Electric Vehicle Driver Response Evaluation in Multiaggregator Charging Management With EV Routing

Abstract

Electric vehicle (EV) charging scheduling is a necessary aspect for encouraging the everyday use of EVs. EV charging may be accommodated while benefiting one or more of the stakeholders, i.e., the grid, the aggregator (service provider), and/or the driver. This article presents a profit maximization multiaggregator scheduling scheme, which encapsulates the benefits of the consumer while maximizing the profits of the aggregator in noncollaborative and collaborative scheduling. The manuscript proposes novel fuzzy inference based EV driver response indicator (EVDRI) for gauging the response of the EV driver to a particular scheduling. The EVDRI is dependent on parameters of charging time and cost. Penalties for low satisfaction, along with penalties for any EVs that remain unscheduled are also included in the profit calculation. Furthermore, the potential impact of EV routing on aggregator profits and driver's satisfaction is also explored. Results indicate that the user response is positive (greater satisfaction) in case of collaborative scheduling and with optimum routing. The developed fuzzy EVDRI (F-EVDRI) provides good indication of the satisfaction level of the drivers. Impact of different parameters is also explored on the F-EVDRI wherein charging duration was found to be the parameter that impacts the EVDRI.