A Stochastic Model for Simulating the Availability of Electric Vehicles for Services to the Power Grid

Fluhr, Jonas; Ahlert, Klaus-Henning; Weinhardt, Christof

doi:10.1109/hicss.2010.33

Cited by 47 publications

(36 citation statements)

References 7 publications

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“…As an important prerequisite and conditions for grid largescale integrations electric vehicles (EVs), the battery charging and swapping technologies and related infrastructure facilities for EVs have attracted widespread attention [1][2][3][4][5][6][7]. State Grid Corporation of China (SGCC) attaches great importance for the operational requirements of EVs, and has carried out a series of research programs and demonstration projects in this field.…”

Section: Introductionmentioning

confidence: 99%

Architecture and performance analysis of a smart battery charging and swapping operation service network for electric vehicles in China

Yao

Zeng

et al. 2015

J. Mod. Power Syst. Clean Energy

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In recent years, the Chinese government and State Grid Corporation of China (SGCC) have paid great attention to the technical development and infrastructure construction for electric vehicles (EVs). This paper focuses on the mechanism of Smart Battery Charging and Swapping Operation Service Network for EVs including its overall architecture and operational mode. The overall architecture based on the internet of things is analyzed and clarified through terminal device, station management and management center layers. Then two different types of demonstration projects are presented which expound on the condition of EV's infrastructure construction. Lastly, performance analysis of the charging behaviors of electric taxis in fast charging station based on the Queuing theory is proposed. The simulation results show that the service time and the number of generators has an influence on the average waiting time and the length of queue.

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Section: Introductionmentioning

confidence: 99%

Architecture and performance analysis of a smart battery charging and swapping operation service network for electric vehicles in China

Yao

Zeng

et al. 2015

J. Mod. Power Syst. Clean Energy

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show abstract

“…Because of the structure heterogeneity among the existing database systems and the limitation of data qualities from both objective and subjective factors, the IPDU big data system could not directly meet the requirements of traditional data analysis and decision technologies. At the same time, it also comes into a small sample environment for parts of samples in IPDU big data, and brings out great challenges for the data quality management of distribution networks, which makes it difficult to guarantee the accuracy of analysis and decisions [7,8]. Therefore, the study on heterogeneous data integration technology has a significant influence on the future intelligent power distribution and utilization, which can also greatly improve the accuracy and efficiency of distribution network's operation and decision-making.…”

Section: Introductionmentioning

confidence: 99%

Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

Tan

Liu

et al. 2018

Applied Sciences

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Featured Application: Authors are encouraged to provide a concise description of the specific application or a potential application of the work. This section is not mandatory.Abstract: Heterogeneous characteristics of a big data system for intelligent power distribution and utilization have already become more and more prominent, which brings new challenges for the traditional data analysis technologies and restricts the comprehensive management of distribution network assets. In order to solve the problem that heterogeneous data resources of power distribution systems are difficult to be effectively utilized, a novel generative adversarial networks (GANs) based heterogeneous data integration method for intelligent power distribution and utilization is proposed. In the proposed method, GANs theory is introduced to expand the distribution of completed data samples. Then, a so-called peak clustering algorithm is proposed to realize the finite open coverage of the expanded sample space, and repair those incomplete samples to eliminate the heterogeneous characteristics. Finally, in order to realize the integration of the heterogeneous data for intelligent power distribution and utilization, the well-trained discriminator model of GANs is employed to check the restored data samples. The simulation experiments verified the validity and stability of the proposed heterogeneous data integration method, which provides a novel perspective for the further data quality management of power distribution systems.

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“…Their work is not applicable here because public transit vehicles are not parked long enough to serve as vehicle to grid stores. Specifically, the authors of [21] show at any given point in a day, even during rush hour, more than 90% of all residential vehicles are parked. In comparison, however, the typical taxi in our study parked on average only 12% of each day.…”

Section: Related Literaturementioning

confidence: 99%

“…Several papers address the issue of optimal EV charging times [9,12,14,21,24,29]. Many of these studies conclude off-peak overnight charging of EVs is the best charging strategy for personally owned vehicles, because nearly all such vehicles are parked at this time and overnight charging puts the least burden on the electricity grid.…”

Section: Related Literaturementioning

confidence: 99%

The return on investment for taxi companies transitioning to electric vehicles

2013

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We study whether taxi companies can simultaneously save petroleum and money by transitioning to electric vehicles. We propose a process to compute the return on investment (ROI) of transitioning a taxi corporation's fleet to electric vehicles. We use Bayesian data analysis to infer the revenue changes associated with the transition. We do not make any assumptions about the vehicles' mobility patterns; instead, we use a time-series of GPS coordinates of the company's existing petroleum-based vehicles to derive our conclusions.As a case study, we apply our process to a major taxi corporation, Yellow Cab San Francisco (YCSF). Using current prices, we find that transitioning their fleet to battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) is profitable for the company. Furthermore, given that gasoline prices in San Francisco are only 5.4% higher than the rest of the United States, but electricity prices are 75% higher; taxi companies with similar practices and mobility patterns in other cities are likely to profit more than YCSF by transitioning to EVs.

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A Stochastic Model for Simulating the Availability of Electric Vehicles for Services to the Power Grid

Cited by 47 publications

References 7 publications

Architecture and performance analysis of a smart battery charging and swapping operation service network for electric vehicles in China

Architecture and performance analysis of a smart battery charging and swapping operation service network for electric vehicles in China

Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

The return on investment for taxi companies transitioning to electric vehicles

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