Water Resources Research, 2022
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. An integer programming model with an objective function based on costs is proposed to select pumped‐hydro storage sites Two heuristics are used to speed up the solution processes. The case study shows the benefit of these heuristics An application selects PHS projects next to the reservoir of the Sobradinho hydropower plant in Brazil varying head and operation time An integer programming model with an objective function based on costs is proposed to select pumped‐hydro storage sites Two heuristics are used to speed up the solution processes. The case study shows the benefit of these heuristics An application selects PHS projects next to the reservoir of the Sobradinho hydropower plant in Brazil varying head and operation time.
