Stochastic sizing and siting of grid-scale energy storage under network-constrained hydrothermal unit commitment

This paper proposes a stochastic mixed-integer linear programming model for the optimal sizing and siting (OSS) of grid-scale energy storage systems (ESS). The proposed model considers the network-constrained hydrothermal unit commitment formulation and uncertainties in load demand and in the generation of wind and solar power plants. The model stands out by representing water travel times and the cascade coupling of hydro power plants. The proposed methodology is evaluated using a modified IEEE 24-bus test system. Numerical results demonstrate that allocating 300 MW and 1500 MWh of grid-scale ESS capacity reduces the expected annual operational cost from 55.11 M$ to 50.00 M$. Sensitivity analyses evaluate the impact of grid-scale ESS investment costs, technical parameters of the grid-scale ESS, and renewable energy penetration on the optimal sizing and siting decisions.