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Article
Peer-Review Record

The Wind and Photovoltaic Power Forecasting Method Based on Digital Twins

Appl. Sci. 2023, 13(14), 8374; https://doi.org/10.3390/app13148374
by Yonggui Wang *, Yong Qi, Jian Li, Le Huan, Yusen Li, Bitao Xie and Yongshan Wang
Reviewer 1: Anonymous
Reviewer 2:
Appl. Sci. 2023, 13(14), 8374; https://doi.org/10.3390/app13148374
Submission received: 29 June 2023 / Revised: 15 July 2023 / Accepted: 18 July 2023 / Published: 19 July 2023

Round 1

Reviewer 1 Report

The study is impressive and promising for the planning of renewable energy systems in the future. 

- There are some minor grammatical and syntax errors. Please check the manuscript for these errors. For example: ‘…comprises PV(PV) power, wind…’

- Figure 1 caption should be revised. Instead of using a long explanation in the Figure caption, a short descriptive caption can be given. The figure can be explained in the text. Same for Figure 2.

- A detailed modeling procedure should be given for the digital twin platform of the AI (Artificial Intelligence) Grid. How did you model the digital twin of the connection elements like inverters, transformers, power lines, etc. Is the presented model only based on the data of wind and solar? If it is like this, we can not say it is a grid digital twin platform.

- Reliability of the data also should be investigated.

- The reliability of the digital twin platform should be investigated. Aging of the system and deviations from the rated values, losses, new connections that change the power flow in the system, and etc should be considered.

Author Response

Response to Reviewer 1 Comments

 

Point 1: There are some minor grammatical and syntax errors. Please check the manuscript for these errors. For example: ‘…comprises PV(PV) power, wind….

 

Response 1: We are very grateful for your corrections to your review comments. You have mentioned some minor grammatical and semantic errors. We have checked our manuscript and corrected these issues. In the revised version, we have changed the sentence to read:"... including PV, wind power..." . Other grammatical and ambiguity errors present in the article will also be corrected. Thank you again for your review comments, which are very helpful in improving the quality of our text.

 

Point 2: Figure 1 caption should be revised. Instead of using a long explanation in the Figure caption, a short descriptive caption can be given. The figure can be explained in the text. Same for Figure 2.

 

Response 2:Thank you very much for your review comments. You suggested that we revise the titles of Figures 1 and 2 to use short descriptive titles rather than lengthy explanations. We strongly agree with your suggestion, as it will improve the clarity and readability of the figures and make the explanations of the figures in the text more accurate and detailed. We will revise the titles of Figures 1 and 2 according to your suggestions to better meet your requirements. Thank you again for your valuable comments, which are very helpful to us in improving the quality of the manuscript.

 

Point 3: A detailed modeling procedure should be given for the digital twin platform of the AI (Artificial Intelligence) Grid. How did you model the digital twin of the connection elements like inverters, transformers, power lines, etc. Is the presented model only based on the data of wind and solar? If it is like this, we can not say it is a grid digital twin platform.

 

Response 3:Thank you very much for your review comments. You asked for a detailed modeling procedure for the AI (Artificial Intelligence) Grid Digital Twin Platform and asked how we model the digital twin of connected components such as inverters, transformers, and power lines. You also mentioned whether we are modeling based on wind and solar data only and whether such a model can be called a grid digital twin platform.

We understand your concerns and requirements. Our digital twin platform does cover the modeling of connected components such as inverters, transformers, power lines, etc., and we have modified it to detail the modeling procedures we use in the appendix of the text, along with a visualization of the results in the appendix.The power prediction model we constructed is capable of predicting the power generation of other power types by adjusting the model parameters, but the main focus of our work is on the prediction of wind and photovoltaic power generation, so we do not mention the details of other types of power prediction in the paper. In our future work, we will continue to engage in power prediction research. Our goal is to build a comprehensive and integrated grid digital twin platform to simulate and optimize all aspects of the power system. Thank you again for your valuable comments, which are very helpful for us to improve our research and the quality of the paper.

 

 

Point 4: Reliability of the data also should be investigated.

