With the rapid growth of electric vehicle (EV) ownership, attentions have been paid to the foundation of EVs, the electric vehicle supply equipment (EVSE). Different approaches of effort, among which battery swapping and fast charging are the two most well studied, have been made to solve the tradeoff problem between the battery charging speed and battery lifetime. There has been considerable debate over development strategy between charging and battery swapping. In passenger vehicles, the EV charging mode seems to dominate. But, does it mean that the battery swap mode is a dead-end? The answer should be “No”. There are use cases showing that battery swap can have great potentials for some particular uses, such as taxis and buses. This paper uses Monte Carlo simulations of vehicle behaviors to compare the service capacities and earnings of EV charging and battery swapping for both taxi and bus fleets. Stochastic models of taxis, buses, charging stations (CSs) and battery swapping systems are set up. Subsequently, service capacities of the EVSE are compared. The impact of factors on the service capacity, such as the size of the vehicle's battery, vehicle's moving speed, the power of the CS, and the price of the swapping service is investigated. Finally, possible reasons of today's less prevalence of battery swapping stations are discussed. The results of the analysis, which can be helpful to policymakers and industry investors, show that with same service capacity, an EV battery swapping station could provide significantly more financial and social benefits for the vehicle operators and EVSE service providers than that of an EV CS.

Energy demand and supply vary from area to area, where an unbalanced load may occur and endanger the system security constraints and cause significant differences in the locational marginal price (LMP) in the power system. With the increasing proportion of local renewable energy (RE) sources in microgrids that are connected to the power grid and the growing number of electric vehicle (EV) charging loads, the imbalance will be further magnified. In this article, we first model the EV charging network as a cyber–physical system (CPS) that is coupled with both the transportation networks and the smart grids. Then, we propose an EV charging station recommendation algorithm. With a proper charging scheduling algorithm deployed, the synergy between the transportation network and the smart grid can be created. The EV charging activity will no longer be a burden for power grids, but a load-balancing tool that can transfer energy between the unbalanced distribution grids. The proposed system model is validated via simulations. The results show that the proposed algorithms can optimize the EV charging behaviors, reduce charging costs, and effectively balance the regional load profiles of the grids.

Inductive-power-transfer (IPT) converters should desirably achieve nearly zero reactive circulating power, soft switching of power devices and load-independent constant output voltage or current with optimized transfer efficiency and lowest component ratings. However, the load-independent output characteristic is dependent on IPT transformer parameters and their compensation. The space-constrained IPT transformer restricts the design of the low-order resonant circuit compensated IPT converter, making the IPT converter hard to optimize. This paper will analyze conditions under which any extra design freedom can be allowed for a double-sided LC compensation circuit in order to achieve load-independent output and zero reactive power input. A detailed analysis is given for the double-sided LC compensation achieving zero reactive power input and constant current output, without being constrained by the transformer parameters. Design conditions of the compensation circuit parameters for achieving these two properties are derived. A complementary LC-CC compensated IPT converter is further proposed to extend the output current amplitude limitation of the double-sided LC compensated IPT converter. Finally, prototypes of the IPT converters are constructed to verify the design flexibility of the proposed double-sided LC compensation circuit for achieving the multiple objectives.

In recent years, the frequent occurrences of large-scale blackouts highlight the necessity of enhancing the robustness of power grids. In this paper, based on the cascading failure model which considers both the network topology and electrical characteristics running in power grids, we study how the topological metrics affect the robustness of power grids. The topological metrics considered include both the connectivity of the network and the distribution of generators. We compare the results in typical complex network models and IEEE 118-bus network. Moreover, by using the simulated annealing method, we find the optimal network topology to achieve the best network robustness, and compare the topological metrics before and after the optimization to verify our findings. The results show that in order to enhance the robustness of power grids, it is better to make the network sparsely connected, and place the generators as hubs and decentralize these generators.

The rising proportion of renewable energy (RE) penetration with high variability introduces immense pressure on the stability of power grids. At the same time, a rapid increase in electric vehicle (EV) penetration level leads to uncoordinated charging loads, which poses significant challenges to operators. By properly guiding and scheduling the charging behaviors, EV may no longer be a burden, but a valuable asset to mitigate the RE integration problem. In this paper, we first propose a prioritization ranking algorithm of EV drivers based on their driving and charging behaviors, and then we propose a blockchainbased EV incentive system to maximize the utilization of RE. The proposed system is secure, anonymous, and decentralized. By incorporating the utilities, EV drivers, EV charging service providers, and RE providers into the proposed incentive system, this work provides a plan to guide the EV users to charge at the desired time frames with higher RE generation. The market mechanism of the incentive system is discussed. The effectiveness of the system is verified by simulation.