Rule-Based Enhanced Energy Management Scheme for Electric Vehicles Fast-Charging Workplace Using Battery Stacks and Solar Power

Abstract

Global cognizance for a green environment will embark on the rising demand for Plugin Electric vehicles (PEV) in the upcoming years. In this article, an online power management scheme (RTPMS) for a solar power battery-buffer grid-connected charging facility in an educational work area is developed. This algorithm contributes to lessening the overall diurnal price of recharging the PEVs, alleviating the influence of the charging station on the power grid, while participating in shaving the rise of the load curve. The understudy paper sheds the idea of quick charging of PEV integrated with energy storage stacks, photovoltaic systems and at the least demand with the power grid subject to constraints scenarios. Forecasting and statistical parameters are considered in the RTPMS to model the many uncertainties encompasses such as the photovoltaic power, PEVs arrival-departure period, and the energy present in their car batteries during their entrance at the station. The paper demonstrate maximum profit acquired by fast electric station besides lessening the overloading on the power grid with the execution of resilient RTPMS. The efficacy of the proposed supervisory rule-based method is stamped through assigning different assignments through MATLAB code editor.