EV Charging Station Load Prediction in Coupled Urban Transportation and Distribution Networks

The increasingly large number of electric vehicles(EVs)has resulted in a growing concern for EV charging station load prediction for the purpose of comprehensively evaluating the influence of the charging load on distribution networks.To address this issue,an EV charging station load predictionmethod is proposed in coupled urban transportation and distribution networks.Firstly,a finer dynamic urban transportation network model is formulated considering both nodal and path resistance.Then,a finer EV power consumption model is proposed by considering the influence of traffic congestion and ambient temperature.Thirdly,the Monte Carlo method is applied to predict the distribution of EVcharging station load based on the proposed dynamic urban transportation network model and finer EV power consumption model.Moreover,a dynamic charging pricing scheme for EVs is devised based on the EV charging station load requirements and the maximum thresholds to ensure the security operation of distribution networks.Finally,the validity of the proposed dynamic urban transportation model was verified by accurately estimating five sets of test data on travel time by contrast with the BPR model.The five groups of travel time prediction results showed that the average absolute percentage errors could be improved from 32.87%to 37.21%compared to the BPR model.Additionally,the effectiveness of the proposed EV charging station load prediction method was demonstrated by four case studies in which the prediction of EV charging load was improved from27.2 to 31.49MWh by considering the influence of ambient temperature and speed on power energy consumption.

Study on site selection planning of urban electric vehicle charging station

The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric vehicles.Considering the costs of both operators and users,a site selection model for optimal layout planning of charging stations is constructed,and a queuing theory approach is used to determine the charging pile configuration to meet the charging demand in the planning area.To solve the difficulties of particle swarm global optimization search,the improved random drift particle swarm optimization(IRDPSO)and Voronoi diagram are used to jointly solve for the optimal layout of electric vehicles.The final arithmetic analysis verifies the feasibility and practicality of the model and algorithm,and the results show that the total social cost is minimized when the charging station is 9,the location of the charging station is close to the center of gravity and the layout is reasonable.

Strategic Placement of Charging Stations for Enhanced Electric Vehicle Adoption in San Diego, California

California mandated that 100% of vehicles sold must be electric by 2035. As electric vehicles (EVs) reach a higher penetration of the car sector, cities will need to provide publicly accessible charging stations to meet the charging demand of people who do not have access to a private charging spot like a personal garage. We have chosen to limit our scope to San Diego County due to its non-trivial size, well-defined shape, and dependence on personal vehicles;this project models 100% of current vehicles as electric, roughly 2.5 million. By planning for the future, our model becomes more useful as well as more equitable. We anticipate that our model will find locations that can service multiple population centers, while also maximizing distance to other stations. Sensitivity analysis and testing of our algorithms are conducted for Coronado Island, an island with 24,697 residents. Our formulation is then scaled to set the parameters for the whole county.

Considerations for Planning Charging Stations on College Campuses:A Focus on Safety and Economy

As intelligent networked cars become increasingly integrated into people’s lives,the charging infrastructure of new energy vehicles is becoming a significant factor in the development of the new energy vehicle market.In light of the rapid growth of this market,the problem of charging stations is gradually becoming apparent.This paper puts forward a charging station planning idea.Firstly,a forecast of the charging demand must be made.Subsequently,the economic viability,safety,ease of use for faculty and staff,and the rapid development of new automotive technology must be taken into account.Finally,research and analysis of the actual data must be carried out following the requirements of the different college campuses.

Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.

Energy-storage configuration for EV fast charging stations considering characteristics of charging load and wind-power fluctuation

Fast charging stations play an important role in the use of electric vehicles(EV)and significantly affect the distribution network owing to the fluctuation of their power.For exploiting the rapid adjustment feature of the energy-storage system(ESS),a configuration method of the ESS for EV fast charging stations is proposed in this paper,which considers the fluctuation of the wind power as well as the characteristics of the charging load.The configuration of the ESS can not only mitigate the effects of fast charging stations on the connected distribution network but also improve its economic efficiency.First,the scenario method is adopted to model the wind power in the distribution network,and according to the characteristics of the EV and the driving probability,the charging demand of each station is calculated.Then,considering factors such as the investment cost,maintenance cost,discharging benefit,and wind curtailment cost,the ESS configuration model of the distribution network is set up,which takes the optimal total costs of the ESS for EV fast charging stations within its lifecycle as an objective.Finally,General Algebraic Modelling System(GAMS)is used to linearize and solve the proposed model.A simulation on an improved IEEE-69 bus system verifies the feasibility and economic efficiency of the proposed model.

