Year: 2025
Type: article
Abstract: This study focuses on wind energy potential assessment using the Fuzzy Cognitive Mapping (FCM) method. Given the limitations of fossil resources and their negative environmental impacts, the use of renewable energy sources, especially wind energy, has become an essential necessity. This research emphasizes the assessment of wind energy potential through an analytical fuzzy model that can effectively manage the complexities of energy systems. In this study, 13 key concepts were identified, including economic growth, energy prices, return on investment, investment, demand management, and other important economic, social, and environmental factors. Data were collected through structured interviews with industry experts and the analysis of standard questionnaires, and were subsequently analyzed using the FCM model. The results of this analysis show that factors such as investment levels in wind projects, economic sustainability, and increased energy supply security have significant impacts on the development of wind energy. Additionally, the results highlight the importance of using various scenarios to predict future developments and evaluate strategic decisions in the field of renewable energy. Finally, two scenarios for wind energy development in the country were presented, specifically focusing on investment and supply security. This research not only provides comprehensive analysis of wind energy potential but also offers a conceptual framework for planning and decision-making in the development of renewable energy.
Authors: Ali Naeini, Hamideh Heydari, Sadaf Mahjoubi
Institution: Iran University of Science and Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4412378159