Integrating Environmental and Economic Considerations in Charging Station Planning: An Improved Quantum Genetic Algorithm
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper proposes a mathematical model for locating and sizing electric vehicle (EV) charging stations (CS) to minimize the social costs. While the proposed model presents interesting aspects and could be considered for publication, I have the following comments and questions:
1. Upon first occurrence, clarify "charging station" as "charging station (CS)" and maintain the abbreviation CS throughout the paper.
2. Add a space between "algorithm" and "function" in Table 3. The authors are suggested to read through the paper and get the all the possible typos/mistakes corrected.
3. Please provide an explanation of how c_g is derived in equation (6).
4. Please clarify the method used to calculate the arrival rate of EVs at charging station CS_j (λ_j) in the case study.
5. Please clarify the chromosome coding scheme in the algorithm and provide information on the meaning of each bit in the chromosome.
6. Please provide a clear explanation of how the fitness value is calculated in the Improved Quantum Genetic Algorithm (IQGA).
7. Include the parameter settings used for the IQGA in the case study.
8. Please explain the methodology used to identify the charging demand in the grids using GPS trajectory data.
Please consider these comments and make revisions to improve the clarity and language quality of the paper.
Comments on the Quality of English LanguageMedium level of English
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe paper gives interesting insights for decision making in the adoption of EVs by optimizing the location and sizing of CSs
The approach is consistent and based on previous literature.
Some minor modifications are suggested as follows:
Mistyping / mistakes:
- page 9, Table 3, WOA alg.: in Running Time "5.113" instead of "5.113s"
Further comments:
- page 8, Figure (e): should the Best fitness of F5 converge to the minimum of -959.64 (too many decimal digits in the text in Table 2) instead of about -895?
- page 12, Table 5: for the column of "Optimization solution" it is not clear the use of "," between the couple of numbers regarding "CSs" and "number of chargers": maybe better to use "/" as a text character to separate them
- page 12, Figure 7: please comment in the text the trend of the curve of "carbon emission (million T)" with the data in f4 function in Table 5, where the drop toward less CO2 cost is not so effective like the CO2 emissions with respect to the number of CSs increase
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThis is an excellent article. While there have been many studies undertaken on the problem of how to optimise the locations and numbers of EV charging stations in city or urban areas, this modelling approach is very comprehensive.
The English is very good, the referencing is excellent, the figures are clear. All in all, it is a very interesting and good piece of work
However, I do have a few issues or questions (see attached Word document) and if these are adequately addressed I would have no problems with the paper. I think that it involves just a small bit of cleaning up rather than major changes.
Comments for author File: Comments.pdf
Author Response
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Author Response File: Author Response.pdf
Reviewer 4 Report
Comments and Suggestions for AuthorsThe authors developed a quantum algorithm to be utilized in defining the optimum size and location of electrical vehicles charging stations. The study is well presented and the results are interesting. Some comments can be seen below:
1- Please provide the main findings of the study in the abstract.
2- Headings are better numbered starting from 1 not from 0.
3- Is it Figure or Fig. ?
3- Paragraphs from line 95 to 119 are better merged together and rewritten to clearly clarify your contribution based on the literature.
4- You should provide the references where you got the equations of the model.
5- Does the coefficient that converts the construction cost into the annual operating cost have a constant value?
6- line 241 ‘’ The performance comparison results presented in Table 3 demonstrate that IQGA outperforms the other five algorithms in terms of accuracy for functions F 1to F 5’’. Please elaborate and justify.
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for Authors1.In your research, you have proposed an important and forward-looking model to minimize total social costs, taking into account the construction and operation costs of charging stations, charging time costs for electric vehicle users, and related carbon emission costs. This study has important guiding significance for China to achieve its carbon peak and carbon neutrality goals. To further enrich your work, I suggest that you consider citing the following literature on fuel cell energy management to explore energy management strategies and technologies in the charging process of electric vehicles.
Jia C, He H, Zhou J, Li J, Wei Z, Li K. A novel health-aware deep reinforcement learning energy management for fuel cell bus incorporating offline high-quality experience. Energy. 2023;282:128928.
2.Provide a more detailed explanation of the adjustments made to the Quantum Genetic Algorithm (QGA) in the proposed Improved Quantum Genetic Algorithm (IQGA) to enhance search ability and retain high-quality individuals within the population.
3.Include a discussion on the potential limitations and challenges of the IQGA approach, such as its scalability and applicability to different problem domains.
4.Provide a more comprehensive analysis of the trade-offs between cost-effectiveness and environmental sustainability in the context of CS network expansion and charging power selection.
5.Provide a more detailed explanation of the specific adjustment methods proposed to address the fixed value limitation of the quantum rotation angle in the QGA.
6.Discuss the potential implications of the research findings for policy-makers and stakeholders involved in the planning and development of charging infrastructure.
7.Consider including a section on future research directions, highlighting potential areas for further improvement and expansion of the proposed model and algorithm.
Author Response
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Author Response File: Author Response.pdf