Analysis of positioning of wayside charging stations for hybrid locomotive consists in heavy haul train operations

Hybrid locomotive concepts have been considered as a step towards converting the railway industry into a green transport mode.One of the challenges in integrating a hybrid locomotive in the train consist is that the battery pack in the locomotive needs to be recharged during a long-haul trip which requires stopping of the train.A typical battery pack requires about 1 h to recharge which is unacceptable.With the improvement in the charging system,it is now possible that the same capacity battery pack could be recharged in 10–12 min which can be a competitive option for the railway companies.This paper proposes a method based on simulation to evaluate the positioning of charging stations on a train network.A typical example of a heavy haul train operation hauled by diesel-electric and hybrid locomotives is used to demonstrate the method by using simulation softwares.The result of the simulation study show that the method developed in this paper can be used to evaluate the state of charge(SoC)status of a hybrid locomotive along the track.It is also shown that the SoC status obtained by the simulation method can be further used to assess the positions of charging stations along the track at the design stage.

First large charging station with typical design put into operation

On March 31, in accordance with the typical design requirements of the State Grid, the f irst large electric vehicle (EV) charging station, built by the North China Grid,

Modeling and Experimental Verification of Electric Vehicles Off-Grid Photovoltaic Powered Charging Station

With the increasing development of EVs, the energy demand from theconventional utility grid increases in proportion. On the other hand, photovoltaic(PV) energy sources can overcome several problems when charging EVs from theutility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and alead-acid battery representing the energy storage system (ESS). A bidirectionalDC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed controllers achieve maximum power extraction from the PV and regulate the DC-linkvoltage. It also controls the voltage and current levels of both the ESS and the EVduring the charging/discharging process. The study has been applied to two caseswith different power levels. Analysis, simulation, and implementation of the proposed system are presented. A 120 W laboratory prototype is carried out to verifythe system performance, experimentally. Design guides for higher power levelsare proposed to help in choosing the proper parameters of the converters. Boththe simulation and experimental results are matched and verify the highperformance of the proposed system.

Operational program for proper capacity of electric bus charging station in Expo 2010

In the paper,an operational program of electric bus charging station is proposed,which is special for "The Construction Project for Expo 2010 Temporary Electric Bus Charging Station".Based on the quick-change mode,a vehicle operating schedule model has been established to meet the capacity of transport.Then,according to the quantity of passengers and utilization of batteries,a calculative method of parameters,such as the number of spare batteries and bus departure rules,has been provided.Furthermore,optimal simulation software designed for operating process of the charging station has been identified incorporating actual running data from electric buses and monitoring system of the charging station,and the rationality of the design is verified in the preliminary commissioning and the official operation.

The Bi-directional Three-Phase PWM Rectifier Inverter for Electric Vehicle Charging Station

Applications of electric vehicles need to build a large number of charging stations. The electric vehicle charging stations communicate with the grid. In V2G （vehicle to grid） mode, electric vehicles can be used as energy storage units and transfer power to the grid. The electric vehicles charge at night to reduce the cost and the grid load, simultaneously to fill the valley. When grid load increases, electric vehicles＇ batteries discharge to the grid to improve the stability of the grid. As distributed storage units, electric vehicles are important components of the smart grid. In this paper, the three-phase PWM （pulse width modulation） rectifier used for smart charging and discharging system of electric vehicles are analyzed and designed. This paper includes the principle of PWM rectifier-inverter and direct current control strategy. Also, the SVPWM （space vector pulse width modulation） and system design of three-phase PWM rectifiers are analyzed. A 10 kW prototype is developed. Simulation and experiment results show that the three-phase PWM rectifiers reach the unit power factor. From the experimental results, PWM rectifier implements the sinusoidal grid current and achieves the unit power factor.

Optimal Simultaneous Allocation of Electric Vehicle Charging Stations and Capacitors in Radial Distribution Network Considering Reliability

The popularity of electric vehicles(EVs)has sparked a greater awareness of carbon emissions and climate impact.Urban mobility expansion and EV adoption have led to an increased infrastructure for electric vehicle charging stations(EVCSs),impacting radial distribution networks(RDNs).To reduce the impact of voltage drop,the increased power loss(PL),lower system interruption costs,and proper allocation and positioning of the EVCSs and capacitors are necessary.This paper focuses on the allocation of EVCS and capacitor installations in RDN by maximizing net present value(NPV),considering the reduction in energy losses and interruption costs.As a part of the analysis considering reliability,several compensation coefficients are used to evaluate failure rates and pinpoint those that will improve NPV.To locate the best nodes for EVCSs and capacitors,the hybrid of grey wolf optimization(GWO)and particle swarm optimization(PSO)(HGWO_PSO)and the hybrid of PSO and Cuckoo search(CS)(HPSO_CS)algorithms are proposed,forming a combination of GWO,PSO,and CS optimizations.The impact of EVCSs on NPV is also investigated in this paper.The effectiveness of the proposed optimization algorithms is validated on an IEEE 33-bus RDN.

