scholarly journals Energy Management Method for Fast-Charging Stations with the Energy Storage System to Alleviate the Voltage Problem of the Observation Node

2021 ◽  
Vol 12 (4) ◽  
pp. 234
Author(s):  
Rui Ye ◽  
Xueliang Huang ◽  
Zexin Yang
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Test System ◽  
Assessment Model ◽  
Voltage Change ◽  
Fast Charging ◽  
Voltage Deviation ◽  
Nodal Voltage ◽  
Charging Stations ◽  
Deviation Problem

Large-scale fast charging of electric vehicles (EVs) probably causes voltage deviation problems in the distribution network. Installing energy storage systems (ESSs) in the fast-charging stations (FCSs) and formulating appropriate active power plans for ESSs is an effective way to reduce the local voltage deviation problem. Some deterministic centralized strategies used for ESSs at FCSs are proposed to solve the voltage deviation problem mentioned above. However, the randomness of the EV load is very large, which can probably reduce the effects of deterministic centralized strategies. A fast and reliable centralized strategy considering the randomness of the EV load for ESSs is a key requirement. Therefore, we propose in this paper a day-ahead scheduling strategy with the aim of maximizing the probability of the nodal voltage change being smaller than a preset limit at the observation node. In the proposed strategy, the uncertainty of EV load is taken into account and the probability of the voltage change of an observation node is quantified by a proposed analytic assessment model (AMM). Furthermore, a voltage change optimization model (VCOM) based on a novel control parameter β is proposed, where β can be used as a constraint to suppress the nodal voltage change at the observation node. Finally, the IEEE 33-bus test system is used to verify the effectiveness of the proposed day-ahead ESS strategy.

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.

Driving Coverage of Charging Stations for Battery Electric Trucks Located at Truck Stop Facilities

2021 ◽  
pp. 036119812110315
Author(s):  
Antonio Hurtado-Beltran ◽  
Laurence R. Rilett ◽  
Yunwoo Nam
Keyword(s):  
Rural Areas ◽  
Large Scale ◽  
Interstate Highway ◽  
Fuel Savings ◽  
Study Approach ◽  
Interstate Highway System ◽  
Fast Charging ◽  
Charging Stations ◽  
The U.S ◽  
Highway System

Battery-powered electric trucks could soon be deployed on a large scale along long-haul routes on the U.S. trunk highway system. These vehicles have numerous advantages, including zero emissions, fuel savings, and lower maintenance costs, that make them attractive for motor carrier companies. However, the deployment of this technology depends on the development of a convenient network of fast-charging stations that can provide sufficient driving coverage along the Interstate highway system. The majority of existing fast-charging stations in rural areas currently are not adequate for the movement of large trucks. A potential solution is to install fast-charging stations at the vast network of rural truck stops. Truck stops are specifically designed for the movement of trucks and are already located on the routes with the highest truck demand. The main objective of this study was to develop a methodology for identifying the driving coverage provided if fast-charging stations were located at truck stop facilities along the U.S. Interstate highway system. The contiguous U.S.A. was taken as the study area. The study approach was based on a geographic information system network analysis with a specific focus on the service area. It was found that truck stop facilities could potentially provide 99.5% driving coverage for electric trucks on the Interstate highway system. This makes them opportune locations for future fast-charging stations. These findings may assist transportation planners and operators in defining strategies required for planning the deployment of long-haul electric trucks on the U.S. highway system.

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