Multi-Criteria Decision Analysis for Proposed Areas for Offshore Wind Implementation with Monte Carlo Method

Mata, Cristina; Romero, Daniel; Adema, Niels Cornelis

doi:10.5194/wes-2025-188

Preprints

https://doi.org/10.5194/wes-2025-188

Preprints

30 Oct 2025

| 30 Oct 2025

Status: this preprint is currently under review for the journal WES.

Multi-Criteria Decision Analysis for Proposed Areas for Offshore Wind Implementation with Monte Carlo Method

Cristina Mata, Daniel Romero, and Niels Cornelis Adema

Abstract. This research presents a comparative study on offshore wind energy site selection, focusing on technological, environmental, social, and regulatory barriers, while ensuring compatibility with other marine activities and habitats. The study applies Multi-Criteria Decision Analysis (MCDA) through the Analytic Hierarchy Process (AHP) and contrasts it with a probabilistic approach based on Monte Carlo simulations. Although AHP is widely used, its deterministic nature limits the representation of uncertainty in decision-making. To address this, Monte Carlo methods are applied independently, extending previous approaches by incorporating additional design criteria and enhancing robustness. Results demonstrate that integrating probabilistic uncertainty significantly improves the reliability of site selection, identifying optimal zones with higher confidence. Overall, the study highlights the advantages of Monte Carlo simulations over AHP in supporting sustainable and reliable offshore wind energy planning.

Received: 28 Sep 2025 – Discussion started: 30 Oct 2025

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

Download & links

Cristina Mata, Daniel Romero, and Niels Cornelis Adema

Status: final response (author comments only)

Subscribe to comment alert

RC1:
'Comment on wes-2025-188', Anonymous Referee #1, 25 Nov 2025
In the paper “Multi-Criteria Decision Analysis for Proposed Areas for Offshore Wind Implementation with Monte Carlo Method”, the authors present a comparison of different methods for assessing three potential offshore wind farm locations in Spain. The paper compares Analytic Hierarchy Process (AHP) with two Monte Carlo (MC) simulation approaches for ranking three potential offshore wind farm locations in Spain. The topic is relevant, and the finding that different methods yield significantly different rankings is an interesting case study. However, several points need clarification and improvement:
The authors write: “Unlike most prior research that integrates AHP and Monte Carlo into a hybrid model, this work directly compares the outcomes of traditional AHP with two independent Monte Carlo simulation approaches”. Later they write: “Two Monte Carlo simulation approaches were implemented to refine the AHP results…”. These statements appear contradictory. Are the MC approaches independent of AHP or do they refine its results? Please clarify.

The paper suggests that the MC results are "better," but the basis for this claim is unclear. How do your tests or validations demonstrate superiority? For example: Does MC lead to higher expected revenue or profitability? Does it provide more stable results under uncertainty? Or should the interpretation of the results be something completely different? Please explain the practical implications for decision-makers.

Levelized Cost of Electricity (LCOE) is widely used for site competitiveness. Including an LCOE-based ranking of the three sites would make the paper more accessible to readers familiar with cost-driven approaches.

CAPEX and OPEX are critical in offshore wind investment decisions. Are these included under "Operational/Construction Conditions" (Table 3) or elsewhere? How are export cable distances in Table 2 translated into CAPEX? What cable technology assumptions are made? Please provide more details.

In Table 1, “Levantine-Balearic” shows higher mean wind speed and lower wake losses than “Canary Islands,” yet has a lower capacity factor and fewer full-load hours. Can you please explain why this is?

It would be great to see 1 or 2 scientific references showing the suitability of GWA and WAsP for assessing the offshore wind resources in Spain, including some validation if possible.
Citation: https://doi.org/10.5194/wes-2025-188-RC1
RC2: 'Comment on wes-2025-188', Anonymous Referee #2, 17 Dec 2025

The article investigates the application of different Monte Carlo methods to assess the feasibility of offshore wind turbines in three proposed areas in Spain. The results and analyses are relevant and potentially valuable for the research community. However, I believe that the manuscript requires major revisions before it can be considered for publication. In particular, the following issues should be addressed:
Introduction: The Introduction requires substantial improvement. A more comprehensive review of related and recent literature is necessary, particularly studies employing Monte Carlo or probabilistic approaches for offshore wind assessment. Furthermore, the research gap addressed by this study should be clearly articulated, and the specific novelty and contribution of the work should be explicitly stated.
Techno-economic assessment: Key techno-economic parameters, such as capital expenditure (CAPEX), operational expenditure (OPEX), and levelized cost of energy (LCOE), should be incorporated into the analysis. Including these metrics would significantly strengthen the practical relevance of the study and allow for more meaningful comparisons between the proposed sites.
Validation and robustness of results: Although a sensitivity analysis has been conducted, it appears insufficient to fully demonstrate the robustness and validity of the results. The authors should clarify how the proposed methodology and outcomes are validated. Additional validation approaches, such as comparison with existing studies, benchmarking against real-world data, or more extensive uncertainty and convergence analyses, should be considered to substantiate the reliability of the findings.

