EV-Station-Grid Coordination Optimization Strategy Considering Psychological Preferences
Round 1
Reviewer 1 Report
Thanks for producing an interesting work. Please 1) improve the figure qualities; 2)psychological preferences need to be presented clearly; 3) what is collaborative optimization? 4) why this method is used? 5) Fig 12 does not read well, what is profit? is it measered in USD?
Author Response
Response to Reviewer 1 Comments
Point 1: Improve the figure qualities.
Response 1: I'm sorry for the problem with the figures. The incomplete display of figuers has been resolved, and units have been inserted into the descriptions of the axes of the graphs. (in red)
Point 2: Psychological preferences need to be presented clearly.
Response 2: The detailed description of psychological preferences has been added to lines 96-112. (in red)
In addition, the charging decision-making group has a large scale and a wide distribution of members. The decision-making attributes present complexity and randomness, manifested in the existence of multiple dimensions of evaluation attributes in decision-making issues, and the importance of these attributes is different. That is, users tend to pay more attention to the changes of some attributes when making decisions, while being relatively insensitive to other attributes, presenting unique psychological preferences. Literature [19] uses the quantitative product between the preference vectors between two decision members to illustrate the relationship between the corresponding two de-cision members, and uses similarity relationships to divide decision members into the same aggregation. Literature [20] synthesizes each attribute weight vector and a large group preference matrix, and determines the ranking of decision-making options based on the comprehensive evaluation vector of each option. Literature [21] proposes a large group decision-making method oriented to utility value preference information. However, the above multiple attribute decision making problems do not take into ac-count the irrational psychology of decision makers in the process of preference mining. By analyzing the advantages and disadvantages of the above methods, this paper proposes an irrational group decision-making method that considers complex prefer-ences, and the established model is more consistent with the actual decision-making process.
Point 3: What is collaborative optimization?
Response 3: The specific collaborative optimization method has been shown in the lines 115-120.(in red)
Describing irrational psychology through prospect theory [19], mining user preferences through clustering, and establishing a multi-objective optimization model to regulate the spatial and temporal distribution of charging loads, achieving the goal of peak shaving and valley filling, and reducing grid fluctuations. Users can also effectively reduce charging costs by responding to the optimization objectives, while charging station operators can ensure profitability by regulating prices.
Point 4: Why this method is used?
Response 4: The significance of the method proposed in this paper has been given in lines 121-125.(in red)
The method proposed in this article breaks the assumption of rational decision-making principles and broadens the application scope of behavioral economics, improve the accuracy of decision model results from the very beginning, and collaborative optimization strategy provides theoretical support for formulating scientific charging guidance schemes.
Point 5: Fig 12 does not read well, what is profit? is it measered in USD?
Response 5: The explanation for profit has been given in lines 743-744.(in red)
which represents the electricity sales profits of all charging stations during the 96 periods.
It is measured in USD according to the parameters shown in Table 1.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The article clearly presents the purpose of the considerations, as well as the contribution to the state of the art. After presenting the solution of the considered problem, the results of appropriate calculations are given, followed by a discussion of the obtained results and conclusions.
Comments
* In fact, the article deals with multi-criteria optimization. This aspect of consideration is not sufficiently taken into account.
* Authors should review the entire article, paying attention to the correctness of the used wording, e.g.:
- l. 145: the maximum capacity of road (the capacity of road),
- l. 453: the phase angle difference of the branch ij (the nodal-voltage phase angle difference for the branch ij),
- l. 492: power consumption (energy consumption),
- l. 580: the comprehensive charging cost has been greatly optimized (the comprehensive charging cost has been optimized),
etc.
* Formulas (4) and (25) should be corrected.
* It is necessary to describe the quantities in the formulas more precisely.
* The repeated text fragments should be removed.
* The units of the quantities taken into account should be inserted into the descriptions of the axes of the graphs.
* One designation should only be used in one sense.
* Each acronym should be explained the first time it is used.
* English should be improved.
Author Response
Response to Reviewer 2 Comments
Point 1: In fact, the article deals with multi-criteria optimization. This aspect of consideration is not sufficiently taken into account.
