Analytical Size Estimation Methodologies for Electrified Transportation Fueling Infrastructures Using Public–Domain Market Data

The proliferation of electrified transportation systems is envisioned as a promising solution that could significantly contribute to the reduction of environmental pollution. Deployment of properly sized fueling stations is contemplated as a critical step to set the stage for the transportation electrification. While several optimization-based sizing models are presented in the literature, analytical models to estimate the size of electrified transportation infrastructures are missing from prior studies. Such analytical models can readily be developed at the backend of globally accessible websites or software applications since they do not require any optimization solver. In such a case, public-domain data, such as market prices or transportation demand, from everywhere around the world can be inputted to the model, and various sizing parameters related to each location are returned to the user. To that end, this paper presents new analytical methodologies for the application to the size estimation of electric and hydrogen-based fueling stations as the two major foundations for electrified transportation. The ratings of various components are expressed in terms of the system operation percentage using the proposed formulation, and the desired ratings are selected at which the net profit reaches to the maximum point. Historical public-domain data from real-world systems are utilized for numerical evaluation of the proposed formulation. In addition, the estimation error of the proposed model is analyzed and compared with artificial intelligence-based models for validation purposes.