Optimizing H-Darrieus Wind Turbine Performance with Double-Deflector Design

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The work presents an interesting research of ANN model to predict the performance of a vertical axis wind turbine, this is “pertinent” with the journal, and in the same way its results are important for scientific community.

The manuscript structure is appropriate, starting with an extensive introduction based on update references from serious and relevant journals.

Methodology has been deeply detailed, leaving clarity in the numerical model used to carry out the simulation of the VAWT, where the turbulence model is detailed, its region and generated meshes on each domain, boundary conditions as well as its number of characteristic cycles applied of the time-step.

Model integrates a neural network to predict the optimal deflector design, specifically dimensions of double deflectors.

The validation is accomplished with experimental data previously presented by other authors, as well as some simulations carried out published in other works. The presented case study shows a closer fit to the experimental data than previous publications.

The results and their discussion are widely analyzed from velocity contour of the VAWT for several cases. (with and without single/double deflector).  

An original contribution is supported on neural networks scheme applied for training and subsequently obtaining the predictive model.

It’s a complete work with valuable information, therefore it’s recommended it be published.

Author Response

The authors thank for the referee’s positive comments.

Reviewer 2 Report

Comments and Suggestions for Authors

the paper presents a numerical investigation regarding vertical axis wind turbine with an innovative design with double deflector in order to improve the performance. The results reveal that the average power coefficient can be significantly increased by the usage of double deflectors.

In addition, the results from CFD simulations are employed to train an artificial neural network to find the optimal design for the double deflectors configurations. 

I consider the presented work to be mature and suitable for publication in the Energies journal.

Comments on the Quality of English Language

In my opinion, the english level is quite good.

Author Response

The authors thank for the referee’s positive comments.

Reviewer 3 Report

Comments and Suggestions for Authors

(1) （Line 170-175, page 4）The selection of the power coefficient is somewhat brief, Would you explain it in detail and supplement the corresponding references.

(2) （Line 196-197, page 6）The paper introduces the size and application direction of wind speed, but does not explain which type of wind spectrum is used, such as API, JONSWAP, etc. Please add.

(3) （Line 233-234, page 8）This paper points out that the initial conditions of the numerical simulation are different from the experimental operation, and whether they can be kept consistent to make the comparison more accurate, please explain the situation.

 

(4) （Line 304-307, page 11）In this paper, the numerical model is compared with reference 12, but the author also points out that there is a gap between the results. Please discuss them.

Author Response

The authors thanks for the referee’s helpful comments. Accordingly, we have revised the manuscript and the responses are listed as follows.

Comment#1: （Line 170-175, page 4）The selection of the power coefficient is somewhat brief, Would you explain it in detail and supplement the corresponding references.

Response: The selection of the power coefficient is related to the characteristic time t_c. Because the wave with the highest amplitude dominates the nonlinear interaction between the flow and the wind turbine, we choose 5 times the period of the highest amplitude wave to average the power coefficient. We have added a statement to explain this point (see line 187). The corresponding references also have been added and discussed (see line 175-178 and references 28-29).

Comment#2:（Line 196-197, page 6）The paper introduces the size and application direction of wind speed, but does not explain which type of wind spectrum is used, such as API, JONSWAP, etc. Please add.

Response: In this study we assume a uniform wind profile with constant wind speed and consistent direction. The wind spectrum models such as JONSWAP or API, are often used when dealing with more complex and variable wind conditions, particularly in the applications like offshore engineering or coastal studies. We have revised the related statements to clarify this point (see line 201-202).

Comment#3:（Line 233-234, page 8）This paper points out that the initial conditions of the numerical simulation are different from the experimental operation, and whether they can be kept consistent to make the comparison more accurate, please explain the situation.

Response: The operation of the wind turbine in the CFD model is the same as the practical condition. However, the dimensions of the computational domain in this study are larger than those in the wind tunnel. The purpose of these discussions is to explain why the current numerical prediction is better to fit the experimental data at high values of TSR than other studies. To clarify this point, we have added more statements to explain this situation. (see line 240-242)

Comment#4:（Line 304-307, page 11）In this paper, the numerical model is compared with reference 12, but the author also points out that there is a gap between the results. Please discuss them.

Response: We have added more statements to discuss this point (see line 316-318).