Modeling and optimization of power coefficient using 2K factorial methodology

The main objective of this paper is to model the power coefficient in order to optimize the design of a horizontal axis wind turbine rotor to ensure the optimum aerodynamic power production, based on statistical Design of Experiment (DOE). Sophisticated aerodynamics of the wind turbine and blade geometry is discussed and used to generate the optimum chord and twist distribution of the rotating blades. The dependent variables of the power coefficient are found as the pitch angle, number of blades, and chord and twist distribution. A nonlinear model of the power coefficient based on the dependent variable and their interactions is investigated with the adoption in a 2^K factorial design. The significance of the variables as well as the power coefficient model is ensured by the analysis of variance table and scree plots. Interaction plots revealed that the high value of pitch angle and low value of number of blades has the dominant contribution on the power coefficient, while chord and twist distribution is less significant. The results obtained can be used for feasibility study, optimization, and control of the wind turbine control strategy is feasible and results are verified through simulation.