Improving the grid operation and reliability cost of distribution systems with dispersed generation

In this work, a mathematical model to analyze the impact of the installation and operation of dispersed generation units in power distribution systems is proposed. The main focus is to determine the trade-off between the reliability and operational costs of distribution networks when the operation of isolated areas is allowed. In order to increase the system operator revenue, an optimal power flow makes use of the different energy prices offered by the dispersed generation connected to the grid. Simultaneously, the type and location of the protective devices initially installed on the protection system are reconfigured in order to minimize the interruption and expenditure of adjusting the protection system to conditions imposed by the operation of dispersed units. The interruption cost regards the unsupplied energy to customers in secure systems but affected by the normal tripping of protective devices. Therefore, the tripping of fuses, reclosers, and overcurrent relays aims to protect the system against both temporary and permanent fault types. Additionally, in order to reduce the average duration of the system interruption experienced by customers, the isolated operation of dispersed generation is allowed by installing directional overcurrent relays with synchronized reclose capabilities. A 135-bus real distribution system is used in order to show the advantages of using the mathematical model proposed. © 1969-2012 IEEE.

Association between energy cost of walking, muscle activation, and biomechanical parameters in older female fallers and non-fallers

Objective: To determine the nervous activation, muscle strength, and biomechanical parameters that influence the cost of walking in older fallers and non-fallers. Methods: Maximal voluntary isokinetic torque was measured for the hip, knee and ankle of older women. Oxygen consumption was measured at rest and during 8 min of walking at self-selected speed. An additional minute of walking was performed to collect kinematic variables and the electromyographic signal of trunk, hip, knee, and ankle muscles, which was analyzed by the linear envelope. Cost of walking was calculated by subtracting resting body mass-normalized oxygen consumption from walking body mass-normalized oxygen consumption. Stride time and length, and ankle and hip range of motion were calculated from kinematic data. Findings: Older adult fallers had 28% lower knee extensor strength (p = 0.02), 47% lower internal oblique activation at heel contact (p = 0.03), and higher coactivation between tibialis anterior and gastrocnemius lateralis in each of the gait phases (p < 0.05). For fallers, a higher activation of gluteus maximus was associated with a higher cost of walking (r = 0.55, p < 0.05 and r = 0.71, p < 0.01, before and after heel contact, respectively). For non-fallers, an association between cost of walking and age (r = 0.60, p = 0.01) and cost of walking and thigh muscle coactivation (r = 0.53, p = 0.01) existed. Interpretation: This study demonstrated that there may be links between lower-extremity muscle weakness, muscle activation patterns, altered gait, and increased cost of walking in older fallers. © 2013 Elsevier Ltd. All rights reserved.

Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network

In this paper, a search for supersymmetry (SUSY) is presented in events with two opposite-sign isolated leptons in the final state, accompanied by hadronic jets and missing transverse energy. An artificial neural network is employed to discriminate possible SUSY signals from a standard model background. The analysis uses a data sample collected with the CMS detector during the 2011 LHC run, corresponding to an integrated luminosity of 4.98 fb-1 of proton-proton collisions at the center-of-mass energy of 7 TeV. Compared to other CMS analyses, this one uses relaxed criteria on missing transverse energy (EÌ̧T>40 GeV) and total hadronic transverse energy (HT>120 GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observations, yielding limits in the context of the constrained minimal supersymmetric standard model and on a set of simplified models. © 2013 CERN.

Artificial neural network model of discharge lamps in the power quality context

This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of distribution systems, facing events related to power quality. With the aid of a data acquisition system to monitor the laboratory experiment, and using $$\text{ MATLAB }^{\textregistered }$$ software, data was obtained for the training of two neural networks. These neural networks, working together, were able to represent with high fidelity the behavior of a discharge lamp. The excellent performance obtained by these models allowed the simulation of a group of lamps in a distribution system with shorter simulation time when compared to mathematical models. This fact justified the application of this family of loads in electric power systems. The representation of the device facing power quality disturbances also proved to be a useful tool for more complex studies in distribution systems. © 2013 Brazilian Society for Automatics - SBA.

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Proposta de uma abordagem metodológica para analisar como os fatores posicionais influenciam as prioridades competitivas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An assessment of the economic and social impacts of climate change on the energy sector in the Caribbean

The present report assesses the economic and social impacts of climate change on the energy sector in Antigua and Barbuda, the Bahamas, Barbados, Belize, Cuba, Dominica, the Dominican Republic, Haiti, Grenada, Guyana, Jamaica, Saint Kitts and Nevis, Saint Vincent and the Grenadines, Saint Lucia, Suriname, and Trinidad and Tobago. In the study, the Artificial Neural Network methodology was employed to model the relationship between climate change and energy demand. The viability of the actions proposed were assessed using cost benefit analyses based on models from the National Renewable Energy Laboratory (NREL) of the United States of America.

