Maximum penetration of microgeneration photovoltaic panels in distribution network

In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.

A influência da massagem na sensação retardada de desconforto muscular

Introdução: Apesar dos muitos estudos sobre a temática da sensação retardada de desconforto muscular, atualmente, ainda se discute a explicação dos mecanismos subjacentes a esta condição clínica, bem como, a sua prevenção e tratamento. A literatura sugere a massagem como uma das formas de terapia, contudo, os estudos têm mostrado resultados controversos. Objetivo: Verificar se a massagem aplicada 2 horas após um protocolo de exercício excêntrico tem influência na sensação retardada de desconforto muscular, bem como, se o seu efeito varia dependendo do tempo de aplicação. Métodos: 21 participantes (23,62±1,32 anos; 76,95±12,17 kg; 174,71±4,78 cm; 25,25±4,26 Kg/m 2) foram divididos em três grupos. Foi avaliada a dor, força muscular e a perimetria antes, e 2h, 24h, 48h, e 72h após um protocolo de exercício constituído por três séries de dez repetições de contrações excêntricas dos isquiotibiais do membro dominante, com 80% da força máxima, a uma velocidade constante de 60º/s, numa amplitude entre 0º e 80º, utilizando o dinamómetro isocinético Biodex System 4. A massagem foi efetuada 2 horas após o exercício em dois grupos experimentais com durações diferentes, sendo o terceiro grupo de controlo. Para identificar diferenças entre os grupos no momento inicial e na variável diferença entre o momento inicial e os restantes momentos, recorreu-se ao teste de Kruskal-Wallis, seguido de uma análise Post-Hoc através do teste de Dunn com um nível de significância de 0,05. Resultados: Verificou-se que a massagem teve efeito na redução da dor e na perimetria. Relativamente à força não foram encontradas alterações significativas. Conclusão: Os resultados mostraram que a massagem aplicada 2 horas após o exercício excêntrico, independentemente da duração utilizada, teve efeito na redução da dor, mas não na força muscular. Na perimetria apesar de haver alterações, estas não foram consideradas relevantes.

Maximum-revenue tariff under Bertrand duopoly with unknown costs

This paper considers an international trade under Bertrand model with differentiated products and with unknown production costs. The home government imposes a specific import tariff per unit of imports from the foreign firm. We prove that this tariff is decreasing in the expected production costs of the foreign firm and increasing in the production costs of the home firm. Furthermore, it is increasing in the degree of product substitutability. We also show that an increase in the tariff results in both firms increasing their prices, an increase in both expected sales and expected profits for the home firm, and a decrease in both expected sales and expected profits for the foreign firm.

Maximum-revenue tariff with different roles in a price-setting competition

Published also at Lecture Notes in Engineering and Computer Science

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.