Citation: https://doi.org/10.5194/wes-2025-188-RC2
RC3:
'Comment on wes-2025-188', Anonymous Referee #3, 19 Dec 2025
The manuscript examines an important and timely subject—offshore wind farm siting in Spain using AHP and Monte Carlo simulations. Despite the potential value of this work and the authors’ efforts, the manuscript in its current form necessitates major improvements to enhance its coherence, methodological robustness, and contribution to the field.
Reviewer’s Comments:
Introduction Section: The introduction does not clearly articulate the novelty or specific contributions of the study. Existing international literature already includes applications of the Analytic Hierarchy Process (AHP), Monte Carlo simulations, and site‑suitability assessments for offshore wind projects, including studies focused on Spain. Therefore, the manuscript must explicitly clarify what distinguishes this work from prior research. What is the innovation introduced by this study? What unique contributions does it offer to the field? If the novelty lies solely in the independent application of these methods, this should be justified and contrasted with the potential advantages of developing an integrated or hybrid methodological framework. To strengthen the introduction, I strongly recommend conducting and presenting a comprehensive literature review, which is currently absent. Following this review, the authors should identify the existing research gaps and clearly communicate which of these gaps the present study aims to address. The inclusion of explicit research questions—while not mandatory—could further enhance the clarity of the study’s objectives and help articulate its contributions more effectively.

After presenting a thorough literature review and identifying the current research gaps, the authors should clearly and explicitly describe the study’s contributions and novelty. At present, these elements are not sufficiently evident in the introduction.

Introduction Section, Paragraph 1: The manuscript addresses a highly relevant and timely topic: the sustainable deployment of offshore wind energy. However, the introductory paragraph remains overly general and should be enriched with concrete information. For example, how many offshore wind projects have been developed to date in Spain and in Europe? Why is sustainable site selection critical for offshore wind development? Which specific aspect of offshore wind deployment does this study focus on, and why is this focus important? Expanding this paragraph with precise data and contextualization will significantly strengthen the introduction.

Page 2, Line 49: The sentence “This chapter describes the methods and materials used in the study.” is unnecessary and should be removed.

Section 2.1: The manuscript does not sufficiently explain how the three study sites were identified and delineated. It is essential to clarify the methodological process that led to the selection of these areas. Were geospatial datasets incorporated into a GIS environment, and was a geospatial analysis performed to derive these locations? Did the authors develop a GIS‑based model to determine the spatial extent, shape, and boundaries of the selected sites? The procedure underlying these decisions must be explicitly described, rather than only presenting the site‑selection criteria.

Figure 1: The figure should be revised to include essential cartographic elements, specifically the north arrow and an appropriate map scale. These components are necessary to ensure spatial orientation and to allow readers to interpret distances and spatial relationships accurately. Please incorporate both the north direction and the spatial scale into all map-based figures. In addition, a clear and comprehensive legend must be incorporated. The legend should explicitly distinguish the polygons representing the investigated sites, as well as the interconnection cable routes. At present, the use of identical line colors for multiple features reduces interpretability and should be avoided. Furthermore, it is unclear whether the offshore substation is depicted in the figure, likely due to the small size and limited visual clarity of the current layout. The offshore substation and offshore wind turbines should be clearly highlighted and differentiated using appropriate symbology and a corresponding legend entry. If this cannot be achieved within the current figure dimensions, the figure should be enlarged to ensure readability. As it stands, the representation of what appears to be an offshore substation is ambiguous and will not be sufficiently clear to the reader. A complete legend is particularly important because the map must be fully readable as a standalone figure.

Proper citations are required for the Global Wind Atlas and the WAsP software in the section corresponding to Lines 72–82. All information not generated by the present study must be appropriately referenced. In particular, the material presented in Lines 75–80 appears to be derived from the Global Wind Atlas and should be cited accordingly. This requirement applies throughout the entire manuscript.

The quality of the English language throughout the manuscript requires improvement. Grammatical errors, awkward phrasings, and typographical mistakes are present across sections. I strongly recommend a thorough linguistic revision to enhance clarity, precision, and overall readability.

