Power Quality Enhancement in Grid Connected Hybrid PV/WT System using Tree Seed Algorithm with RNN

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G.Sreenivasan
K.Sudarsan

Abstract

Renewable energy becomes a key contributor to our modern society, but their integration to power grid poses significant technical challenges. The major power quality concerns are voltage sag, swell, fluctuations, distortion, and interruption which are caused by noncontrollable variability of renewable energy resources. In this paper, the D-STATCOM device is utilized for compensating power from PV and wind ranch. To control the power flow efficient control techniques are exercised. Recurrent Neural Network (RNN) with Tree Seed Algorithm (TSA) is employed as a control scheme. Distribution Static Synchronous Compensator (D-STATCOM) can be adopted for reactive power compensation and for reducing the problems caused by the system. The proposed system will be anlyzed in MATLAB/Simulink platform. In order to evaluate the effectiveness of the suggested method, this is compared with the existing methods, such as PSO-RNN and CSO-RNN techniques.

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How to Cite
G.Sreenivasan, & K.Sudarsan. (2020). Power Quality Enhancement in Grid Connected Hybrid PV/WT System using Tree Seed Algorithm with RNN. Helix, 10(02), 211-218. Retrieved from http://helixscientific.pub/index.php/Home/article/view/133
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