27 resultados para Set planning groups


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Pós-graduação em Ciências Biológicas (Biologia Celular e Molecular) - IBRC

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Pós-graduação em Odontologia Preventiva e Social - FOA

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Pós-graduação em Serviço Social - FCHS

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Pós-graduação em Geociências e Meio Ambiente - IGCE

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The hydroelectric power plant Hidroltuango represents a major expansion for the Colombian electrical system (with a total capacity of 2400 MW). This paper analyzes the possible interconnections and investments involved in connecting Hidroltuango, in order to strengthen the Colombian national transmission system. A Mixed Binary Linear Programming (MBLP) model was used to solve the Multistage Transmission Network Expansion Planning (MTEP) problem of the Colombian electrical system, taking the N-1 safety criterion into account. The N-1 safety criterion indicates that the transmission system must be expanded so that the system will continue to operate properly if an outage in a system element (within a pre-defined set of contingencies) occurs. The use of a MBLP model guaranteed the convergence with existing classical optimization methods and the optimal solution for the MTEP using commercial solvers. Multiple scenarios for generation and demand were used to consider uncertainties within these parameters. The model was implemented using the algebraic modeling language AMPL and solved using the commercial solver CPLEX. The proposed model was then applied to the Colombian electrical system using the planning horizon of 2018-2025. (C) 2014 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Diagnosis and planning stages are critical to the success of orthodontic treatment, in which the orthodontist should have many elements that contribute to the most appropriate decision-making. The orthodontic set-up is an important resource in the planning of corrective orthodontics therapy. It consists of the repositioning of the teeth previously removed from the study dental casts and reassembled on its remaining basis. When properly made, the set-up allows a three-dimensional preview of problems and limitations of the case, assisting in decision-making regarding tooth extractions in cases with problems of space, amount of anchorage loss extent and type of tooth movement, discrepancy of dental arch perimeter, discrepancy of inter-arch tooth volume, among others, indicating the best option for treatment. This paper outlines the most important steps for its confection, an evaluation system and its application in the preparation of orthodontic treatment planning.

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Diagnosis and planning stages are critical to the success of orthodontic treatment, in which the orthodontist should have many elements that contribute to the most appropriate decision-making. The orthodontic set-up is an important resource in the planning of corrective orthodontics therapy. It consists of the repositioning of the teeth previously removed from the study dental casts and reassembled on its remaining basis. When properly made, the set-up allows a three-dimensional preview of problems and limitations of the case, assisting in decision-making regarding tooth extractions in cases with problems of space, amount of anchorage loss extent and type of tooth movement, discrepancy of dental arch perimeter, discrepancy of inter-arch tooth volume, among others, indicating the best option for treatment. This paper outlines the most important steps for its confection, an evaluation system and its application in the preparation of orthodontic treatment planning.

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This paper presents a mixed-integer convex-optimization-based approach for optimum investment reactive power sources in transmission systems. Unlike some convex-optimization techniques for the reactive power planning solution, in the proposed approach the taps settings of under-load tap-changing of transformers are modeled as a mixed-integer linear set equations. Are also considered the continuous and discrete variables for the existing and new capacitive and reactive power sources. The problem is solved for three significant demand scenarios (low demand, average demand and peak demand). Numerical results are presented for the CIGRE-32 electric power system.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)