Electric Vehicle Fast Charging Station Research Articles

Efficient solution approaches for locating electric vehicle fast charging stations under driving range uncertainty

We seek to determine the best locations for electric vehicle fast charging stations under driving range uncertainty. Two stochastic programming based models have been recently proposed to handle the resulting stochastic flow refueling location problem: a first one maximizing the expected flow coverage of the network, a second one based on joint chance constraints. However, significant computational difficulties were encountered while solving large-size instances. We thus propose two efficient solution approaches for this problem. The first one is based on a new location-allocation type model for this problem and results in a MILP formulation, while the second one is a tabu search heuristic. Our numerical experiments show that when using the proposed MILP formulation, the computation time needed to provide guaranteed optimal solutions is significantly reduced as compared to the one needed when using the previously published MILP formulation. Moreover, our results also show that the tabu search method consistently provides good quality solutions within short computation times.

Design of an electric vehicle fast-charging station with integration of renewable energy and storage systems

The development of electric vehicles (EVs) depends on several factors: the EV’s acquisition price, autonomy, the charging process and the charging infrastructure. This paper is focused on the last factor: the design of an EV fast-charging station. In order to improve the profitability of the fast-charging stations and to decrease the high energy demanded from the grid, the station includes renewable generation (wind and photovoltaic) and a storage system. Unlike other papers, this one uses a detailed model of the charging process that considers the arrival time and state of charge of electric vehicles. First, the Monte Carlo method is used to model the EV demand and the renewable generation. Later, a genetic algorithm (GA) optimizes the installation and operation of the EV fast-charging station. It finds the optimal solution that maximizes the profit measured by its net present value (NPV). Several cases are studied to analyse the influence of renewable energies and storage systems. The obtained results show that a mix of renewable energies and storage systems attains the best cost efficient solution.

Hierarchical power control strategy on small-scale electric vehicle fast charging station

In order to reduce the environmental hazards from non-renewable energy consumption and promote sustainable social development, renewable electric energy has been developed vigorously in countries around the world as the best strategical choice of cleaner energy development. Especially in transportation sector, large quantities of electric vehicles (EVs) are considered the most promising alternative to alleviate the problems of energy crisis, environment pollution and climate warming. However, with the rapid growth of EVs, much more small-scale fast charging stations (FCSs) have limited distribution capacity to satisfy every charging demand simultaneously and are under big pressure to ensure good service capability. Based on current conditions, this paper proposes a hierarchical power control strategy (HPCS) that considers EVs demand, FCS service capability, and FCS daily load fluctuation as a whole with weighted dynamic priority (WDP) and fluctuation smoothing index (FSI). The assumed system model is based on each EV's unique demand and FCS constraints. The simulation results show that the optimal WDP is sufficiently elastic to satisfy EV's demand urgency and fast charging station operator (FCSO)'s income simultaneously. Moreover, FSI is illustrated concretely to decrease daily load fluctuation and peak load value, which is useful to reduce overall power loss. As a result, the HPCS can be realized on a 32-bit processor platform in a FCS to gain an optimal balance between EVs demands and FCSO's profits.

Hierarchical optimal planning approach for plug‐in electric vehicle fast charging stations based on temporal‐SoC charging demand characterisation

Fast charging stations are critical infrastructures to enable a high penetration level of plug-in electric vehicles (PEVs) into future distribution networks. The fast charging stations need to be carefully planned to meet the PEV charging demand as well as reduce costs. This study addresses this technical challenge and proposes a hierarchical planning solution for both sitting and sizing of PEV fast charging stations based on a temporal-SoC (state-of-charge) characterisation and modelling of PEV fast charging demand. The optimal sitting of fast charging stations is firstly determined to ensure minimising the total number of stations and meeting the PEV fast charging demand considering the constraints of transportation networks and the expected PEV remaining mileage. Then the sizing (number of chargers and waiting spaces) of fast charging station is optimised by the use of M/M/s/N queuing model, so as to maximise the expected profit of the operator. The proposed solution is evaluated through a set of case studies for a range of scenarios, and numerical simulation results have confirmed the effectiveness of the proposed solution.

