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2020-11-02
Carvalho, Martha R, Bezerra, Bernardo, Dall'Orto, Celso, Carlos, Luiz, Rosenblatt, Jose, Veiga, Mario.  2018.  Methodology for determining the energy deficit penalty function for hydrothermal dispatch. 2018 Simposio Brasileiro de Sistemas Eletricos (SBSE). :1—6.
The penalization of the objective function due to energy deficits is a key element for determining the operational policy of hydroelectric reservoirs. Its definition impacts not only operations, but also system expansion. Brazil historically defined these penalties with basis on a proxy of the economic deficit cost, a value in \$/MWh obtained with aid of the Input-Output Matrix. We propose an approach where these penalties are obtained in order to minimize the operation cost and cost of rationing of the system, considering a criterion of security of supply. A case study with data from the Brazilian System illustrates its application.
2019-10-28
Ocaña, Kary, Galheigo, Marcelo, Osthoff, Carla, Gadelha, Luiz, Gomes, Antônio Tadeu A., De Oliveira, Daniel, Porto, Fabio, Vasconcelos, Ana Tereza.  2019.  Towards a Science Gateway for Bioinformatics: Experiences in the Brazilian System of High Performance Computing. 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). :638–647.

Science gateways bring out the possibility of reproducible science as they are integrated into reusable techniques, data and workflow management systems, security mechanisms, and high performance computing (HPC). We introduce BioinfoPortal, a science gateway that integrates a suite of different bioinformatics applications using HPC and data management resources provided by the Brazilian National HPC System (SINAPAD). BioinfoPortal follows the Software as a Service (SaaS) model and the web server is freely available for academic use. The goal of this paper is to describe the science gateway and its usage, addressing challenges of designing a multiuser computational platform for parallel/distributed executions of large-scale bioinformatics applications using the Brazilian HPC resources. We also present a study of performance and scalability of some bioinformatics applications executed in the HPC environments and perform machine learning analyses for predicting features for the HPC allocation/usage that could better perform the bioinformatics applications via BioinfoPortal.