Optimal Day-Ahead Transport and Charge Scheduling of Autonomous Electric Vehicle Fleet using Local Renewable Energy Generation

In recent years, there has been a surge of interest in shared autonomous electric vehicle (AEV) fleet systems, owing to their potential to reduce carbon emissions in the transportation sector and alleviate traffic congestion. Implementation of such systems presents an operational challenge for the existing electrical distribution grid due to the increased daily electric demand. Based on the classical Dial-ARide Problem, this paper proposes a framework from a transit service provider’s perspective to determine an optimal time to serve passenger requests and schedule the charging of an AEV fleet to minimize the charging costs while considering distribution grid constraints. The potential impact on charging costs of a local renewable energy source, which is embedded with public charging stations is analyzed. This optimization model is solved as a mixed-integer linear programming model (MILP) and obtained results with a French low-voltage suburban distribution grid demonstrate the applicability of the proposed model.