Network Of Fast Charging Stations Research Articles

Locating electric vehicle charging stations under uncertain battery energy status and power consumption

Fostering the adoption of electric vehicles (EVs) by private drivers requires the development of a wide network of fast charging stations in which drivers traveling long-distance trips will be able to easily recharge their battery within a few minutes. However, due to their high installation costs, the number of stations that can actually be deployed with the available investment budget is strongly limited. It is thus necessary to carefully choose their location so that the charging demand satisfaction is maximized. This leads to the formulation of a facility location problem known as the flow refueling location problem (FRLP). In this paper, we study the FRLP and seek to take into account uncertainties on the vehicle driving range in the problem modeling. We propose to relax several modeling assumptions previously used in the literature to handle this problem. First, we allow the power consumption on a road segment to depend on the crossing direction. Second, we take into account uncertainties related to the energy available in the battery after recharging at a station as well as uncertainties related to the power consumption on each portion of the road network. Finally, we consider statistical dependencies between the stochastic power consumption on different arcs of the network.We focus on the chance-constrained flow refueling location model, which seeks to maximize the number of drivers for whom the probability of running out of fuel when carrying out their trip is below a certain threshold. To solve the resulting stochastic optimization problem, we propose to use a solution approach based on a partial sample approximation of the stochastic parameters and compare its performance with the one of a previously published approach based on Bonferroni’s inequality. We carry out numerical experiments on a set of medium-size randomly generated and real life instances. Our results show that the proposed partial sample approximation approach outperforms the Bonferroni approach in terms of solution quality and gives station locations which provide a significantly improved demand coverage in practice.

Performance Analysis of Fast Charging Stations for G2V and V2G Micro-grid Systems

In order to promote the switching from ICE vehicles to more environment friendly EVs, a network of fast charging stations is necessary. A lot of research is being conducted in this area in order to design efficient models of chargers along with developing new technologies to mitigate the current problems encountered such as the charging time, incapability to charge multiple vehicles at a time etc. This paper presents the different ways of classifying EV battery charging technologies and also a topological survey of different charging stations proposed in the literature. A three-phase bidirectional charger and a modular fast charger proposed in the literature are also presented along with their modelling, control strategies and simulation results to analyse their respective performances.

Unsplittable Load Balancing in a Network of Charging Stations Under QoS Guarantees

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 non-uniform spatial distribution of EVs that induces uneven power demand at each charging facility, and aims to: (i) avoid straining grid resources by offering price incentives so that customers accept being routed to less busy stations, (ii) maximize total revenue by serving more customers with the same amount of grid resources, and (iii) 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.

Unified Active Filter and Energy Storage System for an MW Electric Vehicle Charging Station

A network of fast-charging stations is of great importance for widespread adoption of electric vehicles (EV) if the so-called range anxiety issue is to be resolved. As with petrol stations, we expect that multiple chargers will be co-located to form charging stations. This layout allows for the fast-charging station to make use of a common rectifier stage and several dc/dc stages to charge multiple EVs. This paper builds on our previous work where we proposed a novel dc-side filter for the 12-pulse rectifier and investigated the power profile for a MW fast-charging station. In this paper, we propose a novel control approach for the filter, based on the virtual resistor injection, which results in further reduction in dc ripple, ac-side harmonics, and filter VA ratings. We also demonstrate that, with the proposed topology and control, the filter stage can be used as dc-side energy storage system.

Electric Power Allocation in a Network of Fast Charging Stations

In order to increase the penetration of electric vehicles, a network of fast charging stations that can provide drivers with a certain level of quality of service (QoS) is needed. However, given the strain that such a network can exert on the power grid, and the mobility of loads represented by electric vehicles, operating it efficiently is a challenging and complex problem. In this paper, we examine a network of charging stations equipped with an energy storage device and propose a scheme that allocates power to them from the grid, as well as routes customers. We examine three scenarios, gradually increasing their complexity. In the first one, all stations have identical charging capabilities and energy storage devices, draw constant power from the grid and no routing decisions of customers are considered. It represents the current state of affairs and serves as a baseline for evaluating the performance of the proposed scheme. In the second scenario, power to the stations is allocated in an optimal manner from the grid and in addition a certain percentage of customers can be routed to nearby stations. In the final scenario, optimal allocation of both power from the grid and customers to stations is considered. The three scenarios are evaluated using real traffic traces corresponding to weekday rush hour from a large metropolitan area in the US. The results indicate that the proposed scheme offers substantial improvements of performance compared to the current mode of operation; namely, more customers can be served with the same amount of power, thus enabling the station operators to increase their profitability. Further, the scheme provides guarantees to customers in terms of the probability of being blocked (and hence not served) by the closest charging station to their location. Overall, the paper addresses key issues related to the efficient operation, both from the perspective of the power grid and the drivers satisfaction, of a network of charging stations.