A Hybrid DEA–Fuzzy COPRAS Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey

Round 1

Reviewer 1 Report

Please cite some relevant papers from the Sustainability Journal. 

Please specify the limitations of the proposed study.

Who is the decision maker in the study? Who will gain the maximum benefit from the paper?

Discussion to enhance clarifying the paper's position and relative contribution to literature in related areas is unconvincing and missing.

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Congratulations on the choice of subject matter. It is an interesting, well-written work, valuable for science.  The layout of the manuscript is correct. The literature cited is relevant to the topic undertaken. The arguments presented in the article confirm the necessary calculations. I believe that the subject matter is original and important from the point of view of the development of science, although in my opinion, the following elements need to be clarified:

 

1.     The lack of a clearly formulated research hypothesis. Therefore, I could not find information on whether the hypotheses were verified positively or negatively.

 

2.     There is no information on what criterion was used in the selection of 10 wind farms for testing.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

 Dear Authors, Editors

 

Thank you for the opportunity to review the manuscript entitled " A Hybrid Dea-Fuzzy Corpas Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey." The topic covered in this manuscript is significant and applicable in real-world situations. After conducting a thorough review, I would like to provide some constructive feedback on certain aspects of the manuscript to ensure that it meets the journal's high standards.

Dear Authors, Editors

Thank you for the opportunity to review the manuscript entitled " A Hybrid Dea-Fuzzy Corpas Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey." The topic covered in this manuscript is significant and applicable in real-world situations. After conducting a thorough review, I would like to provide some constructive feedback on certain aspects of the manuscript to ensure that it meets the journal's high standards.

 

Abstract: The abstract provides a clear overview of the study, which focuses on developing a systematized evaluation framework for assessing the efficiency of wind farms in Turkey. The use of DEA-Fuzzy COPRAS is introduced as a methodology to evaluate the efficiency of 11 wind power plants based on selected inputs and outputs. The advantages of the proposed method, such as accurate efficiency evaluation and consideration of multiple criteria, are highlighted. Additionally, the abstract mentions the ability of DEA-Fuzzy COPRAS to handle uncertainty in wind energy production inputs and outputs. The results are validated through a sensitivity analysis of criteria. The abstract concludes by emphasizing the potential benefits of implementing the proposed method for wind power plants and renewable energy projects, enabling cost savings and improved resource utilization during the planning phase. However, it could be further enhanced by briefly mentioning the implications and broader significance of the research in terms of sustainability and renewable energy development.

 

1.           Introduction:

The Introduction provides a comprehensive background and justification for the study by addressing the increasing electricity demand in Turkey and the necessity of renewable energy sources to fulfill this demand. It effectively highlights the limitations associated with conventional carbon-fueled power plants while emphasizing the rising popularity and accessibility of renewable energy. The introduction introduces wind energy as a sustainable and economically viable solution in Turkey, providing relevant statistics regarding wind power capacity and its contribution to electricity production. The inclusion of visual aids such as figures depicting the growth of wind power installations and the Wind Energy Potential Atlas enhances the clarity of the discussion. The section appropriately introduces the research objective, which is to evaluate the efficiency of wind farms in the Marmara Region of Turkey using the DEA-Fuzzy COPRAS methodology. The novelty of the study is adequately emphasized, particularly in terms of incorporating qualitative and quantitative variables and utilizing FTOPSIS to enhance the DEA method. However, to enhance the understanding of readers, it would be beneficial to provide a clearer explanation of why Multi-Criteria Decision-Making (MCDM) models like DEA and COPRAS based on Fuzzy Sets are suitable for this research. This clarification would help differentiate the contextual information from the specific research approach, especially in comparison to previous studies.  Additionally, it is recommended that the authors explicitly state the unique contributions of this study. By highlighting the distinct aspects that make this research necessary and valuable, readers will gain a better understanding of the importance of conducting this study to address the specific issues faced in Turkey.

2.           Literature review:

The literature review effectively summarizes the existing knowledge on the use of Data Envelope Analysis (DEA) in energy efficiency studies, with a specific focus on wind energy. It provides a clear understanding of DEA's advantages, its applications in various areas, and the potential for incorporating qualitative data into DEA models. However, to further improve the manuscript, attention should be given to the following suggestions:

 Firstly, while the literature review offers a comprehensive overview of DEA and its applications in energy efficiency studies, it would be beneficial to explicitly state the specific research gap or problem that the current study aims to address. By clearly identifying this gap, readers will better grasp the relevance and significance of the study within the existing literature.

Secondly, the review would benefit from a more structured approach, such as categorizing the different applications of DEA in energy efficiency studies. For instance, grouping the studies based on the type of renewable energy source (e.g., wind, solar, hydro) or the specific aspect of energy efficiency being evaluated (e.g., technical efficiency, economic efficiency, environmental impact) would enhance the organization and reader-friendliness of the review.

Furthermore, while the review effectively summarizes the existing literature, it would be valuable to provide a critical analysis of the strengths and limitations of DEA as an energy efficiency measurement tool. This analysis could include discussing potential biases or assumptions associated with DEA, addressing challenges in data collection and analysis, and highlighting areas for further research or improvement.

In addition, the review briefly mentions the potential for incorporating qualitative data and fuzzy logic into DEA models but lacks an in-depth discussion. To enhance the review, it would be helpful to provide a more detailed exploration of the benefits, challenges, and methodologies involved in integrating qualitative data. Moreover, discussing the implications of such integration for enhancing the accuracy and applicability of DEA models would be valuable.

