Wind Energy Ships: Global Analysis of Operability

Round 1

Reviewer 1 Report

This article is very interesting and written clearly. The global reanalysis databases of wind and waves are used to analyze the suitability of ocean areas for the deployment of Energy Ships in terms of operational conditions associated to wind speed and wave height.

Global wind and wave spatial and temporal variability was performed and mean and the standard deviation were calculated for wind velocity and wave height. The Authors show global distribution of: mean wind velocity, standard deviation of wind velocity, inter-annual standard deviation of mean wind velocity and global distribution of: mean significant wave height, standard deviation of the significant wave height and inter-annual standard deviation of significant wave height.

Based on previous calculations the Authors performed Global analysis of Energy Ships operability. The research results are described in great detail.

In the end, the global distribution of the seasonal mean operability was performed on the figures. Ranges of maximum mean operability for the year and for the DJF, MAM, JJA and SON seasons in the trade winds and monsoon coastal regions were performed in tables.

Operation of Energy Ships depends on wind and wave intensities. After the definition of the mean wind velocity and the significant wave height operability ranges for these ships, global databases of wind and waves have been used to plot the global maps for different  reason. These results should be taken as a first approximation to the analysis of Energy Ship operability.

I have no remarks to the article.

 

But the references are not actually. You should add some new articles.

 

And I have a one question. You show mean and std. dev. I know that it is the most popular descriptive statistics but they are calculated for the data which have a normal distribution. Did You check a distribution in Your data?

And, besides everything I’m interested in, how the figures will be look like if You show on the figure dominant (modal) if it doesn't take long.

Best regards

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

First of all, many thanks for your comments and reviews. Thanks to them we believe that the quality of the manuscript will be higher than before.

Next, you will find our answers and comemnts to all of them.

Remark #1:

“I have no remarks to the article but the references are not actually. You should add some new articles”.

Response:

Some new references have been added conveniently referred in the article.

Remark #2:

“And I have a one question. You show mean and std. dev. I know that it is the most popular descriptive statistics but they are calculated for the data which have a normal distribution. Did you check a distribution in your data?”

Response:

For this first global analysis, we considered that the simple statistics presented in the paper would be enough as a first approach to the problem and for an overall comprehension of the more suitable Ocean areas for the deployment of energy ships. Of course, when specific areas were analyzed, more detailed statistics would be necessary for the operability studies.

Remark #3:

“And, besides I´m interested in, how the figures will look like y you show the figure dominant (modal) if it doesn’t take long.”

Response:

We did use the mean values because almost all the published studies focused on changes in wave climate consider the mean as the reference indicator (e.g. Casas-Prat et al., 2018; Hemer et al., 2013; Lemos et al., 2019; Mori et al., 2013; Morim et al., 2018, 2020; Wang et al., 2014).

• Casas-Prat, X.L. Wanga and N. Swart. CMIP5-based global wave climate projections including the entire Arctic Ocean. Ocean Modelling, Volume 123, March 2018, Pages 66-85.
• Hemer, M. A., Katzfey, J. & Trenham, C. E. Global dynamical projections of surface ocean wave climate for a future high greenhouse gas emission scenario. Ocean Model 70, 221–245 (2013).
• Lemos, G. et al. Mid-twenty-frst century global wave climate projections: results from a dynamic CMIP5 based ensemble. Glob. Planet. Change 172, 69–87 (2019).
• Mori, N., Shimura, T., Yasuda, T. & Mase, H. Multi-model climate projections of ocean surface variables under diferent climate scenarios—future change of waves, sea level and wind. Ocean Eng. 71, 122–129 (2013).
• Morim, J., Hemer, M., Cartwright, N., Strauss, D. & Andutta, F. On the concordance of 21st century wind-wave climate projections. Glob. Planet. Change 167, 160–171 (2018).
• Morim, J. et al. A global ensemble of ocean wave climate projections from CMIP5-driven models. Sci. Data 7, 1–10 (2020).
• Wang, X. L., Feng, Y. & Swail, V. R. Changes in global ocean wave heights as projected using multimodel CMIP5 simulations. Geophys. Res. Lett. 41, 1026–1034 (2014).

Reviewer 2 Report

This paper presents the use of Floating Production and Storage (FPS) sailing ships that navigate through the ocean using wind force and utilize harvested wind/wave power to produce and store hydrogen fuel.
The leading idea behind is to find the optimal harvesting regions for wind/wave green energy in a complex model of ship routes with ships to be refuelled, wind/wave current situation for optimal harvesting, … Optimization here is still an open field and probably vary interesting for future research. 

In the article my remarks are:
- Introduction:
   - line 41: specify the unit variable
      - nearshore (distance to the shoreline < 90km)
      - intermediate waters ( depth < 200m )
   - line 78: The main disadvantages of Energy Ships are that they need part of the harvested wind energy to propel the ship
      - It is also a big advantage, able to search for “wealthy energy regions”

- Global wind and wave spatial and temporal variability:
   - Very nice and useful statistics of global wind and wave variability. No comments.

