Multicriteria Decision-Making Evaluation of Blade Element Momentum Theory Algorithms for Optimal Design of Small-Scale HAWT Blades

Abstract

Several blade element momentum theory (BEMT) algorithms have been employed for the design and analysis of wind turbine rotors with varying effectiveness in optimizing the design, weight, performance, and cost. However, the optimal selection of BEMT algorithm for small wind turbines (SWTs) remains an area of ongoing research. This study presents a comprehensive comparison of five selected BEMT algorithms, evaluating their influence on blade geometry and performance across tip-speed ratios (TSRs) ranging from 0.01 to 20. A multicriteria decision-making (MCDM) approach was employed to assess the algorithms based on criteria including power output, power coefficient (Cp), thrust coefficient (CT), manufacturability (Mnf), blade weight, and cost of material (CM). The results demonstrate that both the TSR and the chosen BEMT algorithms significantly impact wind turbine performance. The maximum Cp of 0.569 was achieved at a TSR of 5.5 using the Jha algorithm. The MCDM analysis revealed that power output, Cp, and CT were assigned weights of 0.25, 0.22, and 0.16, respectively, while Mnf, weight, and CM received weights of 0.13, 0.12, and 0.12. This indicated that power output and Cp are the more desirable criteria for selecting suitable BEMT algorithms for SWTs. Among the tested algorithms, the Jha and Manwel methods exhibited superior performance across all TSRs. The MCDM analysis further identified the Jha and Ingram algorithms as the top-ranked options, with appraisal scores of 3.27 and 2.63, respectively. These findings provide valuable insights for the design and optimization of SWT blades, potentially leading to enhanced efficiency and performance.