Branch error reduction criterion-based signal recursive decomposition and its application to wind power generation forecasting

Fen Xiao; Siyu Yang; Xiao Li; Junhong Ni

doi:10.1371/journal.pone.0299955

Peer Review History

Original SubmissionAugust 25, 2023
9 Jan 2024 Decision Letter - Samuel Asante Gyamerah, Editor PONE-D-23-26209Branch Error Reduction Criterion-Based Signal Recursive Decomposition and Its Application to Wind Power Generation ForecastingPLOS ONE Dear Dr. li, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Jan 14 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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We will update your Data Availability statement to reflect the information you provide in your cover letter. 6. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] 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 ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 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. 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(Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This is a very good study which is novel. Hybrid methods are known to perform better than the underlying or single methods to analyse data. The authors also presented the same work with some level of great detail into the suggested method. However, there are few corrections that may need to be done. In line 18 its written In Ref. [6] which i presume was supposed to write the author's name like what the authors did in line 19. This needs correction. Similar mistake is made in line 24 and 43. Decomposition has been used as a preprocessing method in many studies as also cited in this paper. I suggest adding one or 2 sentences after paragraph 1 in Introduction justifying why the wind generation data needs to be decomposed. In Line 192 I suggest carrying out stationarity Tests such as the Augmented Dickey-Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test and then make a conclusion that the data is non-stationary. It would be interesting to add few more years instead of using only 2 years to carry out a study. Reviewer #2: The motivation for the study has been well explained. Choice of Branch Error reduction over VMD has been duly justified. Recommendation for practice and further studies have been given. Some statements in the introductory section need to be cited ****** 6. 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? 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Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0299955.r001
Revision 1
25 Jan 2024 Author Response To Academic Editor Thank you so much for your professional and valuable comments on our manuscripts, we have made changes and improvements accordingly. Comments: 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. Reply: Thank you so much for the kind suggestion. We have carefully checked our manuscript to ensure that this manuscript meets PLOS ONE's style requirements. 2. Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, all author-generated code must be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse. Reply: Thank you very much for your reminder. The code has been packaged for easy running. 3. The Funding Statement and Competing Interests Statement need to be updated. Reply: Thank you for your kind suggestion. The Funding Statement and Competing Interests Statement are updated. 4. Funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form. Please include your amended statements within your cover letter; we will change the online submission form on your behalf. Reply: Sorry for the oversight, the funding information has been placed in Funding Statement section of the online submission form. The updated Funding Statement is as the following: Funding information: State Grid Fujian Electric Power Co. Ltd.: SGTYHT/20-JS-223(SGFJJY00GHJS2200054). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder provided support in the form of salaries for authors Fen Xiao and Siyu Yang, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. 5. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. Reply: Thank you for your suggestion. The minimal data set used in the manuscript has been uploaded as Supporting Information. 6. Please review your reference list to ensure that it is complete and correct. Reply: Thank you for the kind suggestion. All references have been checked carefully. Four new references have been supplemented. To Reviewers #1 We really appreciate the professional and valuable comments on our manuscript. We have made the revisions and improvements accordingly. 1. In line 18 its written In Ref. [6] which i presume was supposed to write the author's name like what the authors did in line 19. This needs correction. Similar mistake is made in line 24 and 43. Reply: Thank you for the kind suggestion. The citations formats have been corrected accordingly. 2. Decomposition has been used as a preprocessing method in many studies as also cited in this paper. I suggest adding one or 2 sentences after paragraph 1 in Introduction justifying why the wind generation data needs to be decomposed. Reply: Thank you for the professional comment. The reason for the decomposition of the generation time series is supplemented at the beginning of the 4th paragraph in the introduction section: “The time series of electricity generation is generally a broadband signal, and its future trend is not stable. Therefore, it is difficult to approximate the relationship between historical measurements and its future changes. The future trend of a narrowband signal is normally considered to be more stable. Therefore, the second type of hybrid model is used to decompose the time series of power generation into narrowband modes, and the final forecasted results are obtained by summarizing the forecasted results of each mode” (Line 37-43). 3. In Line 192 I suggest carrying out stationarity Tests such as the Augmented Dickey-Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test and then make a conclusion that the data is non-stationary. Reply: Thank you for the enlightening comment. The ADF test results of partial and total generation time series of 2020 and 2021 are supplemented to Table 2 in the revised manuscript. Detailed statistics of the ADF test are also presented in Table R.1, which indicates the non-stationarity of the time series data. Due to limited space, can we just not show Table R.1 in the revised manuscript, thank you. Table R.1. ADF test results and critical values (in 'Response to Reviewers.docx') 4. It would be interesting to add few more years instead of using only 2 years to carry out a study. Reply: Thank you for the practically significant suggestion. The historical data of power generation in Fujian Province from Jan 1 2012 to Jun 30 2022 is shown in Fig. R.1, with a total of 3834 daily power generation data. A total of 3653 power generation data in the decade 2012- 2021 is selected as the training set, and a total of 181 power generation data in the first six months of 2022 is selected as the testing set. The same comparison experiments are conducted against the manuscript and the results are shown in Table R.2. Fig. R.1 Power generation trend of Fujian Province from Jan o1 2012 to Jun 30 2019 (in 'Response to Reviewers.docx') Table R.2. Comparative experiments (in 'Response to Reviewers.docx') According to Table R. 2, the same conclusions can be drawn: a. More decomposition layers or more decomposition numbers cannot be equated with better decomposition effect; b. There are randomness and limitations in the final effect of direct decomposition and decomposition according to whether the center frequency is aliased; c. Recursive decomposition based on BER performs more consistently and efficiently in the experiment. Because the trend of power generation and the influencing factors change over time, the distribution of the dataset used for training is not consistent with the new data, resulting in the previous model not being able to forecast the present data at a high level of accuracy, which indicates that the distribution drift occurs. Although the same conclusions can be drawn, the electricity generation data have several characteristics: they are highly influenced by policy, data distribution evolves over time. Compared with one year's data, too much experimental data seems to be less suitable for comparison and presentation to some extent. Therefore, would it be more succinct to use only single year data in the experiment? We look forward to your valuable suggestions. To Reviewers #2 The authors would like to thank you for taking the time to read our manuscript. We have modified our manuscript according to the suggestions and comments. 1. Some statements in the introductory section need to be cited. Reply: Thank you for the kind suggestion. In the introduction section, three references are supplemented, i.e., Ref [1], Ref [2] and Ref [4]. In the comparative experiments section, Ref [25] is supplemented. Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0299955.r002
20 Feb 2024 Decision Letter - Samuel Asante Gyamerah, Editor Branch Error Reduction Criterion-Based Signal Recursive Decomposition and Its Application to Wind Power Generation Forecasting PONE-D-23-26209R1 Dear Dr. li, 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. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Samuel Asante Gyamerah, Ph.D 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 #1: All comments have been addressed ******** 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 #1: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 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 #1: Yes ****** 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 #1: Yes ****** 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 #1: (No Response) ****** 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 #1: Yes: Willard Zvarevashe ******** https://doi.org/10.1371/journal.pone.0299955.r003
Formally Accepted
12 Mar 2024 Acceptance Letter - Samuel Asante Gyamerah, Editor PONE-D-23-26209R1 PLOS ONE Dear Dr. Li, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Samuel Asante Gyamerah Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0299955.r004

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