Two-Layer Robust Optimization Scheduling Strategy for Active Distribution Network Considering Electricity-Carbon Coupling

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper focuses on the low-carbon optimal scheduling problem of active distribution network (ADN). Based on the power-carbon coupling scenario, an ADN low-carbon optimal scheduling strategy considering demand response (DR) priority is proposed. A two-layer distributed robust scheduling model based on carbon potential and load bidirectional feedback mechanism is constructed, which is solved by column and constraint generation (C & CG) algorithm. The case simulation verifies that the model can effectively cope with the demand response behavior in different scenarios, improve the photovoltaic consumption capacity, balance the economic efficiency and robustness of ADN, and promote its evolution to low-carbon and efficient operation mode.

1. The quality of Fig.1 is low.
2. It is assumed that the node carbon potential only depends on the injected carbon flow, and the carbon density loop dependence caused by the radiation characteristics of the distribution network is not considered. It is suggested to increase the carbon flow propagation constraint of the radiation network. Besides, the following related research can be compared: a: Two-stage robust operation of electricity-gas-heat integrated multi-energy microgrids considering heterogeneous uncertainties b: Extension of pole differential current based relaying for bipolar LCC HVDC lines
3. The priority function is not standardized. If F / G is less than 1 and λ is greater than 1, the Z value will be inflated, and the relevant parameters should be normalized.
4. The heat map can be used to show the change curve of industrial load priority under different weight combinations, and to verify the correctness of the given weight.
5. The format of the picture and its number is not uniform.
6. The influence of extreme weather can be considered in the confidence formula.
7. It supposed to increase the test data of some actual scenarios

 

Comments on the Quality of English Language

good

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This paper proposes a two-layer distributed robust scheduling model for active distribution networks that considers demand response priorities to enhance photovoltaic consumption, balance economic efficiency with operational robustness, and promote a secure and reliable transition to a low-carbon power system. Overall, the comparisons are sufficient and interesting. However, there are several points where clarifications, justifications, and expansions would improve the manuscript.

 

1. The abstract should be revised to incorporate key quantitative findings from the research, thereby more effectively highlighting the study's primary contributions and results.
2. A comprehensive discussion of existing research gaps is necessary. This involves clearly articulating the specific limitations or unexplored areas within the current body of knowledge that this research aims to address.
3. The uncertainty set in Eq. (23) of this paper is similar to the uncertainty set in “fortifying renewable-dominant hybrid microgrids: a bi-directional converter based interconnection planning approach”, and “A two-stage robust optimization for centralized-optimal dispatch of photovoltaic inverters in active distribution networks”. Citing and discussing these works would enhance the paper’s overall quality and contextual grounding.
4. To improve the clarity and readability of the manuscript, please consider increasing the font size for the text and labels within Figure 2.
5. The case study analysis would be significantly strengthened by including the algorithm's convergence curves and a discussion of the computational solution times. This would provide valuable insight into the model's efficiency and practical performance.
6. The conclusion should discuss potential directions for future research and extensions of this work.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Below are my comments on the paper:

1. Key results are mentioned without values or comparative performance (e.g., % cost reduction, emission cut). Authors have to put more specific results in the Abstract.
2. Some equations (7 and 11) are not well-explained. Why were those formulations chosen? How are weights determined?
3. It is recommended to provide a discussion on sensitivity analysis
4. Scenario comparison is internal (S1–S4), but how does it perform against methods in ref [6] or ref[12]?
5. In conclusion, provide sentences about limitations and future work.
6. The paper contains many grammatical errors

Comments on the Quality of English Language

1. The paper contains many grammatical errors

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Thanks for the revision, and it is suggested to accept for publication.