1 research outputs found
Distributed Control for Charging Multiple Electric Vehicles with Overload Limitation
Severe pollution induced by traditional fossil fuels arouses great attention
on the usage of plug-in electric vehicles (PEVs) and renewable energy. However,
large-scale penetration of PEVs combined with other kinds of appliances tends
to cause excessive or even disastrous burden on the power grid, especially
during peak hours. This paper focuses on the scheduling of PEVs charging
process among different charging stations and each station can be supplied by
both renewable energy generators and a distribution network. The distribution
network also powers some uncontrollable loads. In order to minimize the on-grid
energy cost with local renewable energy and non-ideal storage while avoiding
the overload risk of the distribution network, an online algorithm consisting
of scheduling the charging of PEVs and energy management of charging stations
is developed based on Lyapunov optimization and Lagrange dual decomposition
techniques. The algorithm can satisfy the random charging requests from PEVs
with provable performance. Simulation results with real data demonstrate that
the proposed algorithm can decrease the time-average cost of stations while
avoiding overload in the distribution network in the presence of random
uncontrollable loads.Comment: 30 pages, 13 figure