This paper presents a robust scheduling scheme for
energy storage systems (ESSs) deployed in distribution networks
to facilitate high penetrations of renewable energy sources (RES).
This scheme schedules the charging and discharging of an ESS
cognizant of state-of-charge (SoC) limits, transmission line real
time thermal ratings (RTTR), and voltage constraints. Robust
optimization (RO) has been adopted to deal with the uncertainty
of RES output, load, and RTTR. Two methods have been introduced
to estimate the tradeoff between the cost and the probability
of constraint violations. The proposed scheduling scheme is tested
on the IEEE 14 and 118 busbar networks with real load, generation,
and RTTR profiles through Monte Carlo simulation (MCS).
Test results show that the proposed scheme is able to minimize
or curtail the probability of constraint violation to a desired level.
In contrast, classical optimal power flow (OPF) approaches which
do not consider uncertainty, when coupled with RTTR and ESS,
result in a low PoS. At the same time, compared to conservative
OPF approaches, the proposed scheme reduces the power and
energy requirement of ESS.