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ANN Control for Improved Performance of Wind Energy System Connected to Grid
Brijesh Kumar, Kanwarjit Singh Sandhu, Rahul Sharma
DOI: 10.15598/aeee.v20i4.4474
Abstract
This paper proposes the novel control strategy to improve the power quality injection of wind energy system using Doubly Fed Induction Generator (DFIG) into the grid by implementing artificial neural network. The torque ripple produced in DFIG due to loading by grid tied inverter, which leads to poor power quality injection into the system. Also, these ripples transferred by DC link and causes heating losses and generator phase current distortion. Therefore, this paper modelled ANN based control scheme to reduce the torque ripple content and restrict the transfer of ripple by DC link to improve the outcome of wind energy system while operating in variable conditions. The DFIG system under studied are modelled and simulated in MATLAB SIMULINK to verify the improvement using proposed control strategy. The recent control technique is also simulated for reflecting the effectiveness in the proposed control method. The outcomes obtained are studied and analysed with the existing control scheme to highlight the improvement obtained by proposed control.
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