7 resultados para Distribution de Pareto

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Um evento extremo de precipitação ocorreu na primeira semana do ano 2000, de 1º a 5 de janeiro, no Vale do Paraíba, parte leste do Estado de São Paulo, Brasil, causando enorme impacto socioeconômico, com mortes e destruição. Este trabalho estudou este evento em 10 estações meteorológicas selecionadas que foram consideradas como aquelas tendo dados mais homogêneos do Que outras estações na região. O modelo de distribuição generalizada de Pareto (DGP) para valores extremos de precipitação de 5 dias foi desenvolvido, individualmente para cada uma dessas estações. Na modelagem da DGP, foi adotada abordagem não-estacionaria considerando o ciclo anual e tendência de longo prazo como co-variaveis. Uma conclusão desta investigação é que as quantidades de precipitação acumulada durante os 5 dias do evento estudado podem ser classificadas como extremamente raras para a região, com probabilidade de ocorrência menor do que 1% para maioria das estações, e menor do que 0,1% em três estações.

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This paper proposes an alternative codification to solve the service restoration in electric power distribution networks using a SPEA2 multiobjective evolutionary algorithm, assuming the minimization of both the load not supplied and the number of switching operations involved in the restoration plan. Constrains as the line, power source and voltage drop limits in order to avoid the activation of protective devices are all included in the proposed algorithm. Experimental results have shown the convenience on considering these new representations in the sense of feasibility maintenance and also in the sense of better approximation to the Pareto set. ©2009 IEEE.

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This paper presents a mixed-integer linear programming model to solve the conductor size selection and reconductoring problem in radial distribution systems. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. The proposed model and a heuristic are used to obtain the Pareto front of the conductor size selection and reconductoring problem considering two different objective functions. The results of one test system and two real distribution systems are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 1969-2012 IEEE.

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This paper presents a mixed-integer linear programming model to solve the problem of allocating voltage regulators and fixed or switched capacitors (VRCs) in radial distribution systems. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. An heuristic to obtain the Pareto front for the multiobjective VRCs allocation problem is also presented. © 2012 Elsevier Ltd. All rights reserved.

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The capacitated redistricting problem (CRP) has the objective to redefine, under a given criterion, an initial set of districts of an urban area represented by a geographic network. Each node in the network has different types of demands and each district has a limited capacity. Real-world applications consider more than one criteria in the design of the districts, leading to a multicriteria CRP (MCRP). Examples are found in political districting, sales design, street sweeping, garbage collection and mail delivery. This work addresses the MCRP applied to power meter reading and two criteria are considered: compactness and homogeneity of districts. The proposed solution framework is based on a greedy randomized adaptive search procedure and multicriteria scalarization techniques to approximate the Pareto frontier. The computational experiments show the effectiveness of the method for a set of randomly generated networks and for a real-world network extracted from the city of São Paulo. © 2013 Elsevier Ltd.