165 resultados para Multi- Choice mixed integer goal programming


Relevância:

100.00% 100.00%

Publicador:

Resumo:

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

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Pós-graduação em Engenharia Elétrica - FEIS

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Pós-graduação em Engenharia Mecânica - FEG

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Pós-graduação em Engenharia Elétrica - FEIS

Relevância:

100.00% 100.00%

Publicador:

Resumo:

In this paper, the optimal reactive power planning problem under risk is presented. The classical mixed-integer nonlinear model for reactive power planning is expanded into two stage stochastic model considering risk. This new model considers uncertainty on the demand load. The risk is quantified by a factor introduced into the objective function and is identified as the variance of the random variables. Finally numerical results illustrate the performance of the proposed model, that is applied to IEEE 30-bus test system to determine optimal amount and location for reactive power expansion.

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Pós-graduação em Engenharia Elétrica - FEIS

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Pós-graduação em Engenharia Elétrica - FEIS

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relevância:

100.00% 100.00%

Publicador:

Resumo:

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

Relevância:

100.00% 100.00%

Publicador:

Resumo:

One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.