Design Optimization of a Utility Scale Wind Turbine Blade Using a Genetic Algorithm

Driven by the increasing fossil fuel prices, global warming and climatic change, the world is currently witnessing an increasing development in renewable energy technologies, particularly those of wind energy. As such, engineers around the world are trying to optimize the design of wind turbines to maximize the captured energy while simultaneously minimizing the cost. This work aims to develop a mathematical tool to be used to compare different wind turbine designs and hence to reach the ultimate goal of an optimized wind turbine rotor designed specifically to operate in the Saharan regions of North Africa and the Middle East. As a case study, the main aerodynamic and structural parameters of the NREL 5MW virtual rotor have been optimized for the wind conditions prevalent at the Zaafarana site in Egypt. Specifically, the airfoil chord lengths and twist angles — smoothed using Bezier curves — as well as the layup sequence of the spar caps have been considered i n the optimization process which was carried out using a Genetic Algorithm (GA) developed i n MATLAB and coupled with NREL’s FAST Modularization Framework. The results showed that the NREL 5MW wind turbine design optimized for the site specific wind conditions of Zaafarana using airfoil families with low-sensitivity to dust accumulation, achieved a drop of 2.41% of the Levelized Cost of Energy of Energy (LCOE) over that of the baseline design. The developed turbine rotor design is tested for structural integrity commensurate with IEC standards.