 

Response 4:Thank you very much for your review comments. You mentioned that we should also investigate the reliability of the data. This is a very important point and we fully agree with your comments.

In our study, we place great importance on the reliability and accuracy of the data. We take a variety of measures to ensure that the data sources we use are reliable. This includes careful screening and validation of data sources, use of data from recognized and reliable data providers or authorities, and multiple cross-validation and calibration of data.

In addition, we will describe in detail the specific information and sources of the data sources we used in the text and cite them in the references so that readers are aware of the assurances of data reliability in our study. We will emphasize the source and quality of the data and clearly state that our study was conducted based on reliable data.

Thank you again for your review comments, and we will continue to strengthen our investigation and explanation of data reliability to ensure the credibility and reliability of our study in this regard. Your comments are very helpful for further improvement of our study!

 

 

Point 5: The reliability of the digital twin platform should be investigated. Aging of the system and deviations from the rated values, losses, new connections that change the power flow in the system, and etc should be considered

 

Response 5: Thank you very much for your review comments. You mentioned that we should investigate the reliability of the digital twin platform and consider factors such as system aging, deviation from ratings, losses, and changes in tidal currents in the system. Your comments are very pertinent and we fully agree with you.

We primarily focused on the factors influencing wind and solar power generation due to natural conditions, but we did not extensively analyze unforeseen events such as equipment failures. However, we acknowledge the importance of investigating these issues and plan to delve deeper into them in future work. We have mentioned this point in the concluding section of the paper as well.

Thank you again for your review comments, your suggestions are invaluable for us to further improve the reliability analysis of the digital twin platform.

Author Response File: Author Response.docx

Reviewer 2 Report

In this paper a digital twin-based method for predicting wind and PV power utilizing digital twin technology which provides a highly realistic simulation environment that enables accurate monitoring, optimal control, and decision support for power system operations. In this paper, a good topic is proposed and well organized. The following comments need to be addressed by the authors:

1) Introduction section must be more completed. It mainly can include four key components: motivation, literature survey (newly published paper should be presented (2020-2023)), research gap statement, contributions, and the organization of the paper. Please modify this section accordingly. Some papers such as below can be effective for literature review in this paper: Stochastic optimization – based economic design for a hybrid sustainable system of wind turbine, combined heat, and power generation, and electric and thermal storages considering uncertainty: A case study of Espoo, Finland; Stochastic-Metaheuristic Model for Multi-Criteria Allocation of Wind Energy Resources in Distribution Network Using Improved Equilibrium Optimization Algorithm; Deterministic and probabilistic multi-objective placement and sizing of wind renewable energy sources using improved spotted hyena optimizer.

2) Research gap should be presented accurately in a separate paragraph.

3) Paper organization is missing the end of the introduction section.

4) How are modeling and forecasting errors included in the presented approach?

5) Future work and research limitations should be presented in the conclusion section.

 

 

 

Minor editing of English language required.

Author Response

Response to Reviewer 2 Comments

 

Point 1:Introduction section must be more completed. It mainly can include four key components: motivation, literature survey (newly published paper should be presented (2020-2023)), research gap statement, contributions, and the organization of the paper. Please modify this section accordingly. Some papers such as below can be effective for literature review in this paper: Stochastic optimization – based economic design for a hybrid sustainable system of wind turbine, combined heat, and power generation, and electric and thermal storages considering uncertainty: A case study of Espoo, Finland; Stochastic-Metaheuristic Model for Multi-Criteria Allocation of Wind Energy Resources in Distribution Network Using Improved Equilibrium Optimization Algorithm; Deterministic and probabilistic multi-objective placement and sizing of wind renewable energy sources using improved spotted hyena optimizer.

 

Response 1:Thank you for your review comments. Based on your suggestions, we will revise the introduction section to include more complete content. Below are examples of the changes made to each of the key components based on the information you provided:

(1) We have reworked the introduction section by adding 1.1 Literature Review; 1.2 Research Gaps, Contirbutions, and Objectives; 1.3 Paper Structure

(2) Literature Survey: We modified the Literature Survey section to include the most recently published papers (2020-2023) and consolidated all the literature into Table 1.