Response 1: The specific collaborative optimization method has been shown in the lines 104-109.(in red)
Describing irrational psychology through prospect theory [19], mining user preferences through clustering, and establishing a multi-objective optimization model to regulate the spatial and temporal distribution of charging loads, achieving the goal of peak shaving and valley filling, and reducing grid fluctuations. Users can also effectively reduce charging costs by responding to the optimization objectives, while charging station operators can ensure profitability by regulating prices.
Point 2: Authors should review the entire article, paying attention to the correctness of the used wording, e.g.:
- l. 145: the maximum capacity of road (the capacity of road),
- l. 453: the phase angle difference of the branch ij (the nodal-voltage phase angle difference for the branch ij),
- l. 492: power consumption (energy consumption),
- l. 580: the comprehensive charging cost has been greatly optimized (the comprehensive charging cost has been optimized),
etc.
Response 2: I’m sorry for the careless writing. The above content has been modified, and other content has been reviewed and modified accordingly.(in red)
Point 3: Formulas (4) and (25) should be corrected.
Response 3: Formulas (4) and (25) have been corrected. (in red)
Point 4: It is necessary to describe the quantities in the formulas more precisely.
Response 4: The descriptions of the quantities in the formulas have been checked and modified, respectively in lines 442 and 477. (in red)
Point 5: The repeated text fragments should be removed.
Response 5: The repeated text fragments have been deleted in lines 203 and 179.(in red)
Point 6: The units of the quantities taken into account should be inserted into the descriptions of the axes of the graphs.
Response 6: The units of the quantities have been inserted into the descriptions of the axes of the graphs.(in red)
Point 7: One designation should only be used in one sense.
Response 7: The repeated designations have been changed in formula 1 and 3.(in red)
Point 8: Each acronym should be explained the first time it is used.
Response 8: Ecronyms have been explained in lines 7 and 46.(in red)
Point 9: English should be improved.
Response 9: Some spelling errors and incorrect sentences have been corrected.(in red)
Author Response File: Author Response.pdf
Reviewer 3 Report
The work is interesting, particularly unique in the user behavioral modeling such as the herding effect in the estimation of spatial-temporal charge demand load predictions, and using it as an input to the price based optimization strategy, so the work is making a valid contribution there.
However, the diversity of the data inputs and the correlation analysis of the model input features to the resulting output should be further scrutinized to understand how each input feature impacts the charge demand outcome and weighted accordingly.
Author Response
Response to Reviewer 3 Comments
Point 1: The diversity of the data inputs and the correlation analysis of the model input features to the resulting output should be further scrutinized to understand how each input feature impacts the charge demand outcome and weighted accordingly.
Response 1: Thanks a lot for your suggestion. According to relevant researches in the literatures, multiple factors have been selected for sensitivity analysis to obtain correlation to charging decisions. The specific content has been given in lines 303-319. (in red)
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Not all previous comments have been taken into account. The following comments can still be made:
* In fact, the article deals with multi-criteria optimization. This aspect of consideration is not sufficiently taken into account (it is desirable to show how multi-criteria optimization is carried out, as well as to present a discussion on the effects of the applied procedure).
* Formulas (4) and (25) should be corrected.
* It is necessary to describe the quantities in the formulas more precisely.
* The repeated text fragments should be removed (e.g. titles of organizational units of the article).
* The correct units of the quantities taken into account should be inserted into the descriptions of the axes of the graphs.
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Round 3
Reviewer 2 Report
The following comments can still be made:
* Formulas (4) and (26) should be corrected.
* The units of the quantities taken into account should be inserted into the descriptions of the axes of the graphs.
t as a time unit designation in some figures is not a valid time unit designation. A different description of the relevant graph axes should be considered.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 4
Reviewer 2 Report
The following comments can still be made:
* Formula (1) should be verified. ϵ has two different meanings. Set definitions need to be verified.
* Formula (26) should be corrected. Authors can derive that formula from the matrix node-voltage equation.
* The description of the ordinate axes in Fig. 10 should be modified. What is the unit of "Fluctuation of voltage"?
* The description of the ordinate axes in Fig. 11 should be modified. The word "utility" is not understandable in the context of the description of the ordinate axes.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
