  Energy storage systems - in particular, Pumped Hydropower Storage (PHS) -
will be increasingly important to support the transition of power systems
toward zero emissions. The reason is that PHS can mitigate the variability and
uncertainty of renewable energy production from solar and wind power to balance
electricity demand with supply. In this paper, we propose an integer
programming problem for PHS siting that uses a Digital Elevation Model (DEM) to
meet an energy storage requirement. It assumes the existence of a reservoir,
lake, or river, and decides where to build a reservoir that will constitute the
PHS with the existing body of water. This model finds minimum-cost project
candidates given parameters such as desired head, power, and operation time.
The paper discusses different solution methods to assure reservoir closure and
avoid its fragmentation. A heuristic explores the representations of the DEM,
from more aggregate to more precise, to sequentially refine the solution based
on the last selected site, which reduces computational effort. The formulation
is general and the objective function includes both construction and equipment
costs. Constraints are related to the energy storage target and reservoir
closure based on the DEM. We illustrate the methodology by selecting multiple
PHS projects next to the reservoir of the Sobradinho hydropower plant in
Brazil. The result of this model can be seen as a bottom-up step that prepares
PHS candidate projects to be considered by an integrated resource planning
model in a top-down step, that would select from these shortlisted projects.