An assessment of global economic models for climate change

The project comprises three phases of which Phase I would be implemented over the period September to December 2008. The major objectives of Phase I are, firstly, to establish the scope and feasibility of carrying out a study on the costs/benefits of taking action on climate change adaptation and cost effectiveness of mitigation in the Caribbean compared to a “business as usual” scenario, and secondly, to support initial actions to alert policymakers and key influencing constituencies to the urgency of this challenge.

Modelo de virtualização distribuída aplicado ao gerenciamento e replicação de cluster multiuso

Pós-graduação em Ciência da Computação - IBILCE

Planejamento de sistemas de distribuição de energia elétrica através de um modelo de Programação Linear Inteiro Misto (plim)

Pós-graduação em Engenharia Elétrica - FEIS

Análise de novos modelos matemáticos para o problema de planejamento da expansão de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

Planejamento de médio e longo prazo de sistemas de distribuição de energia elétrica com geradores distribuídos (GDs) considerando custos de confiabilidade, operação e expansão

Pós-graduação em Engenharia Elétrica - FEIS

Construct validity of behavioral models of anxiety: where experimental psychopathology meets ecology and evolution

In experimental psychopathology, construct validity is usually enhanced by addressing theories from other fields in its nomological network. In the field of anxiety research, this construct is related to antipredator behavior, conserved across phylogeny in its functions and neural basis, but not necessarily on its topography. Even though the relations between behavioral models of anxiety and statements from behavioral ecology and evolutionary biology are commonly made in anxiety research, these are rarely tested, at least explicitly. However, in order to increase construct validity in experimental anxiety, testing predictions from those theories is highly desirable. This article discusses these questions, suggesting a few ways in which behavioral ecological and evolutionary hypotheses of anxiety-like behavior may be tested.

Inferring a weighted elastic network from partial unfolding with coarse-grained simulations

A number of studies have demonstrated that simple elastic network models can reproduce experimental B-factors, providing insights into the structure-function properties of proteins. Here, we report a study on how to improve an elastic network model and explore its performance by predicting the experimental B-factors. Elastic network models are built on the experimental C coordinates, and they only take the pairs of C atoms within a given cutoff distance r(c) into account. These models describe the interactions by elastic springs with the same force constant. We have developed a method based on numerical simulations with a simple coarse-grained force field, to attribute weights to these spring constants. This method considers the time that two C atoms remain connected in the network during partial unfolding, establishing a means of measuring the strength of each link. We examined two different coarse-grained force fields and explored the computation of these weights by unfolding the native structures. Proteins 2014; 82:119-129. (c) 2013 Wiley Periodicals, Inc.

Search for Gravitational Waves Associated with gamma-ray Bursts Detected by the Interplanetary Network

We present the results of a search for gravitational waves associated with 223 gamma-ray bursts (GRBs) detected by the InterPlanetary Network (IPN) in 2005-2010 during LIGO's fifth and sixth science runs and Virgo's first, second, and third science runs. The IPN satellites provide accurate times of the bursts and sky localizations that vary significantly from degree scale to hundreds of square degrees. We search for both a well-modeled binary coalescence signal, the favored progenitor model for short GRBs, and for generic, unmodeled gravitational wave bursts. Both searches use the event time and sky localization to improve the gravitational wave search sensitivity as compared to corresponding all-time, all-sky searches. We find no evidence of a gravitational wave signal associated with any of the IPN GRBs in the sample, nor do we find evidence for a population of weak gravitational wave signals associated with the GRBs. For all IPN-detected GRBs, for which a sufficient duration of quality gravitational wave data are available, we place lower bounds on the distance to the source in accordance with an optimistic assumption of gravitational wave emission energy of 10(-2)M(circle dot)c(2) at 150 Hz, and find a median of 13 Mpc. For the 27 short-hard GRBs we place 90% confidence exclusion distances to two source models: a binary neutron star coalescence, with a median distance of 12 Mpc, or the coalescence of a neutron star and black hole, with a median distance of 22 Mpc. Finally, we combine this search with previously published results to provide a population statement for GRB searches in first-generation LIGO and Virgo gravitational wave detectors and a resulting examination of prospects for the advanced gravitational wave detectors.