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 A Novel Charging and Discharging Algorithm of Plug-in Hybrid Electric Vehicles Considering Vehicle-to-Grid and Photovoltaic Generation

2019 ◽  
Vol 10 (4) ◽  
pp. 61
Author(s):  
Ahmed Aljanad ◽  
Azah Mohamed ◽  
Tamer Khatib ◽  
Afida Ayob ◽  
Hussain Shareef
Keyword(s):  
Electric Vehicles ◽  
Control Algorithm ◽  
Peak Load ◽  
Distribution Networks ◽  
Management Control ◽  
Photovoltaic Generation ◽  
Technical Problems ◽  
Vehicle To Grid ◽  
Fast Charging ◽  
The Impact

Considering, the high penetration of plug-in electric vehicles (PHEVs), the charging and discharging of PHEVs may lead to technical problems on electricity distribution networks. Therefore, the management of PHEV charging and discharging needs to be addressed to coordinate the time of PHEVs so as to be charged or discharged. This paper presents a management control method called the charging and discharging control algorithm (CDCA) to determine when and which of the PHEVs can be activated to consume power from the grid or supply power back to grid through the vehicle-to-grid technology. The proposed control algorithm considers fast charging scenario and photovoltaic generation during peak load to mitigate the impact of the vehicles. One of the important parameters considered in the CDCA is the PHEV battery state of charge (SOC). To predict the PHEV battery SOC, a particle swarm optimization-based artificial neural network is developed. Results show that the proposed CDCA gives better performance as compared to the uncoordinated charging method of vehicles in terms of maintaining the bus voltage profile during fast charging.

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.

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.

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