A Cloud-Edge Computing Method for Integrated Electricity-Gas System Dispatch

Round 1

Reviewer 1 Report

The work presents a method based on cloud-edge computing that aims to optimize the communication for dispatching between power system and natural gas system. One of the benefits of the method is that of protecting data privacy and reducing network transmission pressure. The method was compared with 3 other methods, resulting in a high quality.

Regarding the importance of the applied method, the authors make a clarification in the conclusions chapter "Cloud-edge computing method has a long training time and the data set requires long time intervals, which makes it difficult to satisfy the demand of real-time dispatching" leads to the idea that the method can only be applied locally, in systems with few nodes.

 

The paper is well organized, having an introduction part, a mathematical modeling part, and finally a part of results followed by conclusions. In the introduction, an analysis of the literature review is carried out. In the Chapter 2 the modeling part of the systems is presented (Power System Model, Natural Gas System Model, Electric-Gas Coupling Unit Model, IEGS Model Operating Cost). In chapter 3 the authors present the cloud-edge computing architecture and in chapter 4 the cloud-edge computing method. Finally, the results obtained by simulation for a combination between an IEEE 9-node power system and an 8-node natural gas system are presented.

 

Regarding the content, the following inadequacies were identified:

1. on pg.3 lines 119-123 it is specified "A case study is provided in Section V to illustrate the effectiveness of the proposed approach. The paper makes a conclusion in Section VI", and in reality the case study was noted with 4.6 and conclusions with 5.

2. on pg. 14, line 415, reference is made to Table 2, but I think it should have been Table 4.

3. in Fig.8, the measure units for power and gas must be added (similar to Fig.7).

Author Response

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Reviewer 2 Report

Integrated electric-gas systems represent a hybrid energy infrastructure combining electricity and natural gas to meet energy demands. These systems are designed to take advantage of the benefits and capabilities of both electricity and natural gas while addressing their respective limitations. The authors present a cloud-edge approach based on a multi-agent deep deterministic policy gradient algorithm to solve the combined optimal dispatch of gas and electricity.  The paper is well-written and presents interesting results; nonetheless, some changes must be made to further improve it.

1.      The literature review in the introduction is sufficient; nonetheless, the authors may complement it with a table classifying previous research work.

2.      The fonts of figure 1 are too small. Please use the same type of font in figures and text.

3.      What are “climbing” constraints reported in line 135? Maybe the authors mean “ramping” constraints. Please explain.

4.      The models presented in section 2 need references.

5.      The test system serves didactic purposes, but it is too small. Please include a bigger test system to verify the applicability of the proposed approach.

6.      What are the main strengths and drawbacks of the proposed approach? Please elaborate.

7.      A list of acronyms and symbols is needed at the end of the document.

English is OK

Author Response

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Reviewer 3 Report

To reduce data transmission pressure and satisfy data protection requirements between power system and natural gas system, this paper uses cloud-edge computing. The aim is to solve the optimal dispatch problem. To this end, authors design a cloud-edge computing architecture and construct a cloud-edge computing algorithm based on the multi-agent deep deterministic policy gradient algorithm.

The paper is generally well organized. There are, however, a number of flaws that have been identified. A number of critical concerns need to be addressed before the paper can be evaluated in its final form

 

1-      The paper needs to be carefully proofread.

2-      Literature appears to be well written, however, authors do not provide any comments regarding the pros and cons, weaknesses and limitations, advantages and contributions of the cited works. In the revised version of this work, please address this concern carefully.

3-      “Therefore, in order to better realize the privacy protection of different systems, …” . This statement needs to be developed further. It is unclear what the idea behind this is.

4-      The papers contain many acronyms, which makes following up difficult. All of them should be gathered at a table.

5-      It is necessary to provide a more detailed explanation of the IEGS model. All links should be supported by references.

6-      There is no reference to any relevant work in the analytical mathematical description equations 1 to 6. Please clarify.

7-      Same concerns for the natural gas system model and electric-gas coupling unit etc….

8-       Any novelty in the described Cloud-Edge Computing architecture?

9-      How are optimization criteria determined? How are authors claiming to solve the global optimization problem?

10-   For the sake of emphasizing all aspects of the design process, a flowchart description is necessary.

11-   Does the system parameter value correspond to a real system parameter value?

12- In the case study, I am unable to see how the optimality problem is addressed and solved.

The paper needs to be carefully proofread.

Author Response

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Reviewer 4 Report

 

The authors tackle a modern topic, which is the integrated electricity-gas system dispatch. However, certain issues need to be addressed:

 1.       The authors are encouraged to add part of the numeric results in the abstract and the conclusions.

2.       In the Introduction, the authors could further analyze the relevant literature in order to include more related work and also comment on the ability of their algorithm to adapt to uncertainties and emergencies. Therefore, the authors are encouraged to expand the literature analysis with recent related research, e.g. such as indicatively:

·         https://doi.org/10.3390/s22239457

·         http://dx.doi.org/10.1049/gtd2.12895

3.       The authors should provide references for all formulas and parameters used in the manuscript, e.g. the parameters of Table 2.

4.       What are the limitations of the proposed algorithm?

5.       The authors should analyze the computing requirements of the proposed algorithm. 

Taking the aforementioned comments into account, a minor revision of the manuscript is recommended.

 

 

Author Response

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Round 2

Reviewer 2 Report

The authors answered all my comments. 

English is OK

Reviewer 3 Report

My comments have been well addressed.