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Electronics
Volume 9
Issue 2
10.3390/electronics9020289
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Article
Peer-Review Record

Very-Short-Term Power Prediction for PV Power Plants Using a Simple and Effective RCC-LSTM Model Based on Short Term Multivariate Historical Datasets

Electronics 2020, 9(2), 289; https://doi.org/10.3390/electronics9020289
by Biaowei Chen 1,2, Peijie Lin 1,2,*, Yunfeng Lai 1,2, Shuying Cheng 1,2, Zhicong Chen 1,2 and Lijun Wu 1,2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Electronics 2020, 9(2), 289; https://doi.org/10.3390/electronics9020289
Submission received: 30 December 2019 / Revised: 2 February 2020 / Accepted: 3 February 2020 / Published: 8 February 2020
(This article belongs to the Special Issue Emerging Technologies for Photovoltaic Solar Energy)

Round 1

Reviewer 1 Report

Authors have presented the work on the improvement of the accuracy of very-short-term (VST) photovoltaic (PV) power generation with help neural network. The work is performed/presented well and contain innovativeness. However, I have the following observations:

The abstract and conclusion part need to improve with some quantitative results. Line 159-163 is not required, rather, importance and innovativeness of the study need to highlight compare to the pertinent literature. Validation of the model with the literature will improve the quality of the paper. Update literature with few more papers like:  Back propagation artificial neural network (BPANN) based performance analysis of diesel engine using biodiesel. AIP J Ren Sus Energy 3, 013101. pp. 1-12. doi: 10.1063/1.3517229 Das B., Jha P., Rezaie B., Gupta R. (2017).

Author Response

 

Thanks for offering us the opportunity to further improve our work. Your time, effort and significant comments are greatly appreciated by all the authors. And please read the word attached.

Author Response File: Author Response.pdf

Reviewer 2 Report

Please read the comments attached.

Comments for author File: Comments.pdf

Author Response

Thanks for offering us the opportunity to further improve our work. Your time, effort and significant comments are greatly appreciated by all the authors. And please read the word attached.

Author Response File: Author Response.pdf

Reviewer 3 Report

The paper is well written. The main remarks are:

Page 4: Please provide also information about the latitude of the location.

Lines 206-207: Text need to be clarified.

Line 329: Change “Figure 7” with “Figure 8”.

Figure 17: Please check, no information is included.

There are some small typos which have to be corrected in the revised version.

Author Response

Thanks for offering us the opportunity to further improve our work. Your time, effort and significant comments are greatly appreciated by all the authors. And please read the word attached.

Author Response File: Author Response.pdf

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