A charging pricing strategy of electric vehicle fast charging stations for the voltage control of electricity distribution networks

With the increasing number of electric vehicles (EVs), the EV fast charging load will significantly affect the voltage quality of electricity distribution networks. On the other hand, EVs have potentials to change the choices of charging locations due to the incentives from the variations of charging prices, which can be considered as a flexible response resource for electricity distribution networks. In this paper, a charging pricing strategy of EV fast charging stations (FCSs) was developed to determine the pricing scheme for the voltage control of electricity distribution networks, which consisted of a simulation model of EV mobility and a double-layer optimization model. Considering the travel characteristics of users, the simulation model of EV mobility was developed to accurately determine the fast charging demand. Taking the total income of FCSs and the users’ response to the pricing scheme into account, the double-layer optimization model was developed to optimize the charging pricing scheme and minimize the total voltage magnitude deviation of distribution networks. A test case was used to verify the proposed strategy. The results show that the spatial distribution of EV fast charging loads was reallocated by the proposed charging pricing scheme. It can also be seen that the proposed strategy can make full use of the response capacity from EVs to improve the voltage profiles without decreasing the income of the FCSs.

Electric Vehicle Fast-Charging Station Unified Modeling and Stability Analysis in the dq Frame

The electric vehicle fast-charging station is an important guarantee for the popularity of electric vehicle. As the fast-charging piles are voltage source converters, stability issues will occur in the grid-connected fast-charging station. Since the dynamic input admittance of the fast-charging pile and the dynamic output impedance play an important role in the interaction system stability, the station and grid interaction system is regarded as load-side and source-side sub-systems to build the dynamic impedance model. The dynamic input admittance in matrix form is derived from the fast-charging pile current control loop considering the influence of the LC filter. Similarly, the dynamic output impedance can be obtained similarly by considering the regional power grid capacity, transformer capacity, and feed line length. On this basis, a modified forbidden region-based stability criterion is used for the fast-charging station stability analysis. The frequency-domain case studies and time-domain simulations are presented next to show the influence of factors from both the power grid side and fast-charging pile side. The simulation results validated the effectiveness of the dq frame impedance model and the stability analysis method.

Electric vehicle fast charging station usage and power requirements

The anticipated usage and power requirements of future fast charging points is critical information for organisations planning the rollout of electric vehicle charging infrastructure. This paper presents two novel methods to assist in such planning, one method to predict the time of day fast charging points will be used and one method to estimate the fast charging power required to satisfy electric vehicle driver requirements. The methods involve taking data from instrumented gasoline vehicles and assuming that all the journeys are instead conducted using full battery electric vehicles. The methods can be applied to any dataset of gasoline vehicle journeys that have key data, namely journey start and end times and distance travelled. The methods are demonstrated using a dataset from the United States. It is predicted that for long distance journeys, when the electric vehicle range is exceeded, fast charging point usage will peak in the evening, with 45% of daily fast charges occurring between the hours of 3pm and 7pm. It is also estimated that to satisfy 80% of long distance journeys a charging rate of 20 miles/minute is required, equating to a charging power of 400 kW assuming the electric vehicles achieve a driving efficiency of 3 miles/kWh.

Fast-charging to a partial state of charge in lithium-ion batteries: A comparative ageing study

At electric vehicle fast-charging stations, it is generally recommended to avoid charging beyond ∼80% State-of-Charge (SOC) since topping-off to full capacity disproportionately increases the charging time. This necessitates studying its long-term impact compared to slower rate charging to full capacity typical of home or residential charging. Here we present the long-term ageing effects on commercial 18650 NMC-LMO/graphite cell cycled between 2.6–4.2V at three different charging protocols: 1.5 C-rate fast-partial charging (to 82.5% SOC), 0.5 C-rate slow standard charging without or with a constant-voltage step (to 93% or 100% SOC). Quantitative discharge-curve and postmortem analyses are used to evaluate ageing. The results show that ageing rate increases in the order: fast-partial charging < standard charging < standard charging with constant-voltage period, indicating that higher SOC-range near full capacity is more detrimental to battery life than fast-charging. The capacity fade is totally dominated by cyclable-lithium loss. The ∼8% NMC-LMO active material loss has negligible impact on the cell capacity fade due to the electrodes excess material in the fresh cell and its moderate loss rate with ageing compared to the cyclable-lithium. Similar ageing modes in terms of capacity fade and impedance rise are found irrespective of the charging protocol.

