Authors:
Jânio Monteiro
1
and
Mário S. Nunes
2
Affiliations:
1
INESC-ID and University of Algarve, Portugal
;
2
INESC-ID, Portugal
Keyword(s):
Smart Grids, Plug-in Electrical Vehicles, Charge Scheduling, Renewable Sources.
Related
Ontology
Subjects/Areas/Topics:
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Systems Modeling and Simulation
Abstract:
The number of Electric Vehicles is estimated to continuously rise over the next years. While this trend is
expected to lead to a reduction in CO2 emission, existing electrical grids have not been planned to support a
large number of electrical vehicle’s batteries charging simultaneously. The integration of distributed
production using renewable energy sources is seen as a solution to meet the requirements of battery
charging. Renewable sources are however affected by variation and lack of predictability, due to the
environmental factors they depend on, which are the cause of inefficiencies and mismatches in the required
demand-response equilibrium. In these conditions, the model and the associated scheduling algorithms to
use in medium to large charging parks play an important role, due to the implications it has in their
operational costs and in the maximization of the return of investments made in renewable sources. In this
paper we propose and evaluate a charging model that engage
s users to participate in demand response
measures, by giving them the ability of selecting two energy components for the charging of their electrical
vehicles, one of which varies according with the variable nature of renewable sources. Based in this model
we propose one scheduling algorithm and compare it with several other solutions, demonstrating that the
proposed solution is able of achieving a significant cost reduction with significant low computational
complexity and processing times, while achieving a high ratio of renewable energy usage.
(More)