Power Quality Enhancement Using Artificial Neural Network-Proportional Integral Controller and Fuzzy Granular Controller for DSTATCOM Integrated with Renewable Energy and Battery Storage System

In the power distribution network, spread of power electronic devices and nonlinear loads has been exacerbate the power quality (PQ) difficulties.D-STATCOMs plays a key role to serve as an active power filter which are commonly used to address these issues.The performance of the distribution network is increased by incorporating the renewable energy sources (RES) such as PMSG-based wind energy conversion system (WECS) with DC capacitor across the D-STATCOM.During the PQ disturbances without controller the THD of source and load currents are 7.46% and 15.32%, by using the PI controller THD's are reduced to 3.02% and 4.01%.The proposed controllers reduced THD with ANN-PI source and load current THD are 2.99% and 3.62% and Fuzzy granular controller are 1.56% and 2.37%.Whereas on the other side, the DC-link voltage with PI controller introduces more fluctuations and reduced voltage level with settling time about 0.1secs, by using ANN-PI voltage fluctuations get reduced and maintain constant voltage, in addition to that in fuzzy granular the magnitude of dc link voltage increased by 10% and settling time got reduced about 0.05secs.The nonsinusoidal source current and load current are tranformed to sinusiodal by the ANN-PI and Fuzzy granular controller and also the power factor is improved nearly to unity.The proposed controllers are designed and tested by using MATLAB/Simulink.