  In metropolitan areas populated with commercial buildings, electric power
supply is stringent especially during business hours. Demand side management
using battery is a promising solution to mitigate peak demands, however long
payback time creates barriers for large scale adoption. In this paper, we have
developed a design phase battery life-cycle cost assessment tool and a runtime
controller for the building owners, taking into account the degradation of
battery. In the design phase, perfect knowledge on building load profile is
assumed to estimate ideal payback time. In runtime, stochastic programming and
load predictions are applied to address the uncertainties in loads for
producing optimal battery operation. For validation, we have performed
numerical experiments using the real-life tariff model serves New York City,
Zn/MnO2 battery, and state-of-the-art building simulation tool. Experimental
results shows a small gap between design phase assessment and runtime control.
To further examine the proposed methods, we have applied the same tariff model
and performed numerical experiments on nine weather zones and three types of
commercial buildings. On contrary to the common practice of shallow discharging
battery for preventing phenomenal degradation, experimental results show
promising payback time achieved by optimally deep discharge a battery.