A Second-Order Cone Programming Model for Planning PEV Fast-Charging Stations

This paper studies siting and sizing of plug-in electric vehicle (PEV) fast-charging stations on coupled transportation and power networks. We develop a closed-form service rate model of highway PEV charging stations' service abilities, which considers heterogeneous PEV driving ranges and charging demands.We utilize a modified capacitated flow refueling location model (CFRLM) to explicitly capture time-varying PEV charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM to enhance model accuracy and computational efficiency.We then propose a stochastic mixed-integer second order cone programming (SOCP) model for PEV fast-charging station planning. The model considers the transportation network constraints of CFRLM and the power network constraints with AC power flow. Numerical experiments are conducted to illustrate the effectiveness of the proposed method.

Heuristic Planning Method of EV Fast Charging Station on a Freeway Considering the Power Flow Constraints of the Distribution Network

A heuristic planning method of electric vehicle (EV) fast charging station on a freeway considering the power flow constraints of the distribution network was proposed. Firstly, the spatial and temporal distribution of EV charging points was determined based on a spatial-temporal model (STM); then the charging demand of candidate fast charging stations was determined based on the Shared Nearest Neighbor (SNN) Clustering algorithm; finally, a heuristic principle was proposed to meet the power flow constraints of the distribution network and the final planning scheme (the location and capacity) was determined. A typical test system was used to verify the validity of the planning method.

Planning of Fast EV Charging Stations on a Round Freeway

A novel planning method of fast electric vehicle (EV) charging stations on a round freeway was developed, considering the spatial and temporal transportation behaviors. A spatial and temporal model based on the origin-destination (OD) analysis was developed to obtain all the EV charging points (the location on the round freeway that an EV needs recharging due to the low battery capacity). Based on a shared nearest neighbor (SNN) clustering algorithm, a location determination model was developed to obtain the specific locations for EV charging stations with their service EV clusters. A capacity determination model based on the queuing theory was proposed to determine the capacity of each EV charging station. The round-island freeway in Hainan Island of China was employed as a test system to illustrate the planning method. Simulation results show that the developed planning method can not only accurately determine the most suitable locations for EV fast charging stations considering the travelling convenience of EV users, but also minimize the sum of waiting cost and charger cost.

Control and operation of power sources in a medium-voltage direct-current microgrid for an electric vehicle fast charging station with a photovoltaic and a battery energy storage system

Although electric vehicles (EVs) are experiencing a considerable upsurge, the technology associated with them is still under development. This study focused on the control and operation of a medium-voltage direct-current (MVDC) microgrid with an innovative decentralized control system, which was used as a fast charging station (FCS) for EVs. The FCS was composed of a photovoltaic (PV) system, a Li-ion battery energy storage system (BESS), two 48 kW fast charging units for EVs, and a connection to the local grid. With this configuration and thanks to its decentralized control, the FCS was able to work as a stand-alone system most of the time though with occasional grid support. This paper presents a new decentralized energy management system (EMS) with two options to control the power sources of the FCS. The choice of the power source depends on the MVDC bus voltage, the state-of-charge (SOC) of the BESS, and the control option of the EMS. This control was tested by simulating the FCS, when connected to several EVs and under different sun irradiance conditions. Simulation results showed that the FCS operated smoothly and effectively, which confirms the feasibility of using this technology in EVs.

