EconPapers    
Economics at your fingertips  
 

Real-Time Forecasting of EV Charging Station Scheduling for Smart Energy Systems

Bharatiraja Chokkalingam, Sanjeevikumar Padmanaban, Pierluigi Siano, Ramesh Krishnamoorthy and Raghu Selvaraj
Additional contact information
Bharatiraja Chokkalingam: Department of Electrical and Electronics Engineering, SRM University, Chennai 603 203, India
Sanjeevikumar Padmanaban: Department of Electrical and Electronics Engineering, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa
Pierluigi Siano: Department of Industrial Engineering, University of Salerno, Salerno 84084, Italy
Ramesh Krishnamoorthy: Department of Electronics and Communication Engineering, SRM University, Chennai 603 203, India
Raghu Selvaraj: Department of Water Resource Development and Management, Indian Institute of Technology, Roorkee 247 667, India

Energies, 2017, vol. 10, issue 3, 1-16

Abstract: The enormous growth in the penetration of electric vehicles (EVs), has laid the path to advancements in the charging infrastructure. Connectivity between charging stations is an essential prerequisite for future EV adoption to alleviate user’s “range anxiety”. The existing charging stations fail to adopt power provision, allocation and scheduling management. To improve the existing charging infrastructure, data based on real-time information and availability of reserves at charging stations could be uploaded to the users to help them locate the nearest charging station for an EV. This research article focuses on an a interactive user application developed through SQL and PHP platform to allocate the charging slots based on estimated battery parameters, which uses data communication with charging stations to receive the slot availability information. The proposed server-based real-time forecast charging infrastructure avoids waiting times and its scheduling management efficiently prevents the EV from halting on the road due to battery drain out. The proposed model is implemented using a low-cost microcontroller and the system etiquette tested.

Keywords: electric vehicle (EV); charging station (CS); state of charge (SOC); structured query language (SQL); personal home page (PHP) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/3/377/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/3/377/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:10:y:2017:i:3:p:377-:d:93207

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-24
Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:377-:d:93207