Coordinated Planning for Fast Charging Stations and Distribution Networks Based on an Improved Flow Capture Location Model

The increasing penetration of plug-in electric vehi-cles(PEVs)should lead to a significant reduction in greenhouse gas emissions.Nevertheless,the development of PEVs is limited by the lack of charging facilities,which is constrained by the coupled transportation-distribution network.This paper presents a stochastic bi-level model for the optimal allocation of fast charging stations(FCSs)and distribution network expansion planning(DNEP).First,a sequential capacitated flow-capturing location-allocation model(SCFCLM)is proposed at the lower level to optimize the allocation of FCSs on the transportation network.Monte-Carlo simulation(MCS)is utilized to estimate daily charging load requirements.Then,we propose an economic model for DNEP at the upper level,and the chance constrained method is employed to relax power flow constraints to address the uncertainties of loads.Numerical experiments are conducted to illustrate the proposed planning method.The influences of the flow capturing sequence and relaxed confidence level on the PEV charging load,FCS planning strategies and DNEP schemes are analyzed.Index Terms-Coordinated planning,fast charging station,flow-capturing model,plug-in electric vehicle,stochastic bi-level model.

Optimal allocation of plug-in electric vehicle charging stations in the distribution network with distributed generation

The transportation sector is characterized by high emissions of greenhouse gases(GHG)into the atmosphere.Consequently,electric vehicles(EVs)have been proposed as a revolutionary solution to mitigate GHG emissions and the dependence on petroleum products,which are fast depleting.EVs are proliferating in many countries worldwide and the fast adoption of this technology is significantly dependent on the expansion of charging stations.This study proposes the use of the hybrid genetic algorithm and particle swarm optimization(GA-PSO)for the optimal allocation of plug-in EV charging stations(PEVCS)into the distribution network with distributed generation(DG)in high volumes and at selected buses.Photovoltaic(PV)systems with a power factor of 0.95 are used as DGs.The PVs are penetrated into the distribution network at 60%and six penetration cases are considered for the optimal placement of the PEVCSs.The optimization problem is formulated as a multi-objective problem minimizing the active and reactive power losses as well as the voltage deviation index.The IEEE 33 and 69 bus distribution networks are used as test networks.The simulation was performed using MATLAB and the results obtained validate the effectiveness of the hybrid GA-PSO.For example,the integration of PEVCSs results in the minimum bus voltage still within accepted margins.For the IEEE 69 bus network,the resulting minimum voltage is 0.973 p.u in case 1,0.982 p.u in case 2,0.96 p.u in case 3,0.961 p.u in case 4,0.954 p.u in case 5,and 0.965 p.u in case 6.EVs are a sustainable means of significantly mitigating emissions from the transportation sector and their utilization is essential as the worldwide concern of climate change and a carbon-free society intensifies.

Novel Planning Approach for Fast-charging Station in Integrated System

A promising way to boost popularity of electric vehicles(EVs)is to properly layout fast charging stations(FCSs)by jointly considering interactions among EV drivers,power systems and traffic network constraints.This paper proposes a novel sensitivity analysis-based FCS planning approach,which considers the voltage sensitivity of each sub-network in the distribution network and charging service availability for EV drivers in the transportation network.In addition,energy storage systems are optimally installed to provide voltage regulation service and enhance charging capacity.Simulation tests conducted on two distribution network and transportation network coupled systems validate the efficacy of the proposed approach.Moreover,comparison studies demonstrate the proposed approach outperforms a Voronoi graph and particle swarm optimization combined planning approach in terms of much higher computation efficiency.

