A K-Additive Fuzzy Logic Approach for Optimizing FCS Sizing and Enhanced User Satisfaction

Reviewer 1-Comments

Authors’ Response

Page 1, Keywords: My suggestion is to include “EVs user waiting time” in the keywords. Alternatively, you may change “charging station utilization” to “charging station user waiting time”. 

Thank you for your comment. We have changed the keywords as requested. The change is highlighted on page 1

Section 2.  Literature Review: My suggestion is to insert a Table presenting global data concerning the market penetration of EVs in various countries, the associated number of charging stations, the cost to buy an EV, the cost to build and operate a charging station etc.

Thank you for your comment. We have inserted a detailed figure illustrating the statistics of EV in global market across the globe. It is highlighted in yellow on page 4.

Section 5. Conclusions: My suggestion is to include the policy recommendations arising from your valuable findings and then address each one to the respective stakeholders (i.e., who will benefit and how).

Thank you for your comment. The Conclusion is updated according to the requested comment. It is highlighted in yellow on page 12 and 13.

Section 5. Conclusions: It would be interesting to include some monetary cost estimates concerning the implementation of your solution.

Thank you for your comment.

We appreciate your interest in including monetary cost estimates in our solution. Implementing our optimal sizing solution for Fast Charging Stations (FCS) would involve several cost factors, including the initial setup costs for installing FCS infrastructure, ongoing maintenance expenses, and potential revenue losses due to fewer FCS deployments. To provide accurate cost estimates, we would need to conduct a detailed cost analysis that considers factors such as the number and type of FCS units, installation and operating costs, electricity costs, and revenue projections based on user demand and pricing models. While we haven't included specific cost estimates in our current study, we acknowledge the importance of this aspect and recommend conducting a thorough cost-benefit analysis as a follow-up to our research. This analysis would provide a comprehensive understanding of the financial implications of implementing our solution and help stakeholders make informed decisions regarding FCS deployment.

Please note that reference [35] is missing from the main body of the manuscript.

Thank you for your comment. We have deleted this uncited reference.

Page 12, Reference [11], “M. Fattahi Bandpey and . K. Gorgani Firouzjah”: Please delete the dot between “and” and “K. Gorgani Firouzjah”. I kindly ask you to check all the references for similar inconsistencies.

Thank you for your comment. We have updated the reference and it is highlighted in yellow on page 14.

Reviewer 2-Comments

Authors’ Response

The article called "A K-Additive Fuzzy Logic Approach for Optimizing FCS Sizing and Enhanced User Satisfaction" is interesting.

The introductory part is well written, as if it had already gone through a revision phase.

My observations begin from paragraph 3.

equation 1: put dt in place of d(t) being an integral

Thank you for your comment. Equation 1 is updated accordingly.

equation 2, I don't like it, since SoC-1, if it were 0% it would be infinite... it's an extreme case but the formulation is improper and then a time = SoC-1 for a time, it doesn't sound good...

Thank you for your comment. We have added a small number 0.001 to SoC to prevent the division by zero. This is added and highlighted by yellow on page 5

I would put punctuation after the equations

Thank you for your comment. Punctuation is added to each equation and is highlighted in yellow

each parameter present in equations 3 and 4 on line 232 must be defined, there is a point to remove

Thank you for your comment. Each parameter is defined for equation 3 and 4.

Table 2: to help the algorithm, I wonder whether it is convenient to express the quantities in per unit

Thank you for your comment. We have included the pu and highlighted in yellow on page 8.

I would like to ask you to expand the simulations and discussions part, there is a lot of material to comment on starting from the simulated network to the results which are interesting.

Thank you for your comment. We have included discussion in simulation part on page 11 and highlighted in yellow.

The conclusions could also better reflect the excellent work done

Thank you for your comment. The conclusion is updated and is highlighted in yellow on page 13

I request minor revisions although an improvement of paragraph 4 would be very welcome.

Thank you for your comment. Paragraph 4 on page 6 is updated and highlighted in yellow.

Reviewer 3-Comments

Authors’ Response

The paper presents a K-additive fuzzy logic algorithm to predict the average waiting time and the optimal number of charging stations, using both type 1 and type 2 fuzzy membership functions. The solution validation is done through simulation.

Comments and recommendations for the manuscript improvement:

-The methodology research must be more detailed presented, highlighting the design and implementation stages of the proposed solution (the k-additive fuzzy logic algorithm).

