  Energy storage is expected to play an increasingly important role in
mitigating variations that come along with the growing penetration of renewable
energy. In this paper, we study the optimal bidding of an energy storage unit
in a semi-centralized market. The energy storage unit offers its available
storage capacity and maximum charging/discharging rate to the operator; then
the operator clears the real-time market by minimizing the total cost. The
energy storage unit is paid/charged at locational marginal price (LMP). The
problem casts down to a bilevel optimization problem with a mixed-integer
lower-level. An improved surrogate-based method with the combined
spatial-temporal entropy term is developed to solve this problem. Numerical
examples demonstrate the scalability, efficiency, and accuracy of the proposed
method.