Thank you again for your valuable comments, we have revised the introduction section according to your suggestions to make it more complete and accurate. Your review comments are very helpful for us to improve the paper .

 

 

Point 2: Research gap should be presented accurately in a separate paragraph.

 

Response 2 Thank you very much for your review comments. You mentioned that the research gaps should be accurately presented in a separate paragraph. We strongly agree with your suggestion that presenting the research gaps in a separate paragraph would more clearly highlight the value and innovation of our study.

Based on your comments, we will add a dedicated paragraph in section 1.2 of the introduction section detailing existing research gaps and unresolved issues in the research area.

Such modifications will make our research gaps clearer and readers will be able to better understand the importance of our research in academia and practice.

Thank you again for your review comments and we have followed your suggestion to add a separate paragraph in the introduction section to present the research gaps in detail. Your suggestions are invaluable to us in improving the structure and content of the paper.

 

Point 3: Paper organization is missing the end of the introduction section.

 

Response 3:Thank you very much for your review comments. You have pointed out that our paper is organized with a missing ending in the introduction section. We strongly agree with you and will add an appropriate ending to the introduction section.

Based on your suggestion, we will expand the ending of the introduction section appropriately. We will summarize the main points of the introduction section and provide a bridge for the reader to transition to the main body of the paper. In the conclusion, we will also emphasize our research objectives and contributions, as well as the importance of this study to the field. And 1.3 paper structure was added to ensure that readers have a clear understanding of the structure of the essay.

With this revision, our introduction section will be more complete and coherent so that readers can clearly understand the background, research objectives and significance of the paper.

Thank you again for your review comments, and we have added a conclusion to the introduction section based on your suggestion. Your valuable comments are very helpful for us to improve the structure and content of the paper.

 

Point 4: How are modeling and forecasting errors included in the presented approach?

 

Response 4:Thank you very much for your review comments. For the digital twin modeling error, we improved the modeling accuracy by studying and understanding the system in depth, using more accurate physical modeling algorithms, and consulted experts in related fields to obtain their relevant knowledge and experience in this field, which helped us to reduce the modeling error.

The problem of dealing with prediction errors. First, we performed data preprocessing, including data cleaning, screening, and normalization steps to reduce the effects of noise and outliers and to improve the quality of the data. Second, we performed feature engineering to select suitable feature variables and transform, combine, or downscale them to improve the expressive power and prediction accuracy of the model. Then, we adopted a cross-validation method to evaluate the generalization ability of the model and validated it on multiple training and test sets, where the ratio of the training set to the test set is 8:2. And in order to more scientifically and comprehensively evaluate the wind and PV power load forecasting models proposed in this study, we chose the mean squared error (MSE), the mean absolute error (MAE) and the root mean square error (RMSE) as the evaluation metrics so that we can better estimate the performance of the model on unseen data and obtain more accurate prediction error estimates.

Overall, in our approach, we actively consider modeling and prediction errors and take appropriate measures to assess, minimize, or report the impact of these errors. This contributes to the reliability of the models and the accuracy of the results, and enhances the understanding of uncertainty.

Thank you very much for your review comments, and we have provided more specific answers based on your suggestions. Your suggestions are very helpful for us to improve the paper!

Point 5: Future work and research limitations should be presented in the conclusion section.

 

Response 5:Thank you very much for your review comments. You pointed out that we should present future work and research limitations in the conclusion section. We strongly agree with you and will include these in the conclusion section.

Following your suggestion, we will detail in the conclusion section the directions for future work, i.e., issues that need to be further explored and investigated in our research area. We will suggest some possible directions for expansion and improvement in order to facilitate academic and practical progress.

At the same time, we will also honestly discuss the limitations of our research. These limitations may include cross-region prediction, cross-system prediction, and the impact of equipment issues, to name a few. We will clearly point out these limitations and use the issues of these limitations as a major direction for future research.

By including future work and research limitations in the conclusion section, we are able to provide a comprehensive research perspective and provide valuable references and inspiration for future researchers.

Once again, thank you for your review comments, and we have followed your suggestion to present future work directions and research limitations in the conclusion section. Your valuable comments are very helpful for us to improve the structure and content of the paper!

Author Response File: Author Response.docx

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