Grid Integration of Wind Farms by UPQC Based Neural Network

In this paper a novel control strategy presented to grid integration of wind farms using squirrel-cage induction generators (SCIG) by unified power quality conditioner (UPQC) based on adaptive linear neural network (ADALINE). The interaction between wind generators and grid cause increasing short circuit urrent level , instability, fault ride-through (FRT) or low voltage ride-through (LVRT) capability problem during fault condition. A new control strategy established for generation reference signals of series converter (SERC) and shunt converter (SHUC) considering Spanish grid code. This control scheme can fulfill compensate all types of voltage sags. Also the proposed controller supplements the phase jump recovery. This control scheme deal with a dual control of real and reactive power transaction between wind energy conversion system based SCIG (WECS-SCIG) and grid. As well as, ADALINE makes a fast dynamic response to any changes in speed, voltage and other important parameters of SCIG facing of short circuit and instability of wind farm. The simulation results can verified the high efficiency of proposed NN-UPQC strategy to enhancement of power quality of wind farms

Keywords:

UPQC , Wind Farm , LVRT , Neural Network , MO-ADALINE , Grid Code