Diminishing Energy Consumption Cost and Optimal Energy Management of Photovoltaic Aided Electric Vehicle (PV-EV) By GFO-VITG Approach

This paper proposes a hybrid GFO-VITG approach for the energy management system (EMS) of the photovoltaic (PV) aided electric vehicle (EV). The proposed system is the combination of Ground water flow optimization (GFO) and Vascular Invasive Tumor Growth optimization algorithm (VITG), and hence, it is known as the GFO-VITG method. The main aim of this paper is optimal energy management for diminishing the system cost with power loss of the system. Additionally, based on the enhancement of EMS for optimal control of PV-aided EVCS, the GFO-VITG method is proposed. The GFO-VITG model enhances the vehicle-to-grid (V2G) method for producing complementary functions and takes dynamic cost of electricity. The proposed technique is stimulated under MATLAB/Simulink, and efficiency is compared with that of existing techniques. Consequently, the output shows that the GFO-VITG model is efficient for getting better solution through minimal computation and also lessens the difficulty of requisite algorithms. The simulation outcomes demonstrate that the energy management system can decrease the overall expenses more than 55% in summer, 29% in winter related to typical charging policy, when ensuring the fulfillment index of electric vehicle-charging demands without knowing the departure time of electric vehicles. In the number of iterations of 100, 250, 500, and 1000, the simulation times of the proposed technique are 14.8 seconds, 29.2 seconds, 69.9 seconds, and 77.1 seconds.