Authors:
Ebisa Negeri
and
Nico Baken
Affiliation:
Delft University of Technology, Netherlands
Keyword(s):
Smart Grid, Load Balancing, Distributed Generation, Electric Vehicle.
Related
Ontology
Subjects/Areas/Topics:
Energy and Economy
;
Load Balancing in Smart Grids
;
Smart Grids
Abstract:
With increasing penetrations of renewable distributed generations (DGs) and electrified vehicles (EVs), the
volatility of the renewable sources and the huge load of the EVs induce tremendous challenges for the power
grid. The two technologies also have considerable synergetic potential to alleviate these challenges if they are
intelligently coordinated. The aim of this paper is to investigate how the (dis)charging of EVs could be intelligently
coordinated with the production of the local DGs to reduce the peak load on the power grid. We consider
a neighborhood energy community that is composed of prosumer households. Three EV (dis)charging scenarios
are compared: the dumb strategy where all EVs are charged for the next commute as soon as they return
from the previous commute, the centralized (dis)charging strategy where the EVs are managed by a centralized
scheduling unit, and the distributed (dis)charging strategy where the households autonomously schedule
their EVs while coordinati
on is achieved through providing dynamic pricing based incentives. Our simulation
results show that the distributed and centralized charging strategies can reduce the peak load up to 44.9%
and 75.1%, respectively, compared to the dumb charging strategy. Moreover, the relative performnce of the
algorithms with respect to environmental values.
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