Zoning for exploration of wind energy in Ceará with the use of geographic information systems (GIS) and multicriteria analysis

• Autor(a) principal: Vale, Daniela Cadore
• Data de Publicação: 2020
• Outros Autores: Silva, Renato Sipelli, Rocha, Erika da Justa Teixeira, Alexandria, Auzuir Ripardo de
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/3809
• topic: Parque eólicos; Energias renovables; Potencial para la instalación de parques eólicos; Jerarquía analítica de procesos.; Parques eólicos; Energias renováveis; Potencial para instalação de parques eólicos; Processo de hierarquia analítica.; Windfarms; Renewable energy; Potential for windfarms installation; Process analytical hierarchy.

Wind energy has many advantages compared to traditional energies, from the ability to reduce the use of fossil fuels as well as the possibility of creating jobs in the areas where the projects are installed. The growth of this type of generation in Brazil has been driven by strong investor interest due to the characteristics of the country's winds, mainly from the Northeast. The winds are strong, stable and most of the time follow the same direction, characteristics that make windfarms in the Northeast region have high levels of capacity factor. By evaluating the data from the wind farms installed in Ceará, it can be observed that they present one of the best capacity factors in Brazil and have values above the world average. This indicates and reinforces the viability of implementing this type of energy generation in the area. It was verified that there are studies about wind conditions but there are no studies that correlate this information with the infrastructure conditions of the State. Therefore, the objective of the present work is to identify the appropriate areas for the allocation and use of wind energy in the State of Ceará through the integration of Geographic Information Systems (GIS) tools and multicriteria analysis for decision making.