Assessment of the use of vanadium redox flow batteries for energy storage and fast charging of electric vehicles in gas stations

A network of conveniently located fast charging stations is one of the possibilities to facilitate the adoption of Electric Vehicles (EVs). This paper assesses the use of fast charging stations for EVs in conjunction with VRFBs (Vanadium Redox Flow Batteries). These batteries are charged during low electricity demand periods and then supply electricity for the fast charging of EVs during day, thus implementing a power peak shaving process. Flow batteries have unique characteristics which make them especially attractive when compared with conventional batteries, such as their ability to decouple rated power from rated capacity, as well as their greater design flexibility and nearly unlimited life. Moreover, their liquid nature allows their installation inside deactivated underground gas tanks located at gas stations, enabling a smooth transition of gas stations' business model towards the emerging electric mobility paradigm. A project of a VRFB system to fast charge EVs taking advantage of existing gas stations infrastructures is presented. An energy and cost analysis of this concept is performed, which shows that, for the conditions tested, the project is technologically and economically viable, although being highly sensitive to the investment costs and to the electricity market conditions.

A Control Algorithm for Electric Vehicle Fast Charging Stations Equipped With Flywheel Energy Storage Systems

This paper proposes a control strategy for plug-in electric vehicle (PEV) fast charging station (FCS) equipped with a flywheel energy storage system (FESS). The main role of the FESS is not to compromise the predefined charging profile of the PEV battery during the provision of a hysteresis-type active power ancillary service to the overhead power system. In that sense, when the active power is not being extracted from the grid, an FESS provides the power required to sustain the continuous charging process of the PEV battery. A key characteristic of the whole control system is that it is able to work without any digital communication between the grid-tied and FESS converters. Detailed system modeling and dynamics analysis of the controller are carried out for the different operating modes of the FCS system. A lab-scale prototype was built to validate the proposal. The presented experimental results proved the high accuracy of the theoretical analysis.

Reactive power control for an energy storage system: A real implementation in a Micro-Grid

In last years, the power system operators are tackling many challenges for the renewable energies integration on the grid. Further, the expected increase of electrical demand due to the uncoordinated contemporary charging of a huge number of Electric Vehicles (EVs) can create chaotic phenomena with a negative impact especially on the distribution network. Help can be offered by the deployment of Smart Grid technologies, such as Smart Metering Systems (SMSs), Information and Communications Technology (ICT) and Energy Storage Systems (ESSs). In particular, in Micro-Grids, Battery ESSs (BESSs) can play a fundamental role and can become fundamental for the integration of EV fast charging stations and distributed generations. In this case the storage can have peak shaving, load shifting and power quality functions. The ESSs can provide ancillary services also on the grid as the reactive control to adjust the power factor. In the present paper, a monitoring control program to manage the reactive power of a real ESS in a Micro-Grid has been implemented. The system is a prototype, designed, implemented and now available at ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development) labs. A wide experimental activity has been performed on the prototype system in order to test this functionality for the integration in a bigger Smart Grid available at the same ENEA labs including the Micro-grid. The integration has been possible, thanks to the free ICT protocols used by the researchers and which are described here. The results of the experimental tests show that the system can have good performance to adjust the power factor in respect to the main distribution grid and an EV charging station.

Multi-Objective Optimization of Electric Vehicle Fast Charging Stations with SPEA-II

Abstract During the past two decades, electrification of the transportation sector is gradually becoming a global trend due to the environmental benefits from electric vehicle (EV). Although EV charging post plays as a primary energy supply, public EV Fast Charging Station (FCS) is definitely an important backup energy supply system to the EV customers in case of urgent need. Based on current existing FCS system and the prediction of the EV charging need in the future, this paper proposes a multi-objective EV FCS layout re-planning optimization problem, which simultaneously takes the economic issue and the customers’ satisfaction into consideration. To solve the problem a popular multi-objective evolutionary algorithm, Strengthen Pareto Evolutionary Algorithm-II (SPEA-II), is employed in this study. Numerical case studies shows that the SPEA-II can successfully address the balance between different objectives during the re-planning FCS procedure by contrast to that of a single-objective optimization method (Improved Genetic Algorithm).

Development of Electric Vehicle Charging Corridor for South Carolina

ABSTRACT We apply a flow-based location model, called Multipath Refueling Location Model (MPRLM), to develop an electric vehicle (EV) public charging infrastructure network for enabling long-haul inter-city EV trips. The model considers multiple deviation paths between every origin-destination (O-D) pairs and relaxes the commonly adopted assumption that travelers only take a shortest path between O-D pairs. This model is a mixed-integer linear program, which is intrinsically difficult to solve. With greedy-adding based heuristics, the MPRLM is applied to optimally deploy EV fast charging stations along major highway corridors in South Carolina. Compared to engineering methods, the optimization model reduces the capital cost of establishing a fast charging network by two thirds. We also explore the interplay between the spatial distributions of cities, vehicle range, and routing deviation tolerance as well as their impacts on the locational strategies.

