  This paper introduces a mathematical formulation of energy storage systems
into a generation capacity expansion framework to evaluate the role of energy
storage in the decarbonization of distributed power systems. The modeling
framework accounts for dynamic charging/discharging efficiencies and maximum
cycling powers as well as cycle and calendar degradation of a Li-ion battery
system. Results from a small-scale distributed power system indicate that
incorporating the dynamic efficiencies and cycling powers of batteries in the
generation planning problem does not significantly change the optimal
generation portfolio, while adding substantial computational burden. In
contrast, accounting for battery degradation leads to substantially different
generation expansion outcomes, especially in deep decarbonization scenarios
with larger energy storage capacities. Under the assumptions used in this
study, it is found that battery energy storage is economically viable for 2020
only under strict carbon emission constraints. In contrast, given the projected
technology advances and corresponding cost reductions, battery energy storage
exhibits an attractive option to enable deep decarbonization in 2050.
