Impacts of electric vehicle charging station with the integration of renewable energy with grid connected system: a hybrid technique

This manuscript proposes a new hybrid system to analyze the impact of the electric-vehicle-charging-station with the combination of renewable energy and grid-connected system. The proposed method is the implementation of Forensic-Based Investigation (FBI) and Artificial Transgender Longicorn Algorithm (ATLA) called FBI–ATLA method. The objective of the proposed system is to provide the computational complexity, reduce the cost, improve efficiency and enhance the network power. Here, two sorts of charging stations are deemed regarding with power supply capabilities. While type 1 charging stations utilize the power grid, renewable energy sources and vehicle-to-grid technology, type 2 charging stations have swappable batteries. The charging station may be met by four dissimilar power sources: (i) power grid (PG); (ii) batteries stored in charging stations; (iii) renewable energy sources (e.g., solar-energy); (iv) the energy discharged from electric vehicles (EV) to grid via vehicle-to-grid (V2G) connection. The implementation of the FBI–ATLA introduced through the MATLAB platform, and the performance of proposed method is compared with existing methods. In ANN, PSO, GA and proposed technique, the values of effectiveness during 100, 200, 500 and 1000 is 99.0037%, 99.2356%, 99.8363% and 99.9373%. Finally, the result shows that the proposed system is proficient than other existing techniques.