AN OPTIMIZATION FRAMEWORK FOR ELECTRIC VEHICLES CHARGING STATIONS ALLOCATION USING DEMAND BASED ON CITY TRAFFIC COUNT

Abstract

Selecting good locations for the placement of Electric Vehicle (EV) public charging stations is important for the uptake of EVs. As EVs are considered to have lower green gas emissions to internal combustion engines, the uptake of EVs is considered better for the environment. Many factors are involved in the location-allocation problem for EV public charging stations, such as understanding demand, needs assessment, identifying possible locations, and selecting a facility location optimization model. This study provides a framework to improve demand identification and estimation accuracy and reliability by using traffic data and VISUM traffic simulation software. The case study of Doha is presented by applying three facility location optimization models. The set covering model results provide well-distributed stations, while the maximum coverage model locates stations in a concentrated area.