"An ANN Based Frequency Response of VSWT with Distinct Control Strategies"


Chakka Jashmitha, Dr. K. Jithendra Gowd, Assistant Professor


This paper presents an approach involving variable speed wind turbine (VSWT) generators in the frequency control to consider the healthy increase of wind power production. The popular approaches that promote the frequency regulation of the WTGs are droop control and a virtual inertia control. On the other side, the inappropriate and intermittent flow of the wind exacerbates the application of these techniques effects stability of the wind turbine, which will cause a breach of the permitted reserve power and the minimum rotor speed of the turbine. Beside these methods a dynamic de-loading technique is considered so that as frequency changes, the wind turbine operating curve is altered using tip-speed ratio control. This provides transient response and steady-state sharing of power within the stability criteria. In addition to this a dynamic inertial response is proposed in order to provide inertial weighting gain in order that the response to rotor speed which reflects the amount of kinetic energy in a rotating mass. Artificial Neural Network, a component of artificial intelligence functions as human brain. A feed forward neural network is considered. Furthermore, existence of a fair power margin is a necessary requirement for continuous power sharing. The poor performance of PI controller can be overcome by considering artificial neural network and the entire work is performed in MATLAB/SIMULINK.