Modelling of electric vehicle charging station and controlled by fuzzy logic controller with different modes of operation

The main objective of implementing charging stations is to ensure the good charging to theElectric Vehicles by using a solar PV array which is interconnected to the battery energy storagesystems. The charging station regulates the supply voltage and frequency without the use of amechanical speed governor. It also assures that energy gained from grid or by the DG set willhave the unity power factor (UPF) when the load is nonlinear. Besides this, the Point of CommonCoupling (PCC) voltage is synchronised with the grid/generator voltage in order to providecontinuous charging. In order to increase the optimal efficiency of the charging stations, thecharging stations will perform the active/reactive power transfer from the vehicle to grid, vehicleto house and vehicle to vehicle (V2V) power transfer. The operational experiment of the chargingstation is simulated and verified by using MATLAB/SIMULINK.

Steady-state Stability Assessment of AC-busbar Plug-in Electric Vehicle Charging Station with Photovoltaic

Although the deployment of alternating current(AC)-busbar plug-in electric vehicle(PEV)charging station with photovoltaic(PV)is a promising alternative,the interaction among subsystems always causes the instability problem.Meanwhile,the conventional generalized Nyquist criterion(GNC)is complex,and it is not suitable for the design of the AC system.Therefore,this paper proposes a modified infinityone-norm(MION)stability criterion based on the impedance method to assess the stability of the foresaid charging station.Firstly,the typical structure and operation modes of the charging station are studied.Furthermore,each subsystem impedance matrix is built by small-signal method,and the MION stability criterion based on impedance method is proposed to assess the charging station stability.Compared with the previous simplified stability criteria based on the norm,the proposed criterion has lower conservatism.Furthermore,the design regulation for the controller parameters is provided,and the stability recovery way is provided by connecting the doubly-fed line and energy storage equipment,which are selected based on intermediate variable,i.e.,short-circuit ratio(SCR).Finally,the effectiveness and conservatism of the proposed stability criterion are validated through simulation and experimental results.

Impact of EV load uncertainty on optimal planning for electric vehicle charging station

With the development of electric vehicles(EV), there is a huge demand for electric vehicle charging stations(EVCS). The utilization of renewable energy sources(RES) in EVCS can not only decrease the energy fluctuation by participating in peakload reduction of the grid, but also reduce the pollution to the environment by cutting down the use of fossil fuels. In this paper,the optimal planning for grid-connected EVCS with RES is studied by considering EV load uncertainty. Nine scenarios are set based on a different characteristic of EV load to reveal the impact of EV load on net present cost(NPC) and to express the relationship between the optimal capacity and energy flow. Moreover, since electricity price also plays an important role in EVCS planning, an economic comparison between different cases with different electricity prices for peak-valley-flat period is carried out. The results reveal the economic benefits of applying RES in EVCS, and demonstrate that EV load with different characteristics would influence the capacity of each device(PV, battery, converter) in the EVCS optimal planning.

Feasibility of Grid-connected Solar-wind Hybrid System with Electric Vehicle Charging Station

Recently,renewable power generation and electric vehicles(EVs)have been attracting more and more attention in smart grid.This paper presents a grid-connected solar-wind hybrid system to supply the electrical load demand of a small shopping complex located in a university campus in India.Further,an EV charging station is incorporated in the system.Economic analysis is performed for the proposed setup to satisfy the charging demand of EVs as well as the electrical load demand of the shopping complex.The proposed system is designed by considering the cost of the purchased energy,which is sold to the utility grid,while the power exchange is ensured between the utility grid and other components of the system.The sizing of the component is performed to obtain the least levelized cost of electricity(LCOE)while minimizing the loss of power supply probability(LPSP)by using recent optimization techniques.The results demonstrate that the LCOE and LPSP for the proposed system are measured at 0.038$/k Wh and0.19%with a renewable fraction of 0.87,respectively.It is determined that a cost-effective and reliable system can be designed by the proper management of renewable power generation and load demands.The proposed system may be helpful in reducing the reliance on the over-burdened grid,particularly in developing countries.

CHARGING STATION PLANNING FOR PLUG-IN ELECTRIC VEHICLES

A novel model for the charging station planning problem of plug-in electric vehicles is proposed in this paper considering the users＇ daily travel. With the objective of minimizing the total cost, including the charging stations＇ cost （including installing cost and management cost） and the users＇ cost （including station access cost and charging cost）, the proposed model simultaneously handles the problems where to locate the charging stations and how many chargers to be established in each charging station. Considering that different users may have different perception of station access cost and charging cost, two cases （i.e., homogeneous users and heterogeneous users） are typically investigated. The impacts of different discount rates, operating period of the charging stations, number of electric vehicles and number of charging stations on the location of the charging station are also studied. The simulation results not only show that it is very important to locate the charging stations according to the traveling behavior of users, but also verify the validity of the proposed model.