Optimal power control in Renewable Energy sources using Intelligence algorithm

Abstract

An intelligent, Adaptive Neuro-Fuzzy Inference System (ANFIS) based Xilinx Power Management system is proposed for the Hybrid renewable energy sources (HRES). The Xilinx Power Management generator block set (ANFIS-XL-PMS) controller is implemented for the purpose to control and avoid the non-linear nature opted in the HRES power system. Solar (PV), Wind Energy (WE), and Fuel cell (FC) are the primary power sources of the system, and a battery storage system (BES) is used as a backup. A comprehensive power management strategy is intended for the proposed system to control the flow of power between the various energy sources and the system's storage device. The simulation model for the HRES is elegantly designed using the MATLAB/Simulink platform and the Switching patterns are generated using the XLPMS controller. The system performance and output responses of the SMC-XL-ANFIS controller have been verified by carrying out the simulation studies and compared with the existing controller like Sliding Mode Controller (SMC-XL-PMS), and Artificial Neutral Network (ANN-XL-PMS). Simulation results show good performance in terms of voltage and current transient, settling time, load power efficiency, and power quality Also a Prototype model with a PIC microcontroller is designed and the output responses are analyzed.