Software-Defined Electric Vehicle (EV)-to-EV Charging Framework With Mobile Aggregator

Even though electric vehicle (EV)-to-EV charging has the potential to overcome the inconvenience due to a shortage of electric charging stations, its distributed and dynamic nature makes it difficult to match charging EV (C-EV) and discharging EV (D-EV). In this article, we propose a software-defined EV-to-EV charging framework (SD-E2EC) with mobile aggregators, in which, on the basis of the collected information in a global view, the charging controller determines the charging location, monetary cost for C-EV, and monetary reward for D-EV. To maximize the revenue of the operator of SD-E2EC, we formulate a joint optimization problem of determining the appropriate charging location, monetary cost, and reward. As a practical solution to the problem, we propose a highly acceptable pair decision (HAPD) algorithm. Extensive simulation results demonstrate that HAPD can achieve up to 129% revenue (compared to the conventional method using fixed aggregators) while maintaining the waiting time below a certain level.

Automated summary

In this article, a software-defined EV-to-EV charging framework with mobile aggregators is proposed to solve the matching problem of charging and discharging EVs. The charging controller determines the charging location, monetary cost, and reward based on the collected information in a global view, aiming at maximizing the revenue of the operator. A highly acceptable pair decision algorithm is proposed as a practical solution, which achieves up to 129% revenue growth while maintaining the waiting time below a certain level according to extensive simulation results.