Self-Optimizing Control System to Maximize Power Extraction and Minimize Loads on the Blades of a Wind Turbine
Round 1
Reviewer 1 Report
I have no comments and suggestions.
Author Response
Thanks for your kind review.
Reviewer 2 Report
This paper describes a method to design and test a self-optimizing control algorithm for a wind turbine conversion system. It maximizes the power output while reducing the mechanical stress of the blades. The effectiveness of proposed method is validated through validations and compared with other control methods.
I suggest a major revision based on the following points:
1.- The authors are kindly asked to further stress the scientific novelties and new contributions of the paper.
2.- The authors claim that the proposed approach allows reducing the stress on the blades. Please add a paragraph and references explaining the implications on the lifetime and maintenance of the wind turbine. Is it possible to quantify this aspect?
3.- Figure 3. Please detail the software used, and details of the method like number of elements, computational time, etc.
4.- Eq. (15), cost function. The authors should describe why the cost function was defined in this form. Please develop.
5.- Figures 10-12. It is not surprising that the control methods reaching a maximum power extraction also are the ones producing higher levels of stress. Please acknowledge this fact. For example, the NMPC control algorithm provides less power than SOC with less variance and also less stress.
6.- Please provide details of the software that was used in the control part.
I hope that the remarks above will help to improve quality of the paper.
It is recommended to proofread the arcticle carefully
Author Response
Reviewer#2, Concern # 1: The authors are kindly asked to further stress the scientific novelties and new contributions of the paper.
Author response: The authors appreciate the feedback from the reviewer. To handle this recommendation, we have further described the novelty of our work in Section 1.2.
Author action: We updated the manuscript by adding the following paragraph in Section 1.2
The proposed SOC control scheme was implemented in MATLAB/Simulink. The simulations were conducted for various wind speeds and turbulence intensities, and the results were compared to those of the BCS and NMPC schemes. The comparison showed that the generalized SOC model outperformed BCS and NMPC regarding blade stress reduction for a given power output level. Furthermore, it was also observed that the SOC control scheme could extract more power from the turbine compared to the NMPC while keeping blade stresses within acceptable levels. The results confirm that the generalized SOC model is an effective way to reconcile conflicting objectives in wind turbine operation.
Reviewer#2, Concern # 2: The authors claim that the proposed approach allows reducing the stress on the blades. Please add a paragraph and references explaining the implications on the lifetime and maintenance of the wind turbine. Is it possible to quantify this aspect?
Author response: the authors appreciate the feedback from the reviewer. To handle this recommendation, we have included a paragraph of discussion about this topic at the end of Section 1.2.
Author action: we updated the manuscript by including the following paragraph at the end of Section 1.2:
Fatigue loading significantly affects wind turbines' lifespan, especially in the rotor blades. Fatigue loading occurs due to the combination of the wind field's stochastic nature impacting the rotor and rotational sampling caused by the finite spatial coherence of the wind field [22]. Excessive fatigue loads reduce blade life, increase maintenance costs, and financial losses [23]. Therefore, careful consideration of fatigue is crucial during wind turbine design and operation. Extensive literature exists on this subject, primarily focusing on utility-scale turbines due to the cost-effectiveness of testing. However, in small wind turbines, where manufacturers face challenges conducting extensive testing, addressing fatigue becomes even more significant.
Reviewer#2, Concern # 3: Figure 3. Please detail the software used, and details of the method like number of elements, computational time, etc.
Author response: the authors appreciate the careful revision of our manuscript. We have handled these recommendations.
Author action: we updated the manuscript by including the suggested information in the caption of figure 3.
Reviewer#2, Concern # 4: Eq. (15), cost function. The authors should describe why the cost function was defined in this form. Please develop.
Author response: The authors appreciate the careful revision of our manuscript. We have handled this recommendation.
Author action: we updated the manuscript by discussing and justifying the cost function selection. Please refer to the highlighted version to find the manuscript changes.
Reviewer#2, Concern # 5: Figures 10-12. It is not surprising that the control methods reaching a maximum power extraction also are the ones producing higher levels of stress. Please acknowledge this fact. For example, the NMPC control algorithm provides less power than SOC with less variance and also less stress.
Author response: The authors appreciate the feedback from the reviewer. Figure 12 shows a further explanation of the controller's performance, where it is clearly seen the better performance of the SOC over the other two control approaches.
Author action: We updated the manuscript by further discussing the results of Figure 12.
Reviewer#2, Concern # 6: Please provide details of the software that was used in the control part.
Author response: We have specified in Section 1.2 that the software used in this research was MATLAB/Simulink.
Author action: We updated the manuscript by including this information in Section 1.2.
Reviewer 3 Report
This paper demonstrate a multi-target optimization method to maximize power extraction and minimize loads on the blades of a wind turbine. The topic is interesting. And the paper is well organised. It is ready for publication after considering the following issues.
(1) This paper adopts many abbreviations and symbols. A notation table is recommended to make it more readable.
(2） It is recommended to add some quantitative results in the abstract and conclusion sections to illustrate the advatage of the proposed method.
(3) A flow chart of the proposed method is also recommended to brtter clarify the operating process for engineering reference.
The English language of this paper is good.
Author Response
Reviewer#3, Concern # 1: This paper adopts many abbreviations and symbols. A notation table is recommended to make it more readable.
Author response: The authors appreciate the feedback from the reviewer. We have added a notation table at the beginning of the paper.
Author action: We updated the manuscript by adding Table 1 with acronyms definitions.
Reviewer#2, Concern # 2: It is recommended to add some quantitative results in the abstract and conclusion sections to illustrate the advantage of the proposed method.
Author response: The authors appreciate the feedback from the reviewer. We have included a brief description of the results in the abstract to handle this recommendation.
Reviewer#2, Concern # 3: A flow chart of the proposed method is also recommended to better clarify the operating process for engineering reference.
Author response: The authors appreciate the careful revision of our manuscript. We have not added a flowchart since the paper already had an algorithm description (page 12) for engineering and methodology reproduction.
Round 2
Reviewer 2 Report
The authors have replied my questions
The authors have replied my questions
