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Article
Peer-Review Record

Energy-Efficient Power Scheduling Policy for Cloud-Assisted Distributed PV System: A TD3 Approach

Appl. Sci. 2023, 13(21), 11611; https://doi.org/10.3390/app132111611
by Hao Zhang 1, Fuhao Liu 2, Baichao Ma 3, Shengfang Zhang 4, Yuxin Peng 2, Rentao Gu 2 and Jiansong Miao 2,*
Reviewer 1:
Reviewer 2:
Reviewer 3: Anonymous
Reviewer 4: Anonymous
Appl. Sci. 2023, 13(21), 11611; https://doi.org/10.3390/app132111611
Submission received: 7 September 2023 / Revised: 11 October 2023 / Accepted: 19 October 2023 / Published: 24 October 2023
(This article belongs to the Special Issue Intelligent Systems and Renewable/Sustainable Energy)

Round 1

Reviewer 1 Report

The report is attached.

Comments for author File: Comments.pdf

The English is fine. Minor edits are needed.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

nergy-Efficient Power Scheduling Policy for Cloud-assisted

Distributed PV System: A TD3 Approach

After reviewing the paper the following modifications are required before go to the next stages 

 

1. The current research novelty explanation need to improve clearly for the readers

2. Compare the present technique involved with previous techniques with a comparison table interms of the parameters

3.  Explain clearly Energy Storage Device Operation Model in the research paper with required parameters

4. Give the comparison table for Convergence performance of different parameters how they are varied for required algorithm

5. Include more recent works related to the research and its comparison for the proposed algorithm 

Need to be improved

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

I do appreciate the work and the presentation, keeping simple but concise. 

However, a very straightforward scenario has been taken for validation of the algorithm. I propose to also consider a couple of more cases/examples to have a more deep insight of the effectiveness of the twin delayed DDPG algorithm. Thanks

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 4 Report

Paper presents Energy-Efficient Power Scheduling Policy for Solar PV parks. Here are some critical observations, in the light of which the paper can be improved before moving towards publication:

1. How many PV parks your system can adjust?

2. What is O2 complexity of your algorithm and how the complexity of algorithm rises with increase in Solar Park

3. What will happen in the case where two plants are demanding energy while one plant has excess energy. How you set the priority, there is no as such variable

4. In your system, the net metering is essential part for system to work, kindly provide/incorporate the net-metering aspect in the system

5. How you schedule the priority of the energy-demanding and supply-given parks. Either it is Run-time work or some intelligent mechanism or first-serve-first-come basis or proximity basis etc. Is there any cost function for that.
   For instance, 1 Park has more power supply and you can deliver the power to only another single Park but two Parks are demanding energy. What your algorithm will do? 

6. How you generate the PV cases for simulation studies? Something from practical scenario or just self presented cases? Is there any kind of guidelines for such system in your country, if yes, kindly refer. 

7. Simulation studies are limited. Provide more results in the light of remark-    

Minor Edit in English especially in abstract is required

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The author has adquately replied to my comments, so the manuscript is recommended for publication

The English writing is sufficiently clear.

Reviewer 2 Report

After revisions the paper is good

Reviewer 3 Report

Thanks for responding positively. 

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