.". -row 570: There seems to be a logical inconsistency in the interpretation of the MPE values. If the values you refer to at the end of the sentence are the actual values, then we are overestimating (not underestimating) them. If the values correspond to the prediction, I believe this needs clarification. -row 706: There is an unnecessary "i" in the sentence.   - general remark Provide the nessecary general reference for the models examined, when first mentioned 

Author Response

Response to Reviewer 1 Comments

This manuscript reports the evaluation of some methods in terms of their ability to predict electricity demand in Brazil.    The authors explain the importance and originality of their work. Although they do not introduce new methods or suggest improvements, they provide a comprehensive overview and overall evaluation of the models considered within their scope. Overall, this is a well-written manuscript, which in my opinion is consistent with the content of the journal.   Apart from one important question, I have made some minors recommendations that I think will improve the quality of the manuscript. 

 1) Main question -row 510: I cannot understand where in the Figure 7 we conclude that air temperature and energy consumption have a strong positive correlation. Can you explain this?

We deeply appreciate the evaluation carried out by the reviewer. We acknowledge that the sentence was not well written. In fact, the correlation exists between the air temperature and the energy consumption seasonal pattern, not the energy consumption as a whole. We have rewritten the sentence (Section 4.5.2, line 554 of the highlighted version of the manuscript) to clarify that, enabling a more correct interpretation of Figure 7.

2) Minor recommendations/ questions -row 43: What are (7.A,7.B) at the of the sentence?

We express our sincere gratitude for your invaluable review of our work. It refers to the Sustainable Development Goals 7.A and 7.B. To clarify the information, we have added the “SDG” abbreviation in all mentions of the goals, especially in the paragraphs 2 to 4 of the Introduction (lines 25 to 43).

3) -row 275: It is common to quote the whole phrase the first time we use an abbreviation, i.e., "... Gross Domestic Product (GDP) ...".

We are thankful for your observation. We have corrected this, using the whole phrase before the abbreviation.

4) - row 473: I think it is appropriate to cite the original paper, when presenting the Granger Casuality test. (confirm to be sure, I think this is it; https://doi.org/10.2307/1912791).

We greatly appreciate the reviewer's comments. We have confirmed the reference and, acknowledging the importance of citing it, we have done so.

5) -row 491: A bracket is missing after "(Figure 6b.".

We appreciate your review. We have included the missing bracket.

6) -row 570: There seems to be a logical inconsistency in the interpretation of the MPE values. If the values you refer to at the end of the sentence are the actual values, then we are overestimating (not underestimating) them. If the values correspond to the prediction, I believe this needs clarification

We are deeply grateful for the review. We have rewritten the sentences (lines 619 to 626), hoping to achieve a clea'rer phrasing. We have also included a reference to Equation 2, that defines the MAPE metric, to help the reader understand what is being said.

7) -row 706: There is an unnecessary "i" in the sentence.

We appreciate the accurate observation. We have removed the unnecessary letter.

8) - general remark Provide the necessary general reference for the models examined, when first mentioned

We are very grateful for the observation. As requested by the reviewer, the captions were placed in the first graph of Figures 21, 22, 23, and 24. We enlarged Figures 21 to 24 so that they could be fully appreciated by readers.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The paper compares a variety of methods for forecasting energy demand in Brazil. The research has some value and the workload is sufficient, but the following contents need to be revised before the formal publication:

Comment 1: The title of the paper needs to be revised to better reflect the innovation of the research.

Comment 2: Innovation points need to be further strengthened. In the introduction, the innovation points need to be broken down.

Comment 3: Figure 2 font is too small.

Comment 4: In the literature review section, SARIMA, Prohphet, HOLT-winters, and TBATS are some old. TFT methods is used in the field of energy forecasting in recent years, which can be added to the discussion, such as: doi.org/10.1016/j.energy.2024.130782 and doi.org/10.1016/j.energy.2023.129728.

The experimental part is well discussed, good work.

Comments on the Quality of English Language

Fine.

Author Response

Response to Reviewer 2 Comments

The paper compares a variety of methods for forecasting energy demand in Brazil. The research has some value and the workload is sufficient, but the following contents need to be revised before the formal publication:

1) The title of the paper needs to be revised to better reflect the innovation of the research.

We would like to thank you immensely for reviewing our work. To improve the quality of the title, we have rewritten it. We recognize that now it better presents the innovation of the work and the research conducted.

2) Innovation points need to be further strengthened. In the introduction, the innovation points need to be broken down.

We express our gratitude for the review. We created Section 1.1 (line 81 of the highlighted version), in which we explicitly present the novelty and contributions of the work.

3) Figure 2 font is too small.

