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Article
Peer-Review Record

Day-Ahead and Intra-Day Optimal Scheduling Considering Wind Power Forecasting Errors

Sustainability 2023, 15(14), 10892; https://doi.org/10.3390/su151410892
by Dagui Liu 1,2, Weiqing Wang 1,*, Huie Zhang 3, Wei Shi 4, Caiqing Bai 5 and Huimin Zhang 5
Reviewer 1: Anonymous
Reviewer 3: Anonymous
Sustainability 2023, 15(14), 10892; https://doi.org/10.3390/su151410892
Submission received: 21 June 2023 / Revised: 6 July 2023 / Accepted: 7 July 2023 / Published: 11 July 2023

Round 1

Reviewer 1 Report

This paper describes a stochastic unit commitment problem. My comments are the following:

1. The paper needs English improvements. Proofreading by a native English speaker should be conducted to improve both language and organization quality. In addition, there are typos, like “scene”.

2.  The paper has reference errors, like “Error! Reference source not found.”.

3.  Section 1: the introduction requires major improvements. Please start with a brief explanation of the motivation of the paper, followed by a description of the background and research gaps. Then finalize the introduction with the contributions of the paper.

4.  Section 1: the literature review must be improved, only a few works are covered on the topics of stochastic unit commitment and scenario generation techniques for unit commitment problems.

5.   Section 1: what are the research gaps in the literature? The authors did not identify the research gaps. The authors need to identify the research gaps which they are planning to address in the paper.

6.       Section 1: what are the research contributions of this paper? The authors do not describe the research contributions. The authors need to describe the contributions and demonstrate that they fill the research gaps identified in the literature review.

7.       Section 2.1: there are more advanced methods in the literature to model the short-term uncertainty of renewables, like wind. For instance, only consider historical data to generate scenarios. State-of-the-art methods, like Gaussian copula methods, use probabilistic forecasts together with multivariate distributions to generate scenarios with temporal dependencies. Please comment on this.

8.       Section 4: U.S.-based unit commitment problems consider the electricity networks. Why did the authors not model the electricity network? Please provide a comment.

9.       Section 5.1: why did the authors only model the wind uncertainty? What about load uncertainty? Recent works on market optimization participation show that considering load and renewables uncertainties is relevant to reduce costs and avoiding network problems (e.g., 10.1016/j.segan.2022.100666). Please provide a comment, and possibly highlight this aspect as a limitation of this work.

10.   I strongly suggest improving the flow of the conclusion section. Start with a brief explanation of the paper, followed by a description of the main findings. Then finalize the conclusion with one or two suggestions for future work, and limitations.

 

I hope that my comments help the authors to improve their work.

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Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper analyses the day-ahead and intra-day optimal scheduling considering wind power forecasting errors. The research is timely, adds important insight to the current discussion about prices, and fits the scope of the Journal.

The Abstract in its current from is an alternative Introduction, it should clearly describe the scope with more focusing on the proposed approach and the specific results of the study to be applied to other cases.

The state-of-the-art overview on the problem is provided in the introduction, but it is more of the type "researcher X did Y" rather than an authoritative synthesis assessing the current state-of-the-art. Where do we stand today? What seem to be the best methods/models? Have they been properly designed?  Therefore, the literature review part of this paper lacks the recent studies. The works related to this topic were cited but the discussions about the weakpoint of the previous studies as well as the advantages of proposed method were not mentioned. Recently, there are several articles that are similar to this paper. What is specific contribution and novelty of this article?

Methodology: Provide sufficient detail to allow the work to be reproduced. Methods already published should be indicated by a reference with only relevant modifications described.

There is no "Data" section between "methodology" and "results". Open Questions: Which years are considered? Sources? Do you provide a repository to download the data?

The conclusion needs to be revised. Clear contributions about this manuscript need to be presented, while also supported by some data/percentage if possible.

 Moderate editing of English language required

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Please read the attachment. Thank you.

Comments for author File: Comments.pdf

fine

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

No further comments.

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Reviewer 2 Report

Accept in present form

 Minor editing of English language required

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