MODEL PREDICTIVE CONTROL OF BIDIRECTIONAL AC-DC CONVERTER FOR ENERGY STORAGE SYSTEM

Abstract

In this paper, the Algorithm of Model Predictive Control for controlling bi-directional AC to DC converters and their optimization in Energy Systems is proposed to enhance the efficiency and transfer of power in Energy Systems and 3 Phase AC Voltage Source. The interruptible power supply and its requirements are handled in an efficient manner with increased performance of Energy and Storage Systems with the help of proposed Algorithm. The distribution sector of Renewable Energy will be optimized with the help of this advancement because it allows increasing the system efficiencies affiliated with the energy and storage systems. The goal is to implement the proposed Algorithm of Model Predictive Control for prediction of variables by carefully analyzing the cost functions that are used in the system and the checking the discreetness of converter in its specific behavior in the system. This scheme considers that the proposed algorithm will allow better power flow in a bidirectional manner for increasing the response of the system and making it more efficient for facing the change in variables. MATLAB/Simulation will be made for verification of Protypes that are made for 3kw systems. Low-cost functions are preferred for the future firing values and states of converter for necessary enhancements in the existing system. The research will focus on obtaining the optimized values of PF that is closest to the ideal values i.e., 1. The Harmonic Distortion of the System will also be maintained, and the overall number of ripples will also be lessened to achieve better stability in the system. In the cost function optimization, I have optimized the cost function which means that the new proposed model will have low cost, this is called as low-cost model which will be optimized after comparing the error values. The lower the error value will be the lower will be the cost function. At last, the overall increase in efficiency with the proposed technique will be compared with the existing models as to highlight the importance of Model Predictive Control Algorithm and the necessary advancements that the research allowed to come up with a more optimized scheme.