Admission and scheduling mechanism for electric vehicle charging with renewable energy

Integrating renewable energy for Electric Vehicles (EVs) charging scheduling is more challenging than using grid power, due to the time-varying and unpredictable nature of renewable energy generation. Most of the existing works mainly focus on a deterministic setting where the scheduling problem can be solved using various congestion management approaches. In this paper, we develop a stochastic solar generation model and a performance index (the Figure of Merit) to measure the charging station's utility as well as EVs' charging requirements, taking account of the effect of solar energy prediction errors. We further propose a two-stage process (first admission control and then charging scheduling) to find the best solution to the EV charging problem. The results show that the proposed two-stage admission and scheduling mechanism outperforms the First In First Out (FIFO) scheme in terms of reducing delay time and increasing revenue, so that the charging station performs better. The proposed mechanism can also adapt well to uncertain solar generation by finding the optimal trade-off between accepting EVs and missing charging deadlines.