Optimizing Wind Energy Technology Selection Under Uncertain and Incomplete Information Using Fuzzy Best Worst Method and Fuzzy Information Axiom

Abstract

Technology has a pivotal role in wind energy production, encompassing turbine design, control systems, and grid integration solutions. However, selecting the optimal technology investment presents a multifaceted challenge due to rapid industry evolution. Site-specific considerations, economic viability, reliability, durability, and integration with existing infrastructure all weigh heavily in the decision-making process. Environmental and societal impacts are rigorously supposed to be assessed for responsible energy production. A comprehensive approach, including a thorough evaluation of vendor and supplier capabilities, is deemed indispensable. To address these complexities, this study introduces an innovative approach to optimize wind turbine selection within established locations. The proposed methodology integrates the Fuzzy Best Worst Method (FBWM) and the Information Axiom, chosen for their adaptability in handling subjective expert responses. This combination aligns seamlessly with the nuanced nature of wind turbine technology assessment. The study offers a comprehensive review of relevant multi-criteria decision-making techniques, elaborates on the FBWM and Fuzzy Infor mation Axiom (FIA) approach, and presents apractical application. In the study, operational cost, maintenance cost, and power curve emerge as pivotal criteria. Ultimately, the study provides a robust framework for making informed and impactful technology investments in wind energy production.