Optimal control pulses establishment for the power flow management in hybrid renewable energy sources using BCRFA controller

Abstract

These works are introduced to avoid electrical problems in literary works. An intelligent hybrid control technique for optimal power flow management (OPFM) in grid-associated hybrid renewable energy sources (HRES) with energy storage is proposed in this dissertation. For stabilizing power fluctuations, the intelligent controller is proposed. The proposed intelligent controller is joint performance of Big Bang-Big Crunch (BB-BC) and random forest algorithm known as BCRFA controller. In the proposed controller, the BB-BC method reproduces the evaluation process to establish the exact control signals (ECS) system depending on power variations with source, load side. With this appropriate control, HRES can significantly improve the dynamic safety of the power system. Finally, the proposed system is executed on MATLAB/Simulink work site. The efficiency of the BCRFA system compares the existing system. The result of the comparison reveals that HRES power flow using the proposed system is direct efficiently compared with the existing systems. The efficiency of the various techniques and the proposed technique has been analysed in three case studies. In Case 1, the PV, wind, battery and FC gives the efficiency using proposed technique is 95.3617%, 99.1235%, 98.1264% and 99.4677%. In Case 2, the photovoltaic (PV), wind, battery and fuel cell (FC) give the efficiency using the proposed technique is 91.4365%, 93.6537%, 98.5151% and 97.1562%. In Case 3, the PV, wind, battery and FC give the efficiency using the proposed technique is 92.5479%, 91.2369%, 97.5631% and 90.1245%.