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Peer-Review Record

X-Model: Further Development and Possible Modifications

Forecasting 2020, 2(1), 20-35; https://doi.org/10.3390/forecast2010002
by Sergei Kulakov
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3:
Forecasting 2020, 2(1), 20-35; https://doi.org/10.3390/forecast2010002
Submission received: 10 December 2019 / Revised: 25 January 2020 / Accepted: 29 January 2020 / Published: 3 February 2020

Round 1

Reviewer 1 Report

The proposal made seems quite interesting and is properly presented in the article. I have no specific objection or suggestion to improve it.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

The author creates a new version of the X-model. The author uses previous papers to describe what is doing for the new version of the X-model. The X-model is a model that uses the aggregate supply and demand curve to forecast the day-ahead market prices.

This paper proposes a variation in the X-model through the transformation of the elastic aggregate demand curve into a new inelastic demand curve and a new aggregate supply curve using published theory.

The reviewer sees a clear contribution to making forecasts compared with previous theories. However, the paper fails in several points that the author should improve.

The main goal of the paper should be specified in the abstract as well as in the introduction section. The main purpose is to improve the X-model, which is used to forecast the day-ahead market prices. This purpose of forecasting is not mentioned in the abstract and paper. The methodologies should be presented in the paper, and the author references other papers. However, this paper should have all the information needed to be reproduced easily by the reader, and it does not happen. The theory used should be present in the paper; this is the X-model and an easy example of the aggregate demand and supply curve transformed into the inelastic demand with a new aggregate supply curve. The author should create a diagram with the different steps that were needed for all the processes of forecasting and put these steps in order. Hence, the author needs to improve the Methodology section. The nomenclature of the models and equations should be legible. If they are not defined in the paper, the reader cannot understand what the author is doing. References need to be revised, for example, refs. 2, 5, and 9, where are they published? Regarding the figures, the units are presented between brackets. Could does the author use this format in all figures, please? Better if the volume is considered as energy (MWh) than (MW) for all the paper. Please, check that the volume in Figure 4 is fixed as EUR/MWh, please correct it, MWh. If you include the coin as EURO better than EUR in the figures, only an O that is not saving too much space.

 

 

 

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 3 Report

I read with interest the proposed work. The work presents new elements and an interesting approach to the topic. However, I would recommend a review of the organization of the text, in order to better clarify the presentation of the method, a more detailed presentation of the results and a more in-depth discussion of them.

More in detail.
Line numbers are not present in the whole text, so it is difficult to refer to specific lines. This is a common problem with Latex, and solutions can be found on the web.

The introduction part should be revised by providing a general overview of the problem, before describing the reference model used. In particular, it would be appropriate both to describe the general scenario and to illustrate the reasons that led to the selection of the X-model as the subject of this study.
The whole part of the description of the X-model up to line 38 should be expanded and redefined as a description of the model used, including it in section 3 on methodology.
The literature review part should, therefore, be revisited and put into a general overview of the problem.
The contribution provided by the article should be included at the end of the introduction as a logical development of the scenario described in the text.

In the description of the methodology, the part related to the removal of outliers and the impact they may have on the performance of the model does not appear clear from the text, and in my opinion deserves a separate section, related to data filtering, with a description of the techniques used. Furthermore, if the presence of outliers and their non-removal may lead to a significant deterioration in the model's performance, this should be discussed in the results discussion part.

The part related to the presentation of the results is not in my opinion sufficiently detailed, the Naive comparison model is not described, and also the comparison with the X-model methodology cannot be limited to the average result over the year.
A more detailed comparison could cover some characteristic cases, showing when the model performs better (or particularly better) and when it performs worse than the benchmarks. The results could also highlight the conditions under which the model shows the best performance and those under which it performs suboptimally and therefore its weaknesses and possible directions of research.

This would allow a real discussion of the results, which is missing from the proposed text.

The conclusions, in addition to a realistic assessment of the contribution provided by the article, could also indicate future developments in this research.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

I have no further relevant questions. I am fully pleased with the revision made.

Reviewer 3 Report

Dear authors, thank you for your work on the review.

In my opinion, the text has improved and is worthy of publication in its current form.

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