Power Quality Enhancement of UPQC Connected WECS using FFA with RNN

In this paper a design of combined operation of Unified Power Quality Conditioner (UPQC) and Wind Energy Conversion System (WECS) is presented to alleviate the power quality problems in distribution system. The integration of wind power into an electric grid encounters the Power Quality (PQ) problems and which will be minimized. The control strategy of UPQC is analyzed with adaptive technique, which is used for Firefly Algorithm (FFA) and Recurrent Neural Network (RNN). To optimize the control pulses to UPQC, FFA is used and the RNN is used to train the optimization parameter. The optimal control pulses are generated by the series and shunt Active Power Filters (APF) based on the source side and load side parameters. This approach is competent to inject the active power to grid in addition to its ability to improve the PQ in distribution system. The performance of the proposed FFA based UPQC system is validated through simulations using MAT LAB/SIMULINK and compared with the existing techniques such as ANFIS support UPQC and GA support UPQC.