Economic Analysis of On-Route Fast Charging for Battery Electric Buses: Case Study in Utah

2019 ◽  
Vol 2673 (5) ◽  
pp. 119-130 ◽  
Author(s):  
Zhaocai Liu ◽  
Ziqi Song ◽  
Yi He
Keyword(s):  
Economic Analysis ◽  
Operating Time ◽  
Capital Costs ◽  
Charging Time ◽  
Fast Charging ◽  
Driving Range ◽  
Transit Agencies ◽  
Battery Technology ◽  
Charging Stations ◽  
The Impact

Battery electric buses (BEBs) are increasingly being embraced by transit agencies as an energy-efficient and emission-free alternative to bus fleets. However, because of the limitations of battery technology, BEBs suffer from limited driving range, great battery cost, and time-consuming charging processes. On-route fast charging technology is gaining popularity as a remedy, reducing battery cost, extending driving range, and reducing charging time. With on-route fast charging, BEBs are as capable as their diesel counterparts in relation to range and operating time. However, transit agencies may have the following concerns about on-route fast charging: 1) on-route fast charging stations require massive capital costs; 2) on-route fast charging may lead to high electricity power demand charges; and 3) charging during peak hours may increase electricity energy charges. This study conducts a quantitative economic analysis of on-route fast charging for BEBs, thereby providing some guidelines for transit agencies. An integrated optimization model is first proposed to determine battery size, charger type, and recharging schedule for a general BEB route. Based on the model, an economic analysis of on-route fast charging is then performed on 10 real-world bus routes and a simplified general bus route with different parameters. The results demonstrate that given the current prices of on-route fast charging stations and batteries, it is always beneficial to install on-route fast charging stations for BEBs. A sensitivity analysis is also conducted to show the impact of potential price reductions of batteries.

scholarly journals Perceived Usage Potential of Fast-Charging Locations

2018 ◽  
Vol 9 (1) ◽  
pp. 14 ◽  
Author(s):  
Julia Krause ◽  
Stefan Ladwig ◽  
Lotte Saupp ◽  
Denis Horn ◽  
Alexander Schmidt ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Point Of View ◽  
Charging Infrastructure ◽  
Charging Time ◽  
Points Of Interest ◽  
Fast Charging ◽  
Business Perspective ◽  
Charging Stations ◽  
User Perspectives ◽  
Model Point

Fast-charging infrastructure with charging time of 20–30 min can help minimizing current perceived limitations of electric vehicles, especially considering the unbalanced and incomprehensive distribution of charging options combined with a long perceived charging time. Positioned on optimal location from user and business perspective, the technology is assumed to help increasing the usage of an electric vehicle (EV). Considering the user perspectives, current and potential EV users were interviewed in two different surveys about optimal fast-charging locations depending on travel purposes and relevant location criteria. The obtained results show that customers prefer to rather charge at origins and destinations than during the trip. For longer distances, charging locations on axes with attractive points of interest are also considered as optimal. From the business model point of view, fast-charging stations at destinations are controversial. The expensive infrastructure and the therefore needed large number of charging sessions are in conflict with the comparatively time consuming stay.

Multi-objective optimal planning of fast charging stations by considering various load models in distribution system

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Gurappa Battapothula ◽  
Chandrasekhar Yammani ◽  
Sydulu Maheswarapu
Keyword(s):  
Distribution System ◽  
Constant Current ◽  
Constant Power ◽  
Multi Objective ◽  
Load Models ◽  
Power Load ◽  
Fast Charging ◽  
Charging Stations ◽  
Constant Power Load ◽  
The Impact

Abstract Electric vehicles (EVs) load and its charging methodologies play a significant role in distribution system planning. The inaccurate modelling of EV load may overload the distribution system components, increase in Network Power Loss (NPL) and Maximum Voltage Deviation (MVD). The Constant Power (CP) load model is more popularly used to model both the conventional and EV loads in the distribution system. But the CP load modelling cannot provide accurate information of EV charging process. In this paper, the EV load is modelled as constant Impedance-constant Current-constant Power (ZIP), Exponential, Constant Current and Constant Power load models and the conventional loads are modelled as Residential–Industrial–Commercial (RIC) and Constant Power load models. With these EV and conventional load models, the optimal site and size of Fast Charging Stations (FCSs) in the distribution system have been determined. Further, to analyse the impact of load of FCSs in the distribution system, the distribution indices are calculated. The multi-objective hybrid SFL-TLBO algorithm has been used to determine the optimal location and size FCSs with the minimization of NPL, MVD and EV User Cost (EVUC) in the distribution system. To consider the uncertainty of the initial SOC of EVs, the Monte-Carlo simulation technique has been used. These studies have been carried out on 38-bus distribution system and substantiate results are presented.

scholarly journals Stationary Energy Storage System for Fast EV Charging Stations: Simultaneous Sizing of Battery and Converter

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4516 ◽  
Author(s):  
Akhtar Hussain ◽  
Van-Hai Bui ◽  
Ju-Won Baek ◽  
Hak-Man Kim
Keyword(s):  
Energy Storage ◽  
Interest Rates ◽  
Peak Load ◽  
Return Time ◽  
Total Annual Cost ◽  
Worst Case ◽  
Fast Charging ◽  
Stationary Energy ◽  
Charging Stations ◽  
The Impact

