short-paper

EVLib: A Library for the Management of the Electric Vehicles in the Smart Grid

Authors:

Sotiris Karapostolakis,

Emmanouil S. Rigas,

Nick Bassiliades,

Sarvapali D. RamchurnAuthors Info & Claims

SETN '16: Proceedings of the 9th Hellenic Conference on Artificial Intelligence

Article No.: 13, Pages 1 - 4

https://doi.org/10.1145/2903220.2903225

Published: 18 May 2016 Publication History

Get Access

Abstract

EVLib is a Java library for the management and simulation of a number of Electric Vehicle (EV) activities, at a charging station level, within a Smart Grid environment. EVLib aims to solve interoperability issues between a number of Artificial Intelligence (AI)-related techniques already applied in this field. Thus, it provides a simple, yet efficient interface for the management of all major EV-related activities such as the charging and dis-charging of batteries, as well as the battery swapping. Moreover, a large number of parameters, such as the number of chargers, the waiting queues, and the available energy can be easily configured. On top of this, the library supports the simultaneous operation of many EV activities through the efficient use of threads. Finally, the library's efficiency and scalability have been tested in realistic scenarios, while the correctness and safety of the code have been verified using state of the art tools.

References

[1]

H. Farhangi. The path of the smart grid. Power and Energy Magazine, IEEE, 8(1):18--28, January 2010.

Crossref

Google Scholar

[2]

IEA. Global ev outlook. Technical report, 2013.

Google Scholar

[3]

W. Kempton and J. Tomic. Vehicle-to-grid power fundamentals: Calculating capacity and net revenue. Journal of Power Sources, 144(1):268--279, 2005.

Crossref

Google Scholar

[4]

W. J. Mitchel, C. E. Borroni-Bird, and L. D. Burns. Reinventing the automobile: Personal urban mobility for the 21st century. MIT Press, 2010.

Crossref

Google Scholar

[5]

M. A. Nicholas, G. Tal, and J. Woodjack. California statewide charging survey: What do drivers want? 92nd Annual Meeting of the Transportation Research Board, 2013.

Google Scholar

[6]

E. Rigas, S. Ramchurn, and N. Bassiliades. Managing electric vehicles in the smart grid using artificial intelligence: A survey. Intelligent Transportation Systems, IEEE Transactions on, 16(4):1619--1635, Aug 2015.

Google Scholar

[7]

E. S. Rigas, S. D. Ramchurn, and N. Bassiliades. Algorithms for electric vehicle scheduling in mobility-on-demand schemes. In Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on, pages 1339--1344, Sept 2015.

Digital Library

Google Scholar

[8]

E. S. Rigas, S. D. Ramchurn, N. Bassiliades, and G. Koutitas. Congestion management for urban ev charging systems. In Smart Grid Communications (SmartGridComm), 2013 IEEE International Conference on, pages 121--126, 2013.

Crossref

Google Scholar

Cited By

View all

Frendo OGaertner NStuckenschmidt H(2021)Open Source Algorithm for Smart Charging of Electric Vehicle FleetsIEEE Transactions on Industrial Informatics10.1109/TII.2020.303814417:9(6014-6022)Online publication date: Sep-2021
https://doi.org/10.1109/TII.2020.3038144
Sun ZZhao CYan Z(2018)An Optimizing Power System Dispatch with An Extra EV Load Using PLEXOS Appoach2018 China International Conference on Electricity Distribution (CICED)10.1109/CICED.2018.8592362(162-167)Online publication date: Sep-2018
https://doi.org/10.1109/CICED.2018.8592362

Recommendations

Electric Vehicle Optimized Charge and Drive Management

Electric vehicles (EVs) have been considered as a solution to the environmental issues caused by transportation, such as air pollution and greenhouse gas emission. However, limited energy capacity, scarce EV supercharging stations, and long recharging ...
A Decision Function Based Smart Charging and Discharging Strategy for Electric Vehicle in Smart Grid
Abstract
As the number of Electric Vehicle (EV) increases, the uncontrolled EV charging behaviors may cause the grid load fluctuations and other passive effects. In order to balance the EV charging load in the smart grid, an Electric Vehicle Charging and ...
Mobility-Aware Vehicle-to-Grid (V2G) Optimization for Uniform Utilization in Smart Grid Based Power Distribution Network
Abstract
One of the critical bottlenecks of high penetration of Electric Vehicles (EV) is uncoordinated, simultaneous charging of many EVs that can potentially impact the electric distribution grid with unwanted peak load demand. V2G technology enables the ...

Comments

Information & Contributors

Information

Published In

SETN '16: Proceedings of the 9th Hellenic Conference on Artificial Intelligence

May 2016

249 pages

ISBN:9781450337342

DOI:10.1145/2903220

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

EETN: Hellenic Artificial Intelligence Society

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 May 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper
Research
Refereed limited

Conference

SETN '16

SETN '16: 9th Hellenic Conference on Artificial Intelligence

May 18 - 20, 2016

Thessaloniki, Greece

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
128
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)0

Reflects downloads up to 27 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Frendo OGaertner NStuckenschmidt H(2021)Open Source Algorithm for Smart Charging of Electric Vehicle FleetsIEEE Transactions on Industrial Informatics10.1109/TII.2020.303814417:9(6014-6022)Online publication date: Sep-2021
https://doi.org/10.1109/TII.2020.3038144
Sun ZZhao CYan Z(2018)An Optimizing Power System Dispatch with An Extra EV Load Using PLEXOS Appoach2018 China International Conference on Electricity Distribution (CICED)10.1109/CICED.2018.8592362(162-167)Online publication date: Sep-2018
https://doi.org/10.1109/CICED.2018.8592362

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Recommendations

Electric Vehicle Optimized Charge and Drive Management

A Decision Function Based Smart Charging and Discharging Strategy for Electric Vehicle in Smart Grid

Mobility-Aware Vehicle-to-Grid (V2G) Optimization for Uniform Utilization in Smart Grid Based Power Distribution Network

Comments

Information

Published In

In-Cooperation

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations