Enhancing the Performance of Hybrid Grid Connected System with Bi-Directional Energy Management using FPGA Based Predictive Energy Optimization Algorithm with Data Monitoring

The grid connected hybrid system power flow management control is introduced in this system and it is based on the power conversion is used to the bidirectional converters is based on field programmable gate array (FPGA) controller. The proposed FPGA based Predictive Energy Optimization Algorithm (PEOA) technique is used to give the proper switching pulse to the converter is minimize the fault and increase the stability of this grid connected hybrid system. Therefore, the reliability and effectiveness of the system can be enhanced by these control strategies; Power fluctuations are essentially constant. The proposed grid connected hybrid system is analysis with help of the IOT is a process that is utilized to verify data using the Stochastic Linear Data Monitoring (RLDM TM) method, which enables data to be taken from the bus system to the decision-making process required. Through this integrated control strategy, proper power interactions can be achieved in different sub-phases, supporting the power fluctuations and further stability of other sub-phases. The development of a hybrid system proposed by MPPT with a stand-alone DC-DC converter and a voltage-regulated inverter was developed and simulated in the MATLAB environment.