EV fast charging stations and energy storage technologies: A real implementation in the smart micro grid paradigm

In the last years, electric vehicles (EVs) are getting significant consideration as an environmental-sustainable and cost-effective alternative over conventional vehicles with internal combustion engines (ICEs), for the mitigation of the dependence from fossil fuels and for reduction of Green-House Gasses (GHGs) emission. However, many challenges are still ongoing to their large scale implementation. Among them, the negative impact on the electrical grid operation in case of an uncoordinated contemporary charging of a huge number of EVs. In the recent literature different solutions are proposed for handling the peak demand of EVs and the related problems. One answer is offered by the implementation of EV charging strategies, through aggregation agents, for containing the impact on the grid, guaranteeing the quality of the service. The implementation of a real charging strategy is strictly related to a deployment of smart-grid technologies, such as smart meters, Information and Communication Technologies (ICTs) and energy storage systems (ESSs). In particular ESSs are playing a fundamental role in the general smart grid paradigm, and can become fundamental for the integration in the new power systems of EV fast charging stations of the last generation: in this case the storage can have peak shaving and power quality functions and also to make the charge time shorter. In the present paper, an overview on the different types of EVs charging stations, in reference to the present international European standards, and on the storage technologies for the integration of EV charging stations in smart grid is reported. Then a real implementation of EVs fast charging station equipped with an ESS is deeply described. The system is a prototype, designed, implemented and now available at ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development) labs. A wide experimental activity has been performed on the prototype system in order to test its functionalities in the integration in a smart grid available at the same ENEA lab, including a smart metering system. The integration has been possible thanks to the use of a customized communication protocol, developed by the researchers and here described. The results of the experimental tests show that the system has a good performance in the implementation of peak shaving functions, in respect of the main distribution grid, making the prototype like a network nearly zero-impact system.

Bi-directional electric vehicle fast charging station with novel reactive power compensation for voltage regulation

Excessive carbon emissions from the current transportation sector has encouraged the growth of electric vehicles. Despite the environmental and economical benefits electric vehicles charging will introduce negative impacts on the existing network operation. This paper examines the voltage impact due to electric vehicle fast charging in low voltage distribution network during the peak load condition. Simulation results show that fast charging of only six electric vehicles have driven the network to go beyond the safe operational voltage level. Therefore, a bi-directional DC fast charging station with novel control topology is proposed to solve the voltage drop problem. The switching of power converter modules of DC fast charging station are controlled to fast charge the electric vehicles with new constant current/reduced constant current approach. The control topology maintains the DC-link voltage at 800V and provides reactive power compensation to regulate the network bus voltage at the steady-state voltage or rated voltage (one per unit). The reactive power compensation is realized by simple direct-voltage control, which is capable of supplying sufficient reactive power to grid in situations where the electric vehicle is charging or electric vehicle is not receiving charges.

Impact of electric vehicle fast charging on power system voltage stability

The electric vehicle (EV) brings a sustainable future for the next generation of automobiles. Market penetration of EV has been increasing drastically in the recent past. However, EV integration into power grids adds more challenges for power system engineers worldwide. It is essential to evaluate potential grid impacts due to EV integration to guarantee consistent grid operation. Even though a number of power system impact studies have been performed covering several aspects of the problem, the impact on voltage stability has remained almost unattended. The lack of accurate load models to represent EV load for system stability studies is found to be a major gap. Hence, a static load model is developed in this study as an essential base for realistic stability studies. A specific EV load behavior which has not yet been revealed in the literature is identified during the study. Subsequently, the influence of EV load on power system voltage stability is evaluated under different scenarios. The study has discovered that integration of EV fast charging stations may significantly reduce the steady state voltage stability of the power grid.