Photovoltaic mobile charging station for green infrastructure: A data-driven case study

Abstract

In this study, it is aimed to establish photovoltaic-based charging stations for electric micro mobility vehicles (EMMCS). A data-driven optimization approach is presented for the design and site selection solution of EMMCS. This approach consists of a three-step solution methodology. First, 18 criteria affecting the site selection of micro mobility vehicles were determined. The Analytical Hierarchy Process (AHP) was used to calculate the priority values of these criteria, and a new formulation was created by analysing them with six different machine-learning algorithms to increase consistency. Secondly, spatial analyses were conducted via Geographic Information Systems (GIS) to identify the most suitable areas for EMMCS, and a suitability map was obtained. Thirdly, the station assignment process analysis was carried out with Mixed-Integer Programming (MIP). It was recommended to establish 75 stations. The sample design of EMMCS was made based on photovoltaic (PV), and the Alternative ranking technique based on adaptive standardized intervals (ARTASI) approach was adopted to assess the performance of the alternatives. It is observed that EMMCS-8, 9, 31, and 25 have the highest construction priority. All these processes were implemented as a case study and four distinct service classes were defined based on the real-world scenario. To the best of the authors' knowledge, this is the first study in which both the site selection and siting problems of PV-based stations are solved together.