A Distributed In-Transit Processing Infrastructure for Forecasting Electric Vehicle Charging Demand - Université de Pau et des Pays de l'Adour Access content directly
Conference Papers Year : 2013

A Distributed In-Transit Processing Infrastructure for Forecasting Electric Vehicle Charging Demand

Abstract

With an increasing interest in Electric Vehicles (EVs), it is essential to understand how EV charging could impact demand on the Electricity Grid. Existing approaches used to achieve this make use of a centralised data collection mechanism - which often is agnostic of demand variation in a given geographical area. We present an in-transit data processing architecture that is more efficient and can aggregate a variety of different types of data. A model using Reference nets has been developed and evaluated. Our focus in this paper is primarily to introduce requirements for such an architecture. \textcopyright 2013 IEEE.

Dates and versions

hal-01912937 , version 1 (05-11-2018)

Identifiers

Cite

Rafael Tolosana-Calasanz, José Ángel Bañares, Liana Cipcigan, Omer F. Rana, Panagiotis Papadopoulos, et al.. A Distributed In-Transit Processing Infrastructure for Forecasting Electric Vehicle Charging Demand. 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2013, Delft, Netherlands, May 13-16, 2013, 2013, Unknown, Unknown Region. pp.538--545, ⟨10.1109/CCGrid.2013.103⟩. ⟨hal-01912937⟩

Collections

UNIV-PAU LIUPPA
20 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More