We acknowledge and thank the reviewer for the comment. We have edited the image, increasing the font size where needed, and also increased the figure size in the LaTeX source code. We believe this new version of Figure 2 is easier to read.

4) In the literature review section, SARIMA, Prohphet, HOLT-winters, and TBATS are some old. TFT methods is used in the field of energy forecasting in recent years, which can be added to the discussion, such as: doi.org/10.1016/j.energy.2024.130782 and doi.org/10.1016/j.energy.2023.129728

We are very grateful for the reviewer's valuable observation. Acknowledging the importance of the TFT methods, we have mentioned it in the limitations of the work (lines 104 to 108), in the suggestions of future works (lines 786 to 789), and in the literature review (line 129). In the latter, we have included citations to the mentioned  studies.

5) The experimental part is well discussed, good work.

We appreciate your review and valuable comments.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This study investigates the impact of economic, industrial, and climatic variables on energy demand forecasting models in the Brazilian energy sector and conducts a comparative analysis. The research aims to promote sustainable development in the energy sector through effective management of forecasting models, aligning with the objectives of the United Nations Sustainable Development Goal 7 (SDG7). Some suggestions are listed below:

 

The review of this paper primarily focuses on the following aspects: research methodology, data analysis, the rationality of conclusions, and academic norms and ethics. It is suggested that further discussions on the limitations of the study's findings and potential future research directions be included in the conclusion section.

Specific details regarding model selection and parameter settings can be further supplemented and explained to enhance the readability and reproducibility of the article.

In the discussion section, comparisons with energy forecasting models in other countries or regions can be added to highlight the uniqueness and contributions of this study.

Comments on the Quality of English Language

Generally fine

Author Response

Response to Reviewer 3 Comments

This study investigates the impact of economic, industrial, and climatic variables on energy demand forecasting models in the Brazilian energy sector and conducts a comparative analysis. The research aims to promote sustainable development in the energy sector through effective management of forecasting models, aligning with the objectives of the United Nations Sustainable Development Goal 7 (SDG7). Some suggestions are listed below:

1) The review of this paper primarily focuses on the following aspects: research methodology, data analysis, the rationality of conclusions, and academic norms and ethics. It is suggested that further discussions on the limitations of the study's findings and potential future research directions be included in the conclusion section.

We are very grateful for the reviewer's valuable observation. To address it, we have created Section 1.1, in which we present the contributions and also the limitations (lines 100 to 108) of the work. These limitations are mentioned as future works suggestions in the conclusion (lines 786 to 789).

2) Specific details regarding model selection and parameter settings can be further supplemented and explained to enhance the readability and reproducibility of the article.

We would like to express our great gratitude for the comment kindly made by the reviewer. We have created Section 5.1 (line 587) to specify the models selection, parameters settings (as according to other sections of the paper) and other training configurations. We believe that this section greatly improves the reproducibility of the work.

3) In the discussion section, comparisons with energy forecasting models in other countries or regions can be added to highlight the uniqueness and contributions of this study.

We greatly appreciate the reviewer's suggestion. We have included a paragraph in Section 2.3 (lines 278 to 288) in which explicitly mention the novelty and contributions of this work in relation to the others previously mentioned in Table 3 (works in other countries and regions) and in Section 2 (literature review) as a whole.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

It can be accepted.

Author Response

We deeply appreciate your accurate reviews and now acceptance of our work.

Anyway, we provide the reviewer the latest reviewed version of the article.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This study is well completed and innovative to a certain extent. There is just one small suggestion: Please illustrate the results with the properties of these models and explain why.

Comments on the Quality of English Language

Generally fine

Author Response

1) This study is well completed and innovative to a certain extent. There is just one small suggestion: Please illustrate the results with the properties of these models and explain why.

We would like to thank you immensely for reviewing our work. To clarify the parameters selection for each model, we have restructured the Materials and Methods section (Section 3). It is now subdivided into three subsections, describing 3.1) the dataset, 3.2) the data analysis, and 3.3) the models evaluation and forecasting.

We have added lines 343 to 349 in Section 3.1 that better explain the models parameters selection. We have also rewritten the first paragraph of Section 5.1 (lines 622 to 625) so that they justify the parameters selection for these models, including a table column that points to the sections of the paper that more deeply presents the reasoning behind the parameters definitions.

We have also noted a mistake on the previous version of the manuscript, stating that one of the data sources was IBGE, when it actually was the Brazilian Association of Electric Vehicles (ABVE). We have corrected this information both on the text (lines 301 to 306) and on Figure 2. Now Section 3 accurately represents the methodology implemented in the work.

Author Response File: Author Response.pdf

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