Finally, although the review includes relevant studies, it would be beneficial to include more recent publications to ensure the review reflects the current state of research in the field. This could involve searching for studies published in the last few years that have made advancements in DEA methodologies or have explored novel applications of DEA in energy efficiency studies.

By incorporating these suggestions, the literature review will provide a more focused, critical, and up-to-date analysis of DEA's applications in energy efficiency studies, specifically in the context of wind energy.

3.           Methodology:

The authors introduce the Fuzzy COPRAS method, which offers an effective and straightforward approach for Multi-Criteria Decision Making (MCDM) problems by evaluating and ranking alternatives based on their importance and benefit values. The COPRAS method assumes that alternative and criterion values are certain or adequate.

However, to address the challenges of uncertainty and inadequacy, the authors further develop the Intuitionistic Fuzzy COPRAS (IF-COPRAS) method. Before presenting the IF-COPRAS method, the authors should provide a comprehensive explanation of the fundamentals of fuzzy sets and intuitionistic fuzzy sets and highlight the advantages of intuitionistic fuzzy sets in dealing with uncertainty. I suggest that this section should be at the beginning of Methodology such as Sub-section 3.1.

4.           Case study: 

The section mentions that four experts from a prominent wind power plant company in Turkey, each with over 10 years of experience, were interviewed to identify the factors affecting wind deployment and evaluate the 10 wind power plants based on qualitative criteria (C1, C2, C3, C4, and C5). However, the reliability of the findings may be limited due to the small panel of experts involved.

While the expertise and experience of the interviewed experts are valuable, it is important to acknowledge that the opinions and perspectives of only four individuals may not fully represent the entire range of factors influencing wind deployment or provide a comprehensive understanding of the evaluation criteria. The findings could be influenced by individual biases, limited perspectives, or specific organizational interests.

To enhance the reliability and validity of the study, it is recommended to involve a larger and more diverse panel of experts from different wind power plant companies, academic institutions, research organizations, and relevant stakeholders. A broader range of expertise and perspectives can contribute to a more comprehensive and robust evaluation of the factors influencing wind deployment and the qualitative criteria used for evaluation.

5.           Results:

The research findings, as presented in Table 11 and Figure 7, reveal the efficiency scores and outcomes of the DEA models for wind power plants. Four plants (DMU3, DMU5, DMU6, and DMU7) are identified as efficient, while the rest are considered less efficient. Insufficient investment plans for wind power plants are suggested as a contributing factor to this disparity.

The study emphasizes three key points: the potential for improving wind power plant efficiency, the importance of careful investment planning, and the higher relative efficiency of wind farms with fewer turbines compared to those with similar capacities. The research incorporates both qualitative and quantitative data to evaluate the DMUs, enhancing the understanding of efficiency and its relationship with qualitative characteristics. The inclusion of qualitative features expands the generic CCR-DEA model.

A sensitivity analysis is conducted to assess the impact of varying criteria weights on the results. The analysis demonstrates the stability of the wind plant ranking despite changes in qualitative evaluations, indicating the reliability of the ranking outcomes. The study highlights the suitability of the MCDA method for decision-making problems with fluctuating criteria weights, emphasizing the need to consider both quantitative and qualitative data for more accurate and comprehensive decision-making.

The holistic approach employed in the research ensures a well-rounded assessment of the situation, considering non-quantifiable factors and the human element. This approach promotes more effective and sustainable decision-making in the long run. The sensitivity analysis further supports the reliability and applicability of the proposed model.

6.           Implications

This section provides valuable insights into the managerial and practical implications of qualitative DEA for wind power plant evaluations. With some additional real-world examples and possibly further elaboration on specific strategies or actions that can be taken based on DEA findings, the section could become even more impactful.

7.           Conclusion:

The concluding section of the paper presents a comprehensive overview of the study and its findings; however, there are areas that could be improved.

Firstly, a clear and concise summary of the main findings and their implications should be provided, emphasizing their significance in relation to the research objectives. Additionally, the statement regarding the proposed model's ability to address the disadvantage of conventional DEA methods in uncertain environments requires further elaboration and clarification. The inclusion of specific examples or case studies would greatly enhance the discussion on the role of qualitative evaluations in DEA, showcasing practical applications and highlighting the value of incorporating qualitative data. While the future works section presents numerous potential research directions, it would be beneficial to prioritize the most relevant and feasible avenues to ensure focus. Finally, it is important to include a brief reflection on the study's limitations, acknowledging any constraints, data limitations, or assumptions made during the research process. This transparency would strengthen the overall conclusion and provide a balanced perspective.

8.     Reviewer’ opinion:

In summary, after a careful evaluation of the current manuscript, it is evident that a major revision is required in order to meet the rigorous standards set by the journal.

Best regards,

 Minor editing of English language required

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Dear Authors and Editors,

I am grateful for the opportunity to review the article titled "A Hybrid Dea-Fuzzy Corpas Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey." The authors have effectively tackled relevant and contemporary concerns in their research, making it a valuable contribution to the field.

I believe that readers of the journal will find this work interesting. Upon addressing the reviewer's comments, I find that the manuscript has become clear, concise, and well-written. The introduction establishes relevance, while the literature review adequately presents previous findings, allowing readers to understand the rationale and procedures of the current study. Although the methods used are generally appropriate, I recommend clarifying certain details for better comprehension.

The results are presented in a clear and compelling manner. The author's contribution to the research literature in this area is systematic and noteworthy.

Overall, this high-quality manuscript addresses an important issue and proposes a novel method for evaluating wind farm efficiency. The comprehensive approach, consideration of multiple criteria, and acknowledgment of uncertainty make the proposed method promising for decision-makers and stakeholders in the renewable energy sector.

Sincerely,

Minor editing of English language required