Optimal sizing of stationary energy storage systems (ESS) is required to reduce the peak load and increase the profit of fast charging stations. Sequential sizing of battery and converter or fixed-size converters are considered in most of the existing studies. However, sequential sizing or fixed-converter sizes may result in under or oversizing of ESS and thus fail to achieve the set targets, such as peak shaving and cost reduction. In order to address these issues, simultaneous sizing of battery and converter is proposed in this study. The proposed method has the ability to avoid the under or oversizing of ESS by considering the converter capacity and battery size as two independence decision variables. A mathematical problem is formulated by considering the stochastic return time of electrical vehicles (EVs), worst-case state of charge at return time, number of registered EVs, charging level of EVs, and other related parameters. The annualized cost of ESS is computed by considering the lifetime of ESS equipment and annual interest rates. The performance of the proposed method is compared with the existing sizing methods for ESS in fast-charging stations. In addition, sensitivity analysis is carried out to analyze the impact of different parameters on the size of the battery and the converter. Simulation results have proved that the proposed method is outperforming the existing sizing methods in terms of the total annual cost of the charging station and the amount of power buying during peak load intervals.

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

2020 ◽  
Vol 5 (7) ◽  
pp. 601-607
Author(s):  
Veerpratap Meena ◽  
Dr Vinay Pant ◽  
Arunendra Verma ◽  
Kanchan Chariya
Keyword(s):  
New Technologies ◽  
Control Strategies ◽  
Environment Friendly ◽  
Grid Systems ◽  
Charging Time ◽  
Three Phase ◽  
Fast Charging ◽  
Multiple Vehicles ◽  
Simulation Results ◽  
Charging Stations

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.

Reliability Evaluation of Fast-Charging EV Station Entry to Generation and Transmission Electrical System

2013 ◽  
Vol 860-863 ◽  
pp. 1096-1100 ◽  
Author(s):  
Hang Du ◽  
Chun Lin Guo
Keyword(s):  
Power Generation ◽  
Simulation Method ◽  
Reliability Evaluation ◽  
Transmission Power ◽  
Monte Carlo Simulation Method ◽  
Electrical System ◽  
Charging Time ◽  
Fast Charging ◽  
Comprehensive Reliability ◽  
The Impact

This paper predicts the future of rapid charging technology for EV, including its corresponding vehicle types and charging time. We choose the Monte Carlo simulation method to choose the initial charging time, initial SOC for each EV randomly, so as to get the fast charging EV load. After all these, we could have a comprehensive reliability evaluation of the generation and transmission power system includes fast charging EV load. In the end, through a matlab test example, a reliability evaluation on the impact of fast charging EV load on power generation and transmission system is made.

scholarly journals Bi-Level Planning Model of Charging Stations Considering the Coupling Relationship between Charging Stations and Travel Route

2018 ◽  
Vol 8 (7) ◽  
pp. 1130 ◽  
Author(s):  
Haixiang Zang ◽  
Yuting Fu ◽  
Ming Chen ◽  
Haiping Shen ◽  
Liheng Miao ◽  
...  
Keyword(s):  
Queuing Theory ◽  
Planning Model ◽  
Travel Pattern ◽  
Charging Infrastructure ◽  
Factors Affecting ◽  
Satisfaction Index ◽  
Fast Charging ◽  
Total Social Cost ◽  
Charging Stations ◽  
The Impact

The major factors affecting the popularization of electric vehicles (EV) are the limited travel range and the lack of charging infrastructure. Therefore, to further promote the penetration of EVs, it is of great importance to plan and construct more fast charging stations rationally. In this study, first we establish a travel pattern model based on the Monte Carlo simulation (MCS). Then, with the traveling data of EVs, we build a bi-level planning model of charging stations. For the upper model, with an aim to maximize the travel success ratio, we consider the influence of the placement of charging stations on the user’s travel route. We adopt a hybrid method based on queuing theory and the greedy algorithm to determine the capacity of charging stations, and we utilize the total social cost and satisfaction index as two indicators to evaluate the optimal solutions obtained from the upper model. Additionally, the impact of the increase of EV ownership and slow charger coverage in the public parking lot on the fast charging demands and travel pattern of EV users are also studied. The example verifies the feasibility of the proposed method.

scholarly journals Optimal Scheduling and Economic Analysis of Hybrid Electric Vehicles in a Microgrid

2018 ◽  
Vol 19 (6) ◽  
Author(s):  
George Fernandez Savari ◽  
Vijayakumar Krishnasamy ◽  
Josep M. Guerrero
Keyword(s):  
Economic Analysis ◽  
Electric Vehicles ◽  
Electricity Market ◽  
Hybrid Electric Vehicles ◽  
Shuffled Frog Leaping Algorithm ◽  
Charging Time ◽  
High Penetration ◽  
Shuffled Frog Leaping ◽  
Charging Stations ◽  
Priority Algorithm

Abstract A projected high penetration of electric vehicles (EVs) in the electricity market will introduce an additional load in the grid. The foremost concern of EV owners is to reduce charging expenditure during real-time pricing. This paper presents an optimal charging schedule of the electric vehicle with the objective to minimize the charging cost and charging time. The allocation of EVs should satisfy constraints related to charging stations (CSs) status. The results obtained are compared with the two conventional algorithms and other charging algorithms: Arrival time-based priority algorithm (ATP) and SOC based priority algorithm (SPB), Particle Swarm Optimization (PSO) and Shuffled Frog Leaping Algorithm (SFLA). Also, the CS is powered by the main grid and the microgrid available in the CSs. The EVs charging schedule and the economic analysis is done for two cases: (i) With Grid only (ii) With Combined Grid & microgrid. The load shifting of EVs is done based on the grid pricing and the results obtained are compared with the other cases mentioned.

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