Optimization of Wind Turbine Power Coefficient Parameters using Hybrid Technique

被引：0

作者：

Rajakumar S. ^{[1
]}

Ravindran D. ^{[2
]}

机构：

[1] Department of Mechanical Engineering, Anna University of Technology, Tirunelveli, 627007, Tamil Nadu

[2] Department of Mechanical Engineering, National Engineering College, Kovilpatti, 628503, Tamil Nadu

来源：

Journal of The Institution of Engineers (India): Series C | 2012年 / 93卷 / 02期

关键词：

Artificial neural network; Genetic algorithm; Optimization; Power coefficient; Wind turbine;

D O I：

10.1007/s40032-012-0019-z

中图分类号：

学科分类号：

摘要：

Wind turbine is a device that is used for converting kinetic energy from the wind into mechanical energy. The efficiency of wind turbine mainly depends on power coefficient of wind turbine. Maximization of power coefficient is one of the important factors for increasing efficiency in wind turbine. The maximized power coefficient enables high power production at low costs. The power coefficient is maximized by selecting suitable the values of design parameters. In this work a hybrid technique is proposed to optimize the power coefficient parameters of wind turbine blades. The proposed technique is a combination of genetic algorithm and artificial neural network (ANN). Genetic Algorithm is one of the evolutionary programs and it is used to optimize the parameters of power coefficient. The proposed genetic algorithm performs optimization in two phases. Initially, power coefficient parameters are determined for the respective angle of attack and optimized by using genetic algorithm phase I. ANN is used to generate the training data of design parameters of wind turbine. From the training data set, the best power coefficient parameters are optimized by executing phase II of the genetic algorithm. The proposed method is evaluated and its performances are identified. © 2012, The Institution of Engineers (India).

引用

页码：141 / 149

页数：8

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