Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads
Round 1
Reviewer 1 Report
Metaheuristic method for a wind-integrated distribution network to support voltage stabilisation employing electric vehicle loads
Rehman N., et al.
The paper investigates the application of the beluga whale optimization technique for the determination of the optimal size of wind turbine generating systems, including the identification of the optimal position using the distribution load flow method based on the minimisation of the P-Index. The article is scientifically sound, interesting and well written, and, as such, recommended for publication after minor corrections are amended. In the reviewer’s opinion, the literature review could be improved by further clarifying the advantage of using meta-heuristic techniques as opposed to other optimisation techniques and by including additional references, which in some parts are missing. Proof-checking of the manuscript is also suggested. Some examples of corrections are as follows:
· More references should be added to the literature review
· Please do not use en-dash for numerical intervals, such as page 5
Author Response
The authors would like to thank the reviewer for the constructive insights on the paper, which have greatly enhanced the quality of the work. The point-wise responses are given below.
Comment 1: More references should be added to the literature review.
Response: Thank you for your insightful comment. The literature review has been revised in the context of the current state of the art. The publications have been incorporated and addressed in the updated version of the manuscript, and their serial numbers appear in the reference section as [6, 7, 8, 9, 10, 11, 12, 13, 14, and 16] updated in paragraph no. 1 of page no. 2 of the revised manuscript.
Comment 2: Please do not use en-dash for numerical intervals, such as page 5.
Response: Thank you for the constructive comment. We've updated the article to acknowledge your comment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
In the paper Authors proposed beluga whale optimization algorithm to determine the most suitable size of wind turbine generating systems. The optimal placements were determined by minimizing the P-index with use of the distribution load flow method. I find the paper well written and with high scientific soundness. Some text improvements however should be made (proofreading, e.g.: Tables 1 and 2 are in in reverse order, I would prefer seeing an algorithm instead of fig. 4. - also - I do not think putting a picture of a text is well-seen in scientific papers - could be a simple text field with text keeping source formatting instead). Finally I would like Authors to consider these two following issues:1) Have you considered any other optimization algorithm instead of beluga whale? Why do you find this one most suitable for the purpose. 2) Have you considered faults in the lines or other equipment and the problems that these could cause to your solution? What hazards are faults bringing into your solution? Have you consider protection issues coming from your optimization method?
Author Response
The authors would like to express their gratitude to the reviewer for his thorough evaluation as well as his perceptive remarks, both of which contributed to an overall enhancement of the work. The point-wise responses are given below.
Comment 1: Have you considered any other optimization algorithm instead of beluga whale? Why do you find this one most suitable for the purpose.
Response: The performance of different optimization algorithms was investigated through the use of certain performance indices. The performance criteria include the minimization of ISE and IAE, which are able to quantify the loss minimization. The effectiveness of the BWO is validated by comparing its performance index values with conventional PSO as depicted through graphical representations in Figs. 10 and 11 for each of the three scenarios. Additionally, BWO is a parameter-free optimization technique that does not require fine-tuning of its parameters, which gives it a striking advantage over other optimization techniques and has therefore been considered for the present application.
Comment 2: Have you considered faults in the lines or other equipment and the problems that these could cause to your solution? What hazards are faults bringing into your solution? Have you consider protection issues coming from your optimization method?
Response: The work presented in this paper is more confined to the proper and effective utilisation of DGs along with EVs for active and reactive power management in distribution networks. We are doing the steady-state analysis in this study; however, the fault and protection study itself is a big area to be explored and is our future scope, and we will report the results as soon as some breakthrough is achieved. Considering the fault studies will deviate the primarily objective of the presented work. However, authors are thankful to the reviewer for the valuable suggestion, and we will definitely incorporate this in our future projects.
Author Response File: Author Response.pdf
Reviewer 3 Report
This paper presents the optimal location of WTGS based on the matrix approach of DLF. The BWO technique was used to determine the suitable size of WTGS in accordance with EV loads. The topic is timely and interesting however I have questions and comments about the paper as follows:
1. Optimization algorithms can be classified into different types: deterministic, stochastic, and metaheuristic.
Please include the first paragraph of the literature review about other types of optimization algorithms, mentioning why you chose and used metaheuristic methods in your problem? What are the advantages of these methods over other methods in your case study? For example, why didn't you use linear or nonlinear programming?
2. Is there anyone in the literature who uses deterministic optimization algorithms (DG optimization)? If not, explain why.
Can you include this in the manuscript to make it more understandable and to motivate the reader? So, the reader will not think it is just an application . So, any optimization algorithm can work, no matter what it is.
3. Section 4 of the problem formulation, first paragraph on page 7.The other power elements, like capacitor banks, were negligible. If we consider them, what will happen? Will this increase the complexity of the problem, or do you think some features of the proposed algorithms will not work?
4. In Section 4.2, the objective function was only in the sizing of both WTGS and EV loads. But one of the major contributions of this work is to reduce power losses. I don't see reducing the power losses in either the objective function or the constraints.
5. In Section 4.3, the constraints don't include anything about the SOC limits, DLF limits, and/or WTGS constraints.
The authors mentioned nominal voltage levels for range (180V-230V) and SOC (10%-100%) in the last paragraph of Page 5. However, these details are not written down or included in the optimization algorithm's constraints. In addition, there are no constraints related to the EV in the objective function.
6. I think the optimization algorithm in Section 5 is overexplained. It is written on three pages in the manuscript. I meant to say that the BWO was already proposed and explained in reference [27].Why do you need to repeat the information in the reference? It is not part of the contribution. Did you develop anything new in the BWO?
I recommend explaining a paragraph for each phase or step. Then, Figure 4 explains a lot about this algorithm.
7. The location of Table 2 comes before Table 1, please fix this.
8. The explanation about Table 2 isn't clear, can you please explain more, what the numbers in BWO and PSO mean? I know the final results indicate that BWO is better than PSO. But please, explain why and how?
9. Please, explain Table 3 in more clear way. What's the meaning of these numbers in either ISE or IAE? Are those good or bad and why?
10. What the drawbacks, challanges, and the limitation of this work?
Thank you
Author Response
The authors would like to express their gratitude to the reviewer for his thorough evaluation as well as his perceptive remarks, both of which contributed to an overall enhancement of the work. The point-wise responses are given below in an attachment. Please see the attachment
Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
The authors provided answers to all my questions. In the new version of the paper, my recommendations were taken into account. In my opinion, the article in this version can be accepted.
