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.

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.

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.

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.

Monitoring seismicity in the southern Sichuan Basin using a machine learning workflow

Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses.In this study,we propose an automatic workflow based on machine learning(ML)to monitor seismicity in the southern Sichuan Basin of China.This workflow includes coherent event detection,phase picking,and earthquake location using three-component data from a seismic network.By combining Phase Net,we develop an ML-based earthquake location model called Phase Loc,to conduct real-time monitoring of the local seismicity.The approach allows us to use synthetic samples covering the entire study area to train Phase Loc,addressing the problems of insufficient data samples,imbalanced data distribution,and unreliable labels when training with observed data.We apply the trained model to observed data recorded in the southern Sichuan Basin,China,between September 2018 and March 2019.The results show that the average differences in latitude,longitude,and depth are 5.7 km,6.1 km,and 2 km,respectively,compared to the reference catalog.Phase Loc combines all available phase information to make fast and reliable predictions,even if only a few phases are detected and picked.The proposed workflow may help real-time seismic monitoring in other regions as well.

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.

Design scheme for fast charging station for electric vehicles with distributed photovoltaic power generation

The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a design scheme for a fast charging station for electric vehicles equipped with distributed photovoltaic power generation system taking the area with certain conditions in Beijing as an example construction site. The technical indexes and equipment lectotype covering the general framework and subsystems of the charging station are determined by analyzing the charging service demand of fast charging stations. In this study, the layout of the station is developed and the operation benefits of the station is analyzed. The design scheme realizes the design objective of "rationalization, modularization and intelligentization" of the fast charging station and can be used as reference for the construction of a fast charging network in urban area.

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.

Location of Electric Vehicle Charging Station Based on Spatial Clustering and Multi-hierarchical Fuzzy Evaluation

For the charging station construction of electric vehicle,location selecting is a key issue.There are two problems in location selection of the electric vehicle charging station.One is determining the location of charging station;the other is evaluating the location of charging station.To determine the charging station location,an spatial clustering algorithm is proposed and programmed.The example simulation shows the effectiveness of the spatial clustering algorithm.To evaluate the charging station location,a multi-hierarchical fuzzy method is proposed.Based on the location factors of electric vehicle charging station,the hierarchical evaluation structure of electric vehicle charging station location is constructed,including three levels,4first-class factors and 14second-class factors.The fuzzy multi-hierarchical evaluation model and algorithm are built.The analysis results show that the multi-hierarchical fuzzy method can reasonably complete the electric vehicle charging station location evaluation.

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,

Nuclear charge radius predictions by kernel ridge regression with odd-even effects

The extended kernel ridge regression(EKRR)method with odd-even effects was adopted to improve the description of the nuclear charge radius using five commonly used nuclear models.These are:(i)the isospin-dependent A^(1∕3) formula,(ii)relativistic continuum Hartree-Bogoliubov(RCHB)theory,(iii)Hartree-Fock-Bogoliubov(HFB)model HFB25,(iv)the Weizsacker-Skyrme(WS)model WS*,and(v)HFB25*model.In the last two models,the charge radii were calculated using a five-parameter formula with the nuclear shell corrections and deformations obtained from the WS and HFB25 models,respectively.For each model,the resultant root-mean-square deviation for the 1014 nuclei with proton number Z≥8 can be significantly reduced to 0.009-0.013 fm after considering the modification with the EKRR method.The best among them was the RCHB model,with a root-mean-square deviation of 0.0092 fm.The extrapolation abilities of the KRR and EKRR methods for the neutron-rich region were examined,and it was found that after considering the odd-even effects,the extrapolation power was improved compared with that of the original KRR method.The strong odd-even staggering of nuclear charge radii of Ca and Cu isotopes and the abrupt kinks across the neutron N=126 and 82 shell closures were also calculated and could be reproduced quite well by calculations using the EKRR method.

Optimal Siting of Electric Vehicle Charging Stations Based on Voronoi Diagram and FAHP Method

The electric vehicle charging station should be allocated based on traffic density, geographical distribution and other factors, and Voronoi diagram is adopted to set the service area of charging station. In combination with the actual situation of site selection of electric vehicle charging station, the comprehensive benefits index system is established. There are numerous factors influencing the site selection, among which there are uncertainty and fuzziness. The comprehensive evaluation method based on the fuzzy analysis and Analytical Hierarchy Process (AHP) is used to evaluate the comprehensive benefits in the site selection of electric vehicle charging stations, with the consultation of experts. This paper contributes to the best selection of comprehensive benefits and provides the reference for the decision-making of building the electric vehicle charging station. Actual examples show that the method proposed is effective.

Break-Even Analysis on the Charging and Battery-Swapped Station of Electric Vehicles

The construction of electric vehicle charging station plays an important role in the development of electric vehicles and the promotion of the renewable resource. In the paper, a model to analyze the economic benefit of the charging station is presented, which is based on the break-even theory. Then the threshold price is calculated based on the model according to the construction plans of charging facilities in one district. Finally, the strategy for the development of charging faculties is proposed to improve the health growth of electric automotive industry.

A Prediction Method of Charging Station Planning Based on BP Neural Network

The construction of charging service facilities is a very important factor in the popularization of electric vehicles. Therefore, the planning problems of electric vehicle charging station are urgent to be solved. Considering the standard of natural environment, society, traffic, power grid and economy, an evaluation system is created for electric vehicle charging station project through 15 sub-standards. Planning model of charging station is constructed based on BP neural network adopted in the analysis. It is used for location and capacity prediction of charging station planning. By analyzing the model with data samples, a stable network structure is established and the feasibility of the model is verified in the charging station planning.

The Comprehensive Evaluation Research of Automated Charging Station’s Lightning Protection Design in Airport

In order to inspect the good and reliability of automated charging station’s lightning protection design in airport, we set the comprehensive evaluation mathematical model of automated charging station in the airport, through the method of second order fuzzy comprehensive evaluation and evaluate the automated charging station’s lightning protection design comprehensively by using the assessment data of expert database.

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.