An Enhanced MPPT Control for PV with Grid Connected EV Charging System

Abstract

Due to the rising demand for energy, there is a need to find a different source to address the impending energy crisis, which is most likely accomplished by using gridsynchronized electric vehicles (EV). The integration of multiple EV with grid affects the entire Power system causing imbalance in supply-demand, Voltage and frequency. To minimize these issues we add solar Power in this integration. One of the smart grid's technological developments that enables the transfer of energy between EVs and the grid is called vehicle to grid (V2G) technology. In order to lessen the strain on the grid's voltage and current and to speed up charging, this project uses a Landsman converter along with the Radial Basis Function Neural Network (RBFNN) MPPT technique. A fast convergent approach is Maximum Power Point Tracking (MPPT) using RBFNN.  In this work, the Voltage is either boosted or decreased using a Landsman converter. Using a PI controller, the converter's gating circuit is created. If the EV is at rest for long time, the battery gets discharged through the Boost mode and when the EV needs charging, the battery gets charged by the grid through the Buck mode. The excess DC Voltage from PV/ DC Voltage from EV is fed to grid through single phase Voltage source inverter (VSI) and vice versa. The projected plan is authenticated through reproduction using MATLAB. The comparison of the converters shows the greater efficiency of Landsman Converter as 92.3%.