Development of an GA-RBF based Model for Penetration of Electric Vehicles and its Projections

-Electric vehicle technology is seen as crucial by some countries in their efforts to reduce greenhouse gas emissions and lessen their reliance on oil imports for transportation. This is why many car manufacturers are putting serious resources into exploring and perfecting electric vehicles (EVs). As the technology behind electric vehicles develops and as government incentives are put into place, they will progressively be adopted by the transportation sector. Unforeseen effects on the power grid, especially the existing distribution infrastructure, could result from the widespread use of electric vehicles. The first three stages of the suggested approach are data preprocessing, feature extraction, and model training. Normalization of the data is a part of preprocessing. Sparse principal component analysis is used to extract features. After feature extraction, the models are trained using GA-RBF. When compared to GA and RBF, the two most common options, the proposed technique performs better.