An Enhanced MPPT Approach Based on CUSA for Grid-Integrated Hybrid Electric Vehicle Charging Station

Abstract

Because of the fluctuating demands for electricity and the growing awareness of the need to protect the environment from global warming and the depletion of nonrenewable natural resources, battery-powered electric vehicles, or EVs, are being used in the transportation sector as an alternative to internal combustion engine vehicles. However, charging these EVs with conventional fossil fuels is neither economically sustainable nor structurally viable. Therefore, this manuscript proposes a renewable energy-powered EV charging station featuring a combination of solar energy, standby battery systems, sophisticated control techniques such as neural network-integrated grids, the enhanced Cuckoo Search Algorithm for Maximum Power Point Tracking, and the Proportional-Integral-Derivative controller. This idea beats current methods and presents a viable way to drive the EV revolution while lessening environmental effects. It maximizes energy management and guarantees a steady power supply even in erratic weather. Grid integration ensures the consistency of power supplies at charging terminals. When compared to other algorithms that have been investigated in the literature, the designed algorithm exhibits excellent performance. Grid integration, in addition to the standby battery, is essential in ensuring that the charging station has a constant power supply, even during unpredictable weather.