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Article
Peer-Review Record

Liquid Air Energy Storage Model for Scheduling Purposes in Island Power Systems

Energies 2022, 15(19), 6958; https://doi.org/10.3390/en15196958
by Mohammad Rajabdorri *, Lukas Sigrist and Enrique Lobato
Reviewer 1:
Reviewer 2:
Reviewer 3: Anonymous
Energies 2022, 15(19), 6958; https://doi.org/10.3390/en15196958
Submission received: 5 September 2022 / Revised: 19 September 2022 / Accepted: 20 September 2022 / Published: 22 September 2022
(This article belongs to the Special Issue Integrated Energy Systems: Design and Operation Optimization)

Round 1

Reviewer 1 Report

I recommend its publication with minor changes of correcting the typos and grammatical errors. 

Author Response

Dear reviewer,

Thank you so much for trusting our manuscript, and recommending the publication. In the revised version some minor issues are resolved and some modifications are made. The changes are highlighted in a document that we've provided alongside the revised manuscript.

Summary of the changes: I) the grammatical and spelling errors are dealt with in the revised version. II) a figure is added in the introduction that summarizes the reviewed literature. III) the BibTex entry for the references is updated with the latest BibTex entry of Google Scholar. IV) the equations are aligned and referred better in the new version. V) every concern that the reviewers had is tried to be addressed in the revised manuscript.

Reviewer 2 Report

This article presents the detailed mixed integer linear programming (MILP) model of liquid air energy storage, which can be used in scheduling and planning problems. Simulations of the proposed model are carried out for the power system of Tenerife Island, and compared with the basic models.

 

The topic is interesting. However, the reviewer thinks that the contribution of the paper should be highlighted. In order to enhance the quality of the manuscript, please consider including the comments below.

 

1. In the introduction part, the contributions of the paper should be rewritten clearly.

 

2. All variables appearing in the UC formulation (1)-(16) should be clearly explained in this paper. For example, what does the variable x mean?

 

3. The mixed integer linear formulation of UC problem used in this paper only considers the total balance constraint. Why the authors did not consider the network constraint of power system in this paper?

 

4. How to solve the proposed mixed integer linear programming model of liquid air energy storage has not been introduced in this manuscript. Please provide more information about this point.

 

5. More references about how to model various energy storage devices should be also added into this article. For example, Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage, is suggested to be included in literature reviews.

 

6. There are many typos in references which should be double checked and correct with the same format. Also, some of the papers have been presented with incomplete information.

 

7. The authors are invited to perform a thorough proofread of their manuscript, as I can still spot some spelling/grammar mistakes in the paper.

 

8. All abbreviations should be defined by their full name in their first appearing places.

Author Response

Dear reviewer,

Thank you for the careful review of our manuscript. You've made some useful points. We think that the manuscript is improved after this round of reviews. Hopefully, the modifications that are made, can satisfy your concerns. The response to your comments is included in the following. Alongside the revised manuscript, we have provided another document that highlights the differences from the previous draft. You can track the changes there.

Summary of the changes: I) the grammatical and spelling errors are dealt with in the revised version. II) a figure is added in the introduction that summarizes the reviewed literature. III) the BibTex entry for the references is updated with the latest BibTex entry of Google Scholar. IV) the equations are aligned and referred better in the new version. V) every concern that the reviewers had is tried to be addressed in the revised manuscript.

1. Comment: in the introduction part, the contributions of the paper should be rewritten clearly.

1. Answer: the introduction is modified in the revised version of the manuscript. To show the most important contribution of the paper clearly, this sentence is added: "The contribution of this paper is presenting a MIL formulation of LAES, that includes charging start energy (CSE) and discharging start energy (DSE)."

2. Comment: all variables appearing in the UC formulation (1)-(16) should be clearly explained in this paper. For example, what does the variable x mean?

2. Answer: in order to have a clearer presentation, instead of under the equations, we've included all the symbols in the nomenclature section. We believe that might help the readers to read the manuscript more easily. The nomenclature is categorized into indices, parameters, and variables, so the reader can find the symbols from the equations faster. If the reviewer thinks that defining symbols under the equations can enhance the reader's experience, we can also do that.

3. Comment: the mixed integer linear formulation of UC problem used in this paper only considers the total balance constraint. Why the authors did not consider the network constraint of power system in this paper?

3. Answer: In the island under study, the network constraints haven't been a concern for the operators. There are DC power flows that can be included in the formulation, but they wouldn't change the results and conclusions of the paper.

4. Comment: how to solve the proposed mixed integer linear programming model of liquid air energy storage has not been introduced in this manuscript. Please provide more information about this point.