Lines 115-119: The phrase “sources like the…” requires clarification. Please specify precisely which data sources were utilized and ensure that all sources are appropriately cited. Additionally, I recommend including a table that organizes the data sources according to each site-selection criterion. This will enhance transparency, facilitate readers’ ability to locate the relevant information, and strengthen the overall rigor of your research.

Absence of a Methodological Scheme: The Materials and Methods section lacks a clearly defined methodological scheme. For studies that rely on sequential analytical stages, such a scheme is essential, as it offers readers a coherent overview of the methodological architecture, enhances transparency, and supports reproducibility. In the present manuscript, the inclusion of a methodological scheme would significantly improve the clarity of the research design by delineating the procedures employed for identifying eligible sites for evaluation (e.g., geospatial analysis; wind resource assessment, and estimation of energy potential using WAsP), the implementation of the AHP method, the methodological steps associated with the Monte Carlo simulations, the sensitivity analysis techniques, and the innovative components of the proposed approach. Furthermore, a well‑structured scheme would explicitly illustrate how industry expert input is incorporated into the study, indicating the stages at which their contributions are integrated. Overall, the methodological scheme should serve as the backbone of the Materials and Methods section, guiding its organization and coherence.

Table 2: The criterion applied here is not a visual‑impact assessment but rather the setback distance from the coastline intended to mitigate potential visual disturbance. A genuine visual‑impact assessment requires substantially more information, including detailed turbine specifications (hub height, rotor diameter, total tip height), full wind‑farm layout and spatial configuration, geospatial and topographic data, representative observer viewpoints, photorealistic visual simulations, etc. None of these elements are incorporated in the current manuscript. Therefore, the criterion presented cannot be characterized as a visual‑impact, and it should be revised accordingly.

Table 3: It is unclear why proximity to ports is classified as a social criterion rather than a techno‑economic metric. Both in the manuscript’s definition and in standard offshore‑wind‑farm assessment frameworks, proximity to ports is fundamentally a techno‑economic parameter, as it directly influences construction logistics, installation feasibility, and operation‑and‑maintenance (O&M) strategies. The categorization in Table 3 and in your analysis should therefore be reconsidered and revised accordingly.

Line 175: The fundamental Saaty scale ranges from 1 to 9. Please clarify why a 1–7 scale is used in this study and justify this deviation from the standard formulation, particularly in terms of its methodological implications and suitability for your research context.

Lines 184–187: The manuscript states that a 0–10 scale was used. However, adopting such a scale means that the method applied is no longer the AHP. The classical AHP framework, as established by Thomas Saaty, is based on the 1–9 fundamental ratio scale, where each value carries a specific semantic meaning (e.g., equal, moderate, strong, very strong, or extreme importance). Introducing a value of 0 is mathematically incompatible with the pairwise‑comparison structure, as it disrupts the reciprocal matrix (since 1/0 is undefined) and violates the ratio‑scale foundations of AHP. Moreover, earlier in the manuscript (Line 175), you state that a 1–7 scale was used. This creates a methodological inconsistency: the manuscript refers to two different scales (1–7, and 0–10), none of which are clearly justified or coherently applied. It is therefore unclear what scale was actually used in the analysis. Please clarify the intended scale, justify any deviation from the standard 1–9 Saaty scale, and revise the methodology to ensure internal consistency.

Lines 188–194: The description of the AHP procedure requires revision. Expert judgments are organized into a reciprocal 𝑛×𝑛 pairwise‑comparison matrix, in which each criterion is evaluated relative to all others, unity values appear along the diagonal, and reciprocal values occupy symmetric positions. Please revise this section to accurately reflect the methodological structure. Furthermore, the manuscript provides no information regarding the experts who contributed to the weighting process. This is a critical omission, as the validity of AHP results depends heavily on the expertise and credibility of the participants. Please specify: (i) the number of experts involved; (ii) their professional background and years of experience in offshore wind development; (iii) whether they are industry experts, academics, or a combination of both; (iv) their areas of specialization (e.g., environmental assessment, marine spatial planning, offshore engineering); and (v) the rationale for selecting these particular experts. Additionally, the manuscript should clarify the process through which expert input was collected—whether via online questionnaires, structured interviews, workshops, or another method—and whether their involvement was limited exclusively to assigning weights or extended to other stages of the assessment. Without this information, the transparency and reproducibility of the methodology are significantly weakened.