Thank you for your comment. The block diagram of K-additive FLC is presented on page 7 and highlighted in yellow as image and text describing the K-Additive.

What is the main contribution / the novelty of the paper?  Modeling the charging stations or the K-additive fuzzy logic algorithm?

Thank you for the comment.  The contribution is highlighted on page 2 number 3.

- Is the proposed solution more efficient than existing ones? The content of references [31], [32] and [33] (with which comparison is made) should be detailed a bit. I do not understand why these references do not appear at all in chapter 2. Literature Review.

Thank you for your comment. References are added on page 3 in yellow highlights.

The Conclusions chapter must clearly highlight the main contribution of the paper and its novelty and can be a little extended.

Thank you for your comment.

The conclusion is updated as requested.

Please review the Conclusion chapter for typos (what means the numbers 311 and 314 in conclusions)...

Thank you for your comment. The conclusion is updated and highlighted with yellow.

Reviewer 4-Comments

Authors’ Response

(1)  The paper includes a relevant topic and is well written in general. There are some minor grammars, typing and format errors, which should be improved before publication. In addition, some figures do not meet the requirements for publication in a journal and should be improved.

Thank you for your comment.

The grammar, typing, and format errors are properly corrected in the revised manuscript and they are marked with yellow color. Furthermore, the resolution of all figures is improved in order to meet the requirements for publication.

(2)  Different EV have different charging characteristics (and charging time demands). In addition, the charging process is not linear, which influences charging time considerably. There are other impact factors, e.g., environmental conditions, human factors, traffic. In this context, modelling of charging time (page 4) includes simplifications. The effects (and dependencies) of the made simplifications onto the simulation results should be discussed with more effort.

Thank you for your comment.

The charging characteristics of electric vehicles can vary depending on the type of battery, the vehicle's charging system, and other factors. For example, some electric vehicles can take longer to charge than others due to differences in battery capacity and charging technology. The charging process is also not linear because the time it takes to charge an electric vehicle may not be consistent throughout the entire charging cycle. This can be influenced by factors such as the initial state of charge of the battery, the charging rate, and the temperature of the battery.

The K-addidtive FLC has been specifically designed to enhance user satisfaction by strategically optimizing the average waiting time and the quantity of charging stations available. Several key charging parameters, including the number of electric vehicle users, the percentage of charging station utilization, the state of charge of electric vehicles, the total number of charging stations, and the average waiting time, have been carefully evaluated within this framework and highlighted in yellow in the proposed K-additive FLC section.

(3)  Modelling of the charging station should also be discussed more extensively. In this context, the chosen model should be compared to a “real” station, and the influencing factors on simulation (and potentially deviated results) should be elaborated

Thank you for your comment. The discussion is included in page 12 and highlighted in yellow.

(4)  Finally, the differences to cited state-of-the-art ([31], [32], [33]) should be discussed not only on the output side, but also on the methodological side. This should include modelling, sensitivity of parameters, and quality of the results.

Thank you for your comment. The citations are included in Literature review highlighted in yellow. In simulation, the discussion is added and also highlighted in yellow.

(5)  The conclusion should be extended by a summary of the results and a short (critical) discussion of the potential of the methods. It should not include abbreviations, which might be unclear when reading the conclusion only.

Thank you for your comment.

The conclusion is updated and highlighted in yellow.

Reviewer 4-Comments

Authors’ Response

The context of Figure 1 in relation to the reserach is unclear. A more detailed discussion should be added, especially to bring Figure 1 into context.

- The graphical representation of Figure 1 is not sufficient. The resolution of the image seems to be too low.

- It remains unclear, how different charging behaviors are considered in the methodology, including influencing factors from vehicle side, but also infrastructure and environmental conditions. In case that simplifications have been made, these should be introduced and the effects of simplifications on the results should be discussed.

- It remains unclear, how different vehicle characteristics are considered and how they influence the result, e.g. different battery sizes. In addition, it remains unclear, how different infrastructure technology, e.g. different charging power, is considered and how they influence the results.

- The quality of Figure 4 should be improved, especially its resolution.

Thank you for your comment.

Discussion for figure 1 is added and highlighted in yellow on page 3

Figure 1 resolution is enhanced.

We have assumed that EV are homogeneous in model, type of batteries. However, the infrastructure and environmental impacts are to be considered for future work and not in this study. We added the assumption on page 12.

Figure 4 resolution is enhanced.