Research on Optimal Configuration of Landscape Storage in Public Buildings Based on Improved NSGA-II
Round 1
Reviewer 1 Report
Research on optimal Configuration of Landscape storage in Public Buildings based on improved NSGA-II
This paper studies the optimal allocation method of renewable energy in public buildings, and gives the capacity allocation and optimization model of complementary power generation system under multi-objective.
Article is interesting. Few observations are given below;
The abstract is not clear. Objectives and aims are missing in the abstract.
Abstract need revision with some quantitative results.
Some more latest studies are required in the introduction section to further highlight the importance of this study.
Navaratnam, S., Ngo, T., Gunawardena, T., & Henderson, D. (2019). Performance review of prefabricated building systems and future research in Australia. Buildings, 9(2), 38.
González, J., Soares, C. A. P., Najjar, M., & Haddad, A. N. (2021). BIM and BEM Methodologies Integration in Energy-Efficient Buildings Using Experimental Design. Buildings, 11(10), 491.
Equations must be quoted with proper references.
List of abbreviations and symbols are missing.
Authors must summarized results in more systematic way with reference to the previous studies.
Line 678. This is also a problem that NSGA-II is difficult to deal with 678 under strong constraints. The authors must propose proper solutions.
Also, Conclusions are too limited to proof the significant outcome of this study.
Author Response
Response to Reviewer 1 Comments
Point 1: The abstract is not clear. Objectives and aims are missing in the abstract.
Response 1: We appreciate it very much for this good suggestion, and we have done it according to your ideas.We have modified the abstract and you can see it on lines 8 to 21.
Point 2: Abstract need revision with some quantitative results.
Response 2: We appreciate it very much for this good suggestion, and we have done it according to your ideas. We supplement some of the quantitative results of the abstract in lines 17 to 19 of the manuscript.
Point 3: Some more latest studies are required in the introduction section to further highlight the importance of this study.
Navaratnam, S., Ngo, T., Gunawardena, T., & Henderson, D. (2019). Performance review of prefabricated building systems and future research in Australia. Buildings, 9(2), 38.
González, J., Soares, C. A. P., Najjar, M., & Haddad, A. N. (2021). BIM and BEM Methodologies Integration in Energy-Efficient Buildings Using Experimental Design. Buildings, 11(10), 491.
Response 3: We appreciate it very much for this good suggestion, and we have done it according to your ideas. Thank you for providing us with our latest research paper. We have studied the two references you provided and quoted them into our manuscript.You can see it on lines 41 to 50 of the manuscript.
Point 4: Equations must be quoted with proper references.
Response 4: I am sorry that this part was not clear in the original manuscript. I should explain that we actually referenced the formula at the beginning of a large paragraph, not every formula in the paragraph.
Point 5: List of abbreviations and symbols are missing.
Response 5: Thank you for your valuable comments. We have listed the main symbols and abbreviations used in the manuscript in table, which is placed separately in Section 0 Nomenclature for your review.
Point 6: Authors must summarized results in more systematic way with reference to the previous studies.
Response 6: We appreciate it very much for this good suggestion, and we have done it according to your ideas. We have made some additions to the results and explained the experimental results in more detail. You can review these additions on lines 648 through 776.
Point 7: Line 678. This is also a problem that NSGA-II is difficult to deal with 678 under strong constraints. The authors must propose proper solutions.
Response 7: We thank you very much for your careful review of our manuscript and thank you again for your responsible review. We have made modifications in accordance with your advice. We analyze the relationship between unreasonable working conditions and unsatisfied constraints on energy storage systems. We explain that the essence of the spatial transformation method proposed in this manuscript is a mathematical transformation of variables. The energy storage variables that do not satisfy the conditions are properly transformed so that the transformed variables satisfy the constraints, and the transformed variables are considered as feasible schemes. We have placed this explanation on lines 748 to 757 of the manuscript for your review.
Point 8: Also, Conclusions are too limited to proof the significant outcome of this study.
Response 8: We really appreciate your valuable comments. We accept your suggestion to rewrite the conclusion. You may review our changes on lines 795 to 808 of the manuscript.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The capacity allocation and optimization model of a complementary power generation system under multiple objectives is provided in this research, which also analyses the best strategy for allocating renewable energy in public buildings. The following are my comments.
Why didn't the authors utilize NSGA I or III or NSGA II? Justify, please.
What led you to choose NSGA II? In the literature, there are more algorithms available. Justify the decision's selection.
Please check Fig. 1, Fig.1 is NOT clear
The lack of a literature review is another significant finding. I would be able to see any research done on this subject. Identified research gaps and contributions of the proposed study should be elaborated.
However, the authors asserted that NSGA II is more stable, and the experimental section appears to be fine. Compare the proposed work with NSGA III or Just justify your choice of NSGA II. The author should consider more metrics to evaluate the performance of the proposed work
The authors are strongly encouraged to submit the source code in a repository, ideally in Mendeley, IEEE Data Port, or GitHub, to validate the results reported.
Equations are not well edited
Verify your work for grammatical and typographical errors.
All the notations and abbreviations should be checked carefully
Authors claimed, “It can be observed from the figure that in the case solved by STNSGA-II, the battery 684 satisfies the constraint conditions within an optimization period, which reflects that 685 STNSGA-II can indeed solve the problem of strong constraint…” Please more discussion/analysis needs
Update the mechanisms you presented's future scope.
Author Response
Response to Reviewer 2 Comments
Point 1: Why didn't the authors utilize NSGA I or III or NSGA II? Justify, please.
