Turbine blade material selection using fuzzy analytic network process

In the present era, maximum amount of energy consumed is produced by non-renewable sources, which are constrained in their amounts. Eventually, these limited resources would be depleted and new energy sources would have to replace the fossil fuels. Wind energy and oscillating water column wave energy can help alleviate this dependency on non-renewable sources. This kind of sustainable energy is generated by wind turbines and wave energy extraction impulse turbines. The efficiency of a turbine greatly depends on material, shape and angle of its blade. Given the intricacy of turbine blade material selection problem with various alternative choices and numerous criteria having interactions and dependencies, this paper applies a fuzzy analytic network process (FANP)-based approach to select the most appropriate materials for wind energy and wave energy extraction impulse turbine blades. The applicability of FANP method is demonstrated with two examples to prove its adaptability to solve industrial decision-making problems.

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