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Hamidreza Kaviani

Hamidreza Kaviani

Academic rank: Assistant Professor
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Education: PhD.
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Faculty: Technical Engineering
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Research

Title
Aerodynamic optimization of a 5 Megawatt wind turbine blade
Type
JournalPaper
Keywords
Aerodynamic Optimization, Megawatt Wind Turbine, Blade Element Momentum Theory (BEM), Genetic Algorithm (GA), Bezier Curve, Cost Of Energy (COE)
Year
2016
Journal energy equipment and systems
DOI
Researchers Hamidreza Kaviani

Abstract

Wind power has been widely considered in recent years as an available and a clean renewable energy source. The cost of wind energy production is currently the main issue, and increasing the size of wind turbines can reduce wind energy production costs. Hence, megawatt wind turbines are being rapidly developed in recent years. In this paper, an aerodynamic analysis of the NREL 5MW turbine is carried out using the modified blade element momentum theory (BEM). The genetic algorithm (GA) as an optimization method and the Bezier curve as a geometry parameterization technique are used to optimize the original design. The modified BEM results are compared with the NREL published results for verification. Cost of energy (COE) is considered an objective function, which is one of the most important and common choices of objective function for a megawatt wind turbine. Besides, the optimization variables involve chord and twist distributions variation along the blade span. The optimal blade shape is investigated for the minimum cost of energy with considered constant rotor diameter and airfoil profiles. Then the objective function is improved and a new optimum geometry is compared with the original geometry. Although the Annual Energy Production and rated power are reduced by 2% and 3% respectively, the net cost of wind energy production is decreased by 15%, showing the importance of such optimization studies.