Robust unit commitment with large-scale battery storage

As the renewable energy levels are constantly increasing, scheduling of generating units in the day ahead stage is becoming more challenging for system operators. Energy storage is emerging as an attractive solution for dealing with uncertainty and variability of renewable generation. Specifically, large-scale battery storage units are gaining popularity due to their modularity, fast response and ongoing cost reduction. In this paper we model a two-stage adaptive robust unit commitment model with large-scale energy storage. The objective is to minimize the operating costs of thermal generators under the worst wind power output scenario. The over-protection is addressed using a parameter that controls the conservatism of the model. This control parameter can be extended to cover the uncertainty more realistically using multiple bands as the time horizon progresses. The proposed model is tested on an updated IEEE RTS-96 system. Different levels of protecting the system against uncertainty are evaluated and the role of energy storage is analyzed.