Section 2.4.2: Although the manuscript states that random weights were generated from normal distributions and that 10,000 iterations were performed, several essential methodological details are missing. The current description is insufficient to ensure reproducibility or methodological rigor. Specifically, the manuscript does not justify the selection of the probability distributions used to generate the random weights, and does not describe how the AHP‑based suitability scores were recalculated during each Monte Carlo iteration. To ensure methodological completeness, the authors should provide all assumptions and constraints underlying the simulation, and the software or computational environment employed (e.g., Python, MATLAB, R). The authors should clearly describe all methodological steps undertaken in the implementation of the Monte Carlo simulations. A complete and transparent account of the procedure is essential for ensuring reproducibility and for allowing readers to fully understand the analytical workflow.

Sensitivity Analysis: In this study, the assessment of sensitivity would be substantially strengthened by examining how the results respond to variations in the weighting scheme. Employing alternative weighting methods would allow for a more rigorous evaluation of the robustness of both the methodological framework and the expert‑derived weights. For instance, the ENTROPY method offers an objective means of determining criterion weights based on the intrinsic characteristics of the candidate sites. Integrating such an approach would enable a systematic comparison between subjective (expert‑based) and objective weighting schemes, thereby providing deeper insights into the stability of the methodological choices and the reliability of the final site‑suitability outcomes.

Results Section: The subsection titles “Traditional AHP Method”, “Monte Carlo” are misleading, as they refer to the methods rather than the results derived from them. Subsection titles in the Results section should describe the outputs or findings, not the methodological tools themselves. Revising the titles accordingly will improve clarity and accurately reflect the content presented.

Results Section: The manuscript would benefit from a more comprehensive discussion that positions the findings within the international literature. A systematic comparison with studies using similar methodologies or investigating analogous contexts is necessary to demonstrate the distinctiveness, strengths, and weaknesses of the present approach. Such contextualization is necessary to demonstrate the study’s contribution, methodological distinctiveness, and any innovative elements.

Keywords? The manuscript does not include any keywords. Please provide an appropriate set of keywords to enhance the discoverability and indexing of the article.

Title: The title requires refinement. A strong academic title should: (i) clearly articulate the study’s main contribution; (ii) specify the geographical or thematic scope; (iii) highlight any methodological innovation; (iv) preferably adopt a two‑part structure for clarity; (v) avoid unnecessary or repetitive wording; etc.

References: The reference list is insufficient for an original research article. Typically, such manuscripts include approximately 30–50 references to adequately situate the study within the existing literature. The current list contains only 15 references, which does not provide adequate scholarly support for the research. Additionally, the journal follows a title‑style referencing system, and the references must be ordered alphabetically. The current ordering does not comply with this requirement and should be corrected. In general, please review your references carefully and ensure they are complete, accurate, and formatted according to the journal’s guidelines.

Conclusions Section: The study’s contributions and innovative elements remain insufficiently articulated, even within the Conclusions section. This section should clearly and explicitly highlight the novel aspects of the work and its added value to the existing body of knowledge. Furthermore, the directions for future research require greater specificity; they should outline concrete, actionable pathways rather than broad or generic statements. In addition, the manuscript would benefit from a transparent discussion of its limitations. Explicitly acknowledging these limitations will enhance the study’s credibility and provide readers with a more comprehensive understanding of the research.
Citation: https://doi.org/10.5194/wes-2025-188-RC3

Cristina Mata, Daniel Romero, and Niels Cornelis Adema

Viewed

Total article views: 332 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
258	52	22	332	21	22

HTML: 258
PDF: 52
XML: 22
Total: 332
BibTeX: 21
EndNote: 22

Views and downloads (calculated since 30 Oct 2025)

Month	HTML	PDF	XML	Total
Oct 2025	48	6	4	58
Nov 2025	95	16	7	118
Dec 2025	104	27	11	142
Jan 2026	11	3	0	14

Cumulative views and downloads (calculated since 30 Oct 2025)

Month	HTML	PDF	XML	Total
Oct 2025	48	6	4	58
Nov 2025	95	16	7	118
Dec 2025	104	27	11	142
Jan 2026	11	3	0	14

Viewed (geographical distribution)

Total article views: 320 (including HTML, PDF, and XML) Thereof 320 with geography defined and 0 with unknown origin.

Country	#	Views	%

Latest update: 06 Jan 2026

Short summary

This study examines how to choose the best locations for offshore wind farms. Researchers compared a traditional ranking method with a probability-based approach using computer simulations. The probability method better handles uncertainties by testing thousands of scenarios. Results showed this approach identifies suitable locations with greater confidence. This improved decision-making could help planners build environmentally sustainable and economically viable wind farms.


Total:	0
HTML:	0
PDF:	0
XML:	0