4. Answer: The MILP model of LAES is encoded as constraints that can be directly added to the UC problem. The additional constraints that represent the LAES, will be solved alongside the other UC constraint, as an optimization problem. To make it clear, the following is added to the revised version: "The MIL formulation of LAES, that is presented in eq. (6) to eq. (19) are added to the UC optimization problem in eq. (1), to schedule the LAES optimally."

5. Comment: more references about how to model various energy storage devices should be also added into this article. For example,“Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage”, is suggested to be included in literature reviews.

5. Answer: this article is now included in the paper. A figure is also added to this revised version that summarizes the reviewed literature.

6. Comment: there are many typos in references which should be double checked and correct with the same format. Also, some of the papers have been presented with incomplete information.

6. Answer: We updated the bib file of the document, with BibTex from Google Scholar. We think that the references are corrected now.

7. Comment: the authors are invited to perform a thorough proofread of their manuscript, as I can still spot some spelling/grammar mistakes in the paper.

7. Answer: The manuscript is checked and many of the errors are modified now. The changed parts are highlighted in the document showing the differences.

8. Comment: all abbreviations should be defined by their full name in their first appearing places.

8. Answer: all of the used abbreviations are defined when they appear. They are also listed in the nomenclature section, in the acronyms category.

Reviewer 3 Report

1.     Please explain more about the objective functions after the main optimization function in Section 2.1.

2.     What if the utility or power generation company needs to use the flexible electricity cost for the charging process (compression, air in, and refrigeration)? The proposed optimization seems based on the fixed electricity cost.

3.     Why the authors used the forecasted data? If you use historical data, can you get more clear results? For instance, you can compare the results between with and without the proposed operation algorithm?

4.     What simulation tool did the authors use? What are the time windows (performance) of the operation? For example, can the proposed algorithms be executed every 1 min or 1 second?

 

5.     Please also explain more details about Liquid Air Energy Storage system. What are the benefits or disadvantages they have compared to the existing BESS system?

Author Response

Dear reviewer,

Thank you for the careful review of our manuscript. You've made some useful points. We think that the manuscript is improved after this round of reviews. Hopefully, the modifications that are made, can satisfy your concerns. The response to your comments is included in the following. Alongside the revised manuscript, we have provided another document that highlights the differences from the previous draft. You can track the changes there.

Summary of the changes: I) the grammatical and spelling errors are dealt with in the revised version. II) a figure is added in the introduction that summarizes the reviewed literature. III) the BibTex entry for the references is updated with the latest BibTex entry of Google Scholar. IV) the equations are aligned and referred better in the new version. V) every concern that the reviewers had is tried to be addressed in the revised manuscript.

1. Comment: please explain more about the objective functions after the main optimization function in Section 2.1.

1. Answer: the objective function is the sum of the start-up cost of the generators, plus the thermal generation cost. We've added the explanation in the new draft.

2. Comment: what if the utility or power generation company needs to use the flexible electricity cost for the charging process (compression, air in, and refrigeration)? The proposed optimization seems based on the fixed electricity cost.

2. Answer: the cost of the charging process in the proposed formulation is based on the amount of energy that it consumes. The cost of energy depends on the UC solution and is equal to the hourly marginal cost of electricity.

3. Comment: why the authors used the forecasted data? If you use historical data, can you get more clear results? For instance, you can compare the results with and without the proposed operation algorithm.

3. Answer: the purpose of the paper is to investigate the cost-benefits of implementing the LAES in the system, in future scenarios. To do that we had to use the future forecasts of RES scenarios. Although the data is based on official forecasts of Spanish island operators, we have provided a comparison with and without the proposed model.

4. Comment: what simulation tool did the authors use? What are the time windows (performance) of the operation? For example, can the proposed algorithms be executed every 1 min or 1 second?

4. Answer: cplex solver in GAMS is used to solve the MILP problem. Weekly UC for different seasons is solved for this study, then an average number is calculated as a yearly expectation in the tables. Weekly UC is usually not so fast, as it covers so many hours. But if the intention is to solve it on smaller time scales (for example day-ahead of hours-ahead), the run-time will be very small (can be solved under a minute). For even smaller time scales (like minutes and seconds), the authors suggest using a plain UC with the fixed status of the LAES. The chemical and physical processes in the LAES are very slow. Similar to the thermal units, whose commitment status is fixed in real-time operation, the commitment status of LAES is unable to change in very short time scales. The information about the simulation tool is added to the manuscript.

5. Comment: please also explain more details about the Liquid Air Energy Storage system. What are the benefits or disadvantages they have compared to the existing BESS system?

5. Answer: a summary of the advantages and disadvantages of LAES are mentioned in the revised manuscript: "disadvantages of LAES are the relatively high investment cost, large-scale requirements, and low round-trip efficiency. On the other hand, the advantages of LAES are high energy density, low storage losses, and not having geographical limitations."

Round 2

Reviewer 2 Report

No further comments

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