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Rodrigo F. Calili

Publications and source records attributed to Rodrigo F. Calili.

2 recordsLinked to original sources

An integer programming model for the selection of pumped-hydro storage projects

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.

math.OC

Simulation of the energy efficiency auction prices in Brazil

The electricity consumption behavior in Brazil has been extensively investigated over the years due to financial and social problems. In this context, it is important to simulate the energy prices of the energy efficiency auctions in the Brazilian regulated environment. This paper presents an approach to generate samples of auction energy prices in energy efficiency market, using Markov chain Monte Carlo method, through the Metropolis-Hastings algorithm. The obtained results show that this approach can be used to generate energy price samples.

stat.AP