Response 1: We appreciate it very much for this good suggestion, and we have done it according to your ideas. We choose NSGA-II as the solution algorithm for this paper. ​Considering the lack of an elite policy rate for NSGA and the manual setting of the shared parameters, the performance of the algorithm is reduced. The NSGA-II builds on the NSGA to remedy these two shortcomings. At the same time, NSGA-III is not selected because the biggest difference between NSGA-III and NSGA-II is the difference in the selection mechanism, and NSGA-III is more widely used in many objective optimizations.Our manuscript involves only three objectives, which can be trivially satisfied by using NSGA-II. You can review the manuscript on line 431 to 459.
Point 2: What led you to choose NSGA II? In the literature, there are more algorithms available. Justify the decision's selection.
Response 2: We appreciate it very much for this good suggestion, and we have done it according to your ideas. The reason why we choose NSGA-II instead of the method in the reference is that some methods in the reference naturalize the multi-objective into a main objective when solving the multi-objective optimization, but the status of multiple objectives is the same. This method relies too much on the personal will of decision-makers and is not universal. Therefore, NSGA-II algorithm is chosen to solve the multi-objective optimization problem. You can look it up on lines 424 to 430 of the manuscript.
Point 3: Please check Fig. 1, Fig.1 is NOT clear
Response 3: We appreciate it very much for this good suggestion, and we have done it according to your ideas. We have made the front in the figure lager to ensure that you can read it clearly and you can see our changes in line 137.
Point 4: The lack of a literature review is another significant finding. I would be able to see any research done on this subject. Identified research gaps and contributions of the proposed study should be elaborated.
Response 4: We appreciate it very much for this good suggestion, and we have done it according to your ideas. We add some of the most recent literature and point out the identified research gaps and contributions of the proposed research, which can be found on lines 111 to 117 of the manuscript.
Point 5: However, the authors asserted that NSGA II is more stable, and the experimental section appears to be fine. Compare the proposed work with NSGA III or Just justify your choice of NSGA II. The author should consider more metrics to evaluate the performance of the proposed work
Response 5: Thank you for your responsible review of our manuscript. I need to explain your confusion about the experimental section. Essentially, our proposed constraint treatment of spatial transformations is a mathematical transformation of variables. This approach, which can transform variables that do not satisfy the constraints into variables that do by setting appropriate mathematical logic transformations, is more suitable for dealing with the constraints of the energy storage system itself. Mutual constraints between variables of different devices can also be used, but it is relatively cumbersome to establish the appropriate variable transformation formulas. In our manuscript, this way of variable transformation is nested in NSGA-II , which is characterized by a good satisfaction of constraint conditions.
Point 6: The authors are strongly encouraged to submit the source code in a repository, ideally in Mendeley, IEEE Data Port, or GitHub, to validate the results reported.
Response 6: We thank you for taking the time to review our manuscript and appreciate your valuable comments. However, we have to apologize to you. Since the data of our code involves meteorological data, if you are interested in the code, could you please wait until the article is received before making the code public？ Your understanding is greatly appreciated.
Point 7: Equations are not well edited
Response 7: We are sorry for the trouble caused to you when reviewing the manuscript due to the unreasonable proportion allocation of the upper and lower indexes of our equations. Now we have re-edited the equation in the manuscript, and I believe you will be more comfortable in the following review process.
Point 8: Verify your work for grammatical and typographical errors.
Response 8: We really appreciate your comments. We have checked the grammar and typography of the manuscript according to your comments.
Point 9: All the notations and abbreviations should be checked carefully
Response 9: Thank you very much for your careful review of our manuscript. Indeed, as you said, there are some mistakes in the spelling of notations and abbreviations. We carefully checked all the notations and abbreviations and compiled a list to place at the beginning of the text.
Point 10: Authors claimed, “It can be observed from the figure that in the case solved by STNSGA-II, the battery 684 satisfies the constraint conditions within an optimization period, which reflects that 685 STNSGA-II can indeed solve the problem of strong constraint…” Please more discussion/analysis needs
Response 10: We appreciate it very much for this good suggestion, and we have done it according to your ideas. We analyze the cost of public building microgrid systems and the impact of grid connectivity from the comparison of energy storage systems that satisfy the constraints and those that do not. We conclude that constrained energy storage scheduling is beneficial for public building microgrid systems, and that our modified algorithm to ensure that energy storage satisfies self-constraints is indeed effective. You can review our changes on lines 762 to 776 of the manuscript.
Point 11: Update the mechanisms you presented's future scope.
Response 11: We appreciate it very much for this good suggestion, and we have done it according to your ideas. We have added a section on future research in lines 777 to 793 of the manuscript for your review.
Author Response File: Author Response.docx
Reviewer 3 Report
Please, place the Figures. 5, 6, 7 and 10 in color and whitout noise...
For 6.2.1. The Simulation Results put more results on tables and explain it.
For Reference 17, place a more current one.
Author Response
Response to Reviewer 3 Comments
Point 1: Please, place the Figures. 5, 6, 7 and 10 in color and whitout noise
Response: We appreciate it very much for this good suggestion, and we have done it according to your ideas. We have re-colored Figure. 5,6,7 and 10, and at the same time reply to your question about noise. Figure. 5,6,7 and 10 are the data we have given. Due to the large amount of data, they appear crowded in the image.
Point 2: For 6.2.1. The Simulation Results put more results on tables and explain it.
Response:We appreciate it very much for this good suggestion, and we have done it according to your ideas. We have added several sets of data to Table 5, and we have also reinterpreted the table. These changes are on lines 648 to 692.
Point 3: For Reference 17, place a more current one.
Response: We appreciate it very much for this good suggestion, and we have done it according to your ideas.We have replaced reference 17 with a new one.
Author Response File: Author Response.docx
Round 2
Reviewer 2 Report
All comments are addressed.
