scholarly journals An Orderly EV Charging Scheduling Method Based on Deep Learning in Cloud-Edge Collaborative Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jiayong Zhong ◽  
Xiaofu Xiong

The rapid increase of the number of electric vehicles (EVs) has posed great challenges to the safe operation of the distribution network. Therefore, this paper proposes an ordered charging scheduling method for EV in the cloud-edge collaborative environment. Firstly, the uncertainty of user load demands, charging station requirements, and renewable outputs are taken into consideration. Correspondingly, the residential distribution points, EV charging stations, and renewable plants are regarded as the edge nodes. Then, the load demands and renewable outputs are predicted by a model combined with the convolutional neural network and deep belief network (CNN-DBN). Secondly, the power supply plans for charging stations are determined at the cloud side aiming at minimizing the operating cost of the distribution network via collecting the forecasting results. Finally, the charging station formulates the personalized charging scheduling strategies according to EV’s charging plans and the charging demands in order to follow the supply plan. The simulation results show that the load peak-to-valley difference and standard deviation of the proposed algorithm are reduced by 30.13% and 16.94%, respectively, compared with the disorderly charging and discharging behavior, which has verified the effectiveness and feasibility of the proposed method.

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2820 ◽  
Author(s):  
Hui Sun ◽  
Peng Yuan ◽  
Zhuoning Sun ◽  
Shubo Hu ◽  
Feixiang Peng ◽  
...  

With the popularization of electric vehicles, free charging behaviors of electric vehicle owners can lead to uncertainty about charging in both time and space. A time-spatial dispatching strategy for the distribution network guided by electric vehicle charging fees is proposed in this paper, which aims to solve the network congestion problem caused by the unrestrained and free charging behaviors of large numbers of electric vehicles. In this strategy, congestion severity of different lines is analyzed and the relationship between the congested lines and the charging stations is clarified. A price elastic matrix is introduced to reflect the degree of owners’ response to the charging prices. A pricing scheme for optimal real-time charging fees for multiple charging stations is designed according to the congestion severity of the lines and the charging power of the related charging stations. Charging price at different charging station at different time is different, it can influence the charging behaviors of vehicle owners. The simulation results confirmed that the proposed congestion dispatching strategy considers the earnings of the operators, charging cost to the owners and the satisfaction of the owners. Moreover, the strategy can influence owners to make judicious charging plans that help to solve congestion problems in the network and improve the safety and economy of the power grid.


Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3922 ◽  
Author(s):  
Ruijiu Jin ◽  
Xiangfeng Zhang ◽  
Zhijie Wang ◽  
Wengang Sun ◽  
Xiaoxin Yang ◽  
...  

Increasing penetration of electric vehicles (EVs) gives rise to the challenges in the secure operation of power systems. The EV charging loads should be distributed among charging stations in a fair and incentive-compatible manner while ensuring that power transmission and transformation facilities are not overloaded. This paper first proposes a charging right (or charging power ration) trading mechanism and model based on blockchain. Considering all kinds of random factors of charging station loads, we use Monte Carlo modeling to determine the charging demand of charging stations in the future. Based on the charging demand of charging stations, a charging station needs to submit the charging demand for a future period. The blockchain first distributes initial charging right in a just manner and ensures the security of facilities. Given that the charging urgency and elasticity differences vary by charging stations, all charging stations then proceed with double auction and peer-to-peer (P2P) transaction of charging right. Bids and offers are cleared via double auctions if bids are higher than offers. The remaining bids and offers are cleared via the P2P market. Then, this paper designs the charging right allocation and trading platform and smart contract based on the Ethernet blockchain to ensure the safety of the distribution network (DN) and the transparency and efficiency of charging right trading. Simulation results based on the Ethereum private blockchain show the fairness and efficiency of the proposed mechanism and the effectiveness of the method and the mechanism.


Author(s):  
Jayababu Badugu ◽  
Y.P. Obulesu ◽  
Ch. Sai Babu

Electric Vehicles (EVs) are becoming a viable transportation option because they are environmentally friendly and provide solutions to high oil prices. This paper investigates the impacts of electric vehicles on harmonic distortions in urban radial residential distribution systems. The accomplishment of EV innovation relies on the accessibility of EV charging stations. To meet the power demand of growing EVs, utilities are introducing EV charging stations in private and public areas; this led to a change in the residential distribution system infrastructure. In this paper, an urban radial residential distribution system with the integration of an electric vehicle charging facility is considered for investigation. An impact of different EV penetration levels on voltage distortion is analysed. Different penetration levels of EVs into the residential distribution system are considered. Simulation results are presented to validate the work carried out in this paper. An attempt has been made to establish the relationship between the level of penetration of the EVs and voltage distortion in terms of THD (Total Harmonic Distortion)


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 962
Author(s):  
Jian-Tang Liao ◽  
Hao-Wei Huang ◽  
Hong-Tzer Yang ◽  
Desheng Li

With a rapid increase in the awareness of carbon reduction worldwide, the industry of electric vehicles (EVs) has started to flourish. However, the large number of EVs connected to a power grid with a large power demand and uncertainty may result in significant challenges for a power system. In this study, the optimal charging and discharging scheduling strategies of G2V/V2G and battery energy storage system (BESS) were proposed for EV charging stations. A distributed computation architecture was employed to streamline the complexity of an optimization problem. By considering EV charging/discharging conversion efficiencies for different load conditions, the proposed method was used to maximize the operational profits of each EV and BESS based on the related electricity tariff and demand response programs. Moreover, the behavior model of drivers and cost of BESS degradation caused by charging and discharging cycles were considered to improve the overall practical applicability. An EV charging station with 100 charging piles was simulated as an example to verify the feasibility of the proposed method. The developed algorithms can be used for EV charging stations, load aggregators, and service companies integrated with distributed energy resources in a smart grid.


2021 ◽  
Author(s):  
Manjush Ganiger ◽  
Maneesh Pandey ◽  
Rahul Wagh ◽  
Rakesh Govindasamy

Abstract Transition towards electric vehicles (EV) is the key enabler for fighting against climate change as well as for sustainable future. However, to build more confidence on EV transition, availability of charging infrastructure is key. One of the important criterions for vehicle charging station is to have a stable electricity source that can meet varying charging demand. The paper attempts to explore the eco-system of self-sustainable and quasi-renewable charging infrastructure. This paper outlines a circular economy model for EV charging station (EVCS) using a gas turbine from the Baker Hughes™ portfolio. The proposed solution includes Solid Oxide Electrolyzer and a carbon capture unit, integrated to the gas turbine. This integrated system is decarbonized using the hydrogen generated by the electrolysis unit. Proposed solution on EVCS can charge about 1500 EVs in half a day of operation (50% power split). Solution is lucrative and has attractive return on investment. The solution here is having high power density, compared to the actual renewable energy dependent charging stations. The solution is flexible to incorporate Power-to-X conversions. Modular nature of the solution makes it easy to implement in city limits as well as in remote locations, along the highways, where grid availability can be challenging.


Sign in / Sign up

Export Citation Format

Share Document