A global evaluation model applied to wind power plant site selection. (15th April 2023) - Asadi, Meysam; Ramezanzade, Mohsen; Pourhossein, Kazem
Highlights: Presents a global decision-making model based on six criteria to evaluate site quality. In the model, a combination of DOE and MCDM techniques was used to site selection. Approximately 1300 km 2, of Iran was suitable for the harvesting of wind energy. The AHP - FFD technique was used to develop the wind siting model. Data collection was performed based on GIS. Abstract: Site selection is one of the most critical steps in designing wind farms due to the heterogeneous distribution of wind energy on the Earth's surface. Additionally, the wind power site selection problem is a complex process since it must be evaluated from multiple perspectives, including techno-economic, social, and environmental factors. In this regard, the current study proposes a new approach which combines Full Factorial Design and Analytic Hierarchy Process. The output of this combination creates a global model for the site selection of wind power plants. Using this model, the decision-making space is transformed into the scoring space which makes the scores related to candidate sites more meaningful and understandable. Therefore, Iran is selected to find suitable wind sites to reveal the proposed model's capability. The results indicate that approximately 1300, 5109, and 16000 km 2 of the study area are considered outstanding, excellent, and good for the utilization of wind energy. Furthermore, a functional analysis was conducted to ensure that the proposed model was robust, and accordingly, the accuracy of siting some existing wind farm sites was also studied. Based on the calculated scores, some real sites, e.g., Khaf and Manjil, are suitable for wind power development. Some sites could be more carefully selected, like the Binaloud wind site; others have not been appropriately selected, such as the Soffeh, Shiraz, and Sarab sites. Finally, the model can be employed worldwide as a standard index for assessing wind farm site quality.