The operation of the power grid is becoming more stressed, due to the addition of new large loads represented by electric vehicles (EVs) and a more intermittent supply due to the incorporation of renewable sources. As a consequence, the coordination and control of projected EV demand in a network of fast charging stations becomes a critical and challenging problem. In this paper, we introduce a game theoretic based decentralized control mechanism to alleviate negative impacts from the EV demand. The proposed mechanism takes into consideration the nonuniform spatial distribution of EVs that induces uneven power demand at each charging facility, and aims to: 1) avoid straining grid resources by offering price incentives, so that customers accept being routed to less busy stations; 2) maximize total revenue by serving more customers with the same amount of grid resources; and 3) provide charging service to customers with a certain level of quality-of-service (QoS), the latter defined as the long term customer blocking probability. We examine three scenarios of increased complexity that gradually approximate real world settings. The obtained results show that the proposed framework leads to substantial performance improvements in terms of the aforementioned goals when compared to current state of affairs.
Related work on charging station design can be classified into two categories. The first category includes queueing based models, where the goal is to evaluate the charging station performances with respect to long-term statistical metrics e.g., blocking probability, waiting time, etc. For example, the work in @cite_1 proposes an M M s queueing based mathematical model for EV demand for fast charging stations located near highway exits. On the other hand, the design perspective of the second category is related to power engineering. The authors of @cite_11 propose a charging station architecture with a DC bus system, and similar to our model they employ a local energy storage unit to alleviate the stress in the power grid. Related literature is presented in Fig. .
@cite_1 @cite_11
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This paper presents a spatial and temporal model of electric vehicle charging demand for a rapid charging station located near a highway exit. Most previous studies have assumed a fixed charging location and fixed charging time during the off-peak hours for anticipating electric vehicle charging demand. Some other studies have based on limited charging scenarios at typical locations instead of a mathematical model. Therefore, from a distribution system perspective, electric vehicle charging demand is still unidentified quantity which may vary by space and time. In this context, this study proposes a mathematical model of electric vehicle charging demand for a rapid charging station. The mathematical model is based on the fluid dynamic traffic model and the M M s queueing theory. Firstly, the arrival rate of discharged vehicles at a charging station is predicted by the fluid dynamic model. Then, charging demand is forecasted by the M M s queueing theory with the arrival rate of discharged vehicles. This mathematical model of charging demand may allow grid's distribution planners to anticipate a charging demand profile at a charging station. A numerical example shows that the proposed model is able to capture the spatial and temporal dynamics of charging demand in a highway charging station. In this paper the optimum design of a fast-charging station for PHEVs and EVs is proposed to minimize the strain on the power grid while supplying the vehicles with the required power. By studying the power demand of the charging station, a conclusion is reached that the size of the grid tie can be reduced substantially by sizing the grid tie for the average rather than the peak power demand. Therefore the charging station architecture with a single AC DC conversion and a DC distribution to DC DC charging units is proposed. An energy storage system is connected to the DC bus to supply power when the demand exceeds the average that can be provided from the grid. Various topologies for both the AC DC and DC DC conversion are studied to find the optimum design for this application.