**7. Conclusions**

This study investigated an MCDM system for wind farm site selection in Semnan, Iran. The SATBA meteorological station data were employed to classify the area in terms of wind speed. Topological, ecological, and structural restrictions were specified based on the local and constitutional rules and regulations. These restrictions divided the province area into two suitable and unsuitable areas. According to the opinion of the experts, seven main criteria were selected and pairwise compared. The parameters such as distance from power stations, power lines, and distance from communication routes are included in the main criteria to consider the economic factors. Afterward, an AHP method was applied to categorize the suitable area into nine classes to represent the wind farm potential in various province locations. The results show that an MCDM based on AHP is useful for splitting a complicated problem into smaller parts and solving them effectively and does not need a genuine dataset.

This study shows that the most favorable areas of the province to extract wind energy can be used for practical goals. According to the results, almost 36.2% of the total study area is restricted due to being adjacent to environmentally restricted areas, populated areas, and communication routes. Most of the best areas with the highest wind farm potential are located in the northern part of the province. Although these areas have a lower wind speed, the lower distance to the electrical facilities and communication routes could reduce the initial and maintenance costs and make the project more justifiable. The final categorized map shows that the Aradan and Sorkhe regions, located in the province's northwest part, have the highest potential for wind farms. In contrast, the south and southeast region, which mainly consists of desert lands and unurbanized areas, has the least wind farm potential due to the greater distance from communication routes and power grid facilities. The final map is categorized into nine classes. The results represent almost 17.5% of the total study area placed in the three classes with the highest wind farm potential. At the same time, about 21.68% of the study area locates in the three classes with the slightest wind farm potential.

Other renewable resources, including solar energy, offshore wind farms, and geothermal plants, depend on ecological, economic, and environmental factors. In future papers, the MCDM systems could facilitate the site-selection problems for other renewable resources. Additionally, various methods, including fuzzy AHP, Entropy, Dematel, and Swara, can be used in site-selection problems and the results can be compared.

**Author Contributions:** Conceptualization, H.Y.; Formal analysis, H.Y., S.G.M. and M.M.; Investigation, M.M.; Methodology, S.G.M.; Resources, S.G.M.; Software, S.G.M.; Supervision, H.Y.; Validation, H.Y.; Visualization, M.M.; Writing—original draft, S.G.M. and M.M.; Writing—review & editing, H.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** This Study Do not involve any human or animals.

**Informed Consent Statement:** This Study Do not involve any human.

**Data Availability Statement:** The data that support the findings of this study are openly available.

**Conflicts of Interest:** All authors certify that they have no affiliation with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.
