Analysis and selection of optimal sites for wind farms: case study, region north of Mexico
Main Article Content
Abstract
The analytic hierarchy analysis process allowed establishing a hierarchical model of a target function under a set of criteria aimed at choosing the best sites for the installation of wind farms in the north of Mexico. In this study, a large number of known and estimated criteria of diverse types (technical, economic, environmental, and social) were used, based on preliminary studies and information that allowed for the identification of the most relevant variables. The process simplifies a complex problem into simpler ones that can be analyzed independently, facilitating the efforts of decision takers since it allows envisaging the feasible alternatives. Once the most weighty and relevant variables were obtained, each variable was transformed into feasibility maps, and through the technique of map algebra coupled to a geographic information system, the sites were assessed in feasibility percentages in a general map fulfilling the set of imposed variables. The best scenarios for the location of a wind farm corresponded to the southern part of the state of Coahuila. The multicriteria analyses focused on decision-making within the planning process and characterization of feasible sites for a wind farm, are tools that optimize the selection of different variables, favoring the most relevant for the project by considering decision elements that are difficult to assess or quantify.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Once an article is accepted for publication, the author(s) agree that, from that date on, the owner of the copyright of their work(s) is Atmósfera.
Reproduction of the published articles (or sections thereof) for non-commercial purposes is permitted, as long as the source is provided and acknowledged.
Authors are free to upload their published manuscripts at any non-commercial open access repository.
PLUMX metrics