- Wind and waves Energy Ships operational ranges & Global analysis of Energy Ships operability:
   - Very nice and useful statistics of Energy Ships operational ranges and operability. As mentioned before, this field of research needs much similar analysis using optimization approaches to find as optimal as possible scenario for energy harvesting, its delivery and Energy ships survivability.  No further comments.

Author Response

Dear Reviewer,

First of all, many thanks for your comments and reviews. Thanks to them we believe that the quality of the manuscript will be higher than before.

Next, you will find our answers and comemnts to all of them.

Remark #1:

“Introduction. Line 41: specify the unit variable

• nearshore (distance to the shoreline < 90 Km)
• intermediate waters (depth < 200 m)”

Response:

Done

Remark #2:

“The main disadvantages of Energy Ships are that they need part of the harvested wind energy to propel the ship.

• it is also a big advantage, able to search for “wealthy energy regions”

Response:

We agree with the reviewer that the mobility of Energy Ships has the advantage of being capable of search for convenient wind and wave areas for operation. In fact several lines above the comment about the disadvantage this mobility is indicated also as one advantage:

“… first, the Energy Ship could sail to the areas were the wind and wave characteristics are appropriate, depending on location and season to optimize power production …”

Remark #3:

“- Global wind and wave spatial and temporal variability:

• Very nice and useful statistics of global wind and wave variability. No comments.”

Response:

Many thanks.

Remark:

“- Wind and waves Energy Ships operational ranges & Global analysis of Energy Ships operability:

• Very nice and useful statistics of Energy Ships operational ranges and operability. As mentioned before, this field of research needs much similar analysis using optimization approaches to find as optimal as possible scenario for energy harvesting, its delivery and Energy ships survivability. No further comments”.

Response:

Many thanks.

Reviewer 3 Report

Interesting (but fairly basic) application of the global wind and wave data bases in terms of the operability of "wind energy ships". The S4B project serves as crucial  background information for the present study. However there is no publicly available paper describing the S4B project - alternatively the present paper could be amended to provide a short description of that project.

Much more important is the lack of any information on the projected cost of energy from wind energy ships. There is a short mention on p.8 that "tanker, 300 m length was found to produce the lowest LCOE" - but of course the only relevant fact is missing: What is that LCOE amount - my guess is that this will be orders of magnitude away from anything useful - but I might be wrong. Anyway that information MUST be presented otherwise the study is of no value whatsoever.

 

Author Response

Dear Reviewer,

First of all, many thanks for you comments and reviews. Definitively, the paper will reach higher levels of quality thansk to them.

Next you will find our answer to them. All the changes can be found on the reviewed manuscript.

Regards,

 

Remark #1

“Interesting (but fairly basic) application of the global wind and wave data bases in terms of operability of “wind energy ships”. The S4B project serves as crucial background information for the present study. However there is no publicly available paper describing the S4B project- alternatively the present paper could be amended to provide a short description of that project.

Much more important is the lack of any information on the projected cost of energy from wind energy ships. There is a short mention on p.8 that “tanker, 300 m length was found to produce the lowest LCOE”- but of course the only relevant fact is missing: What is that LCOE amount- my guess is that this will be orders of magnitude away from anything useful – but I might be wrong. Anyway that information MUST be presented otherwise the study is of no value whatsoever.”

Answer

We agree to the reviewer that the results of the economic analysis of operation of these ships could be very interesting for publication and in fact we are considering to make a paper relative to these results. The economic model developed has been used in the project to compare the cost of synthetic fuel produced by three ship sizes with common operational conditions. The results obtained indicate that the lower LCOE is obtained by the bigger ship. But the project has not calculated the LCOE in all global locations.

The purpose of this paper is only to give response to one of the Ship 4 Blue project objectives, referring to the global analysis of suitable areas for wind energy ships operation, and the mention of the more suitable ship size was to introduce the paragraph 3 and justify figure 4.

We have added to the paper the project reference:

Grupo Calcom, Bound4Blue, IHCantabria y Centro Nacional del Hidrógeno (2019). Ship 4 Blue. Desarrollo de estudios críticos de tipo técnico y económico para el análisis de la viabilidad de un nuevo sistema de generación de energía eólica off-shore mediante un buque propulsado a vela y dotado de sistemas de producción energética. Entidades financiadoras: Fondos FEDER UE, Gobierno de Cantabria y SODERCAN. Project RM16-XX-20. (in Spanish).

And the paragraph:

“Among the different ship sizes analyzed in the S4B project (100, 150 and 300 m length), a reformed bull carrier or tanker, 300 m length was found to produce the lowest Levelized Cost of Energy (LCOE).”

Has been substituted by the follwoing one:

“Among the S4B research tasks, an economical and financial projection model has been developed to obtain the final production costs in terms of operability variables and ship size and configuration. Using that model, it was found that the lowest LCOE was obtained with the biggest of the three reformed bull carrier of tanker sizes analyzed (100, 150 and 300 m length).”