Power Quality Enhancement using TSA with RNN for 2 kV Grid Connected Hybrid System
Renewable energy becomes turns into a key supporter of our cutting-edge society, however their combination to control power grid poses critical specialized difficulties.The major power quality concerns are voltage sag, swell, fluctuations, distortion and interruption which are caused by non controllable variability of renewable energy resources.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 decreasing the problems caused renewable energy sources. The proposed methodology has been tested for D-STATCOM under various conditions, simulation study can be used to develop control strategy of non conventional energy system to mitigate PQ issues. The proposed system will be implemented in MALAB/Simulink platform. In order to evaluate the effectiveness of the proposed method, this is compared with the existing methods, such as PSO-RNN and CSO-RNN technique and techniques.