1 research outputs found
Optimal Intelligent Control for Wind Turbulence Rejection in WECS Using ANNs and Genetic Fuzzy Approach
One of the disadvantages in Connection of wind energy conversion systems
(WECSs) to transmission networks is plentiful turbulence of wind speed.
Therefore effects of this problem must be controlled. Nowadays,
pitch-controlled WECSs are increasingly used for variable speed and pitch wind
turbines. Megawatt class wind turbines generally turn at variable speed in wind
farm. Thus turbine operation must be controlled in order to maximize the
conversion efficiency below rated power and reduce loading on the drive-train.
Due to random and non-linear nature of the wind turbulence and the ability of
Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) Artificial Neural
Networks (ANNs) in the modeling and control of this turbulence, in this study,
widespread changes of wind have been perused using MLP and RBF artificial NNs.
In addition in this study, a new genetic fuzzy system has been successfully
applied to identify disturbance wind in turbine input. Thus output power has
been regulated in optimal and nominal range by pitch angle regulation.
Consequently, our proposed approaches have regulated output aerodynamic power
and torque in the nominal rang.Comment: International journal of soft computing & soft engineering 201