11 resultados para Power distributions
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
Resumo:
This paper proposes a dedicated algorithm for lation of single line-to-ground faults in distribution systems. The proposed algorithm uses voltage and current phasors measured at the substation level, voltage magnitudes measured at some buses of the feeder, a database containing electrical, operational and topological parameters of the distribution networks, and fault simulation. Voltage measurements can be obtained using power quality devices already installed on the feeders or using voltage measurement devices dedicated for fault location. Using the proposed algorithm, likely faulted points that are located on feeder laterals geographically far from the actual faulted point are excluded from the results. Assessment of the algorithm efficiency was carried out using a 238 buses real-life distribution feeder. The results show that the proposed algorithm is robust for performing fast and efficient fault location for sustained single line-to-ground faults requiring less than 5% of the feeder buses to be covered by voltage measurement devices. © 2006 IEEE.
Resumo:
The number of citations of a scientific publication or of an individual scientist has become an important factor of quality assessment in science. We report a study of the statistical distribution of the citation index of both scientific publications and scientists. We give numerical evidence that Tsallis (power law) statistics explains the entire distribution over eight orders of magnitude (10-4 to 10(4)). Also, we draw Zipf plots in order to analyze the statistical distribution of the citation index of Brazilian and international physicists and chemists. The relatively small group of Brazilian scientists seems more adequate to explain the dynamics of the citation index. In this case, we find that the distribution of the citation index can also be explained by a gradually truncated power law with similar parameters. We finally discuss possible mechanisms behind the citation index of scientists and scientific publications.
Resumo:
Power-law distributions have been observed in various economical and physical systems. Levy flights have infinite variance which discourage a physical approach. We introduce a class of stochastic processes, the gradually truncated Levy flight in which large steps of a Levy flight are gradually eliminated. It has finite variance and the system can be analyzed in a closed form. We applied the present method to explain the distribution of a particular economical index. The present method can be applied to describe time series in a variety of fields, i.e. turbulent flow, anomalous diffusion, polymers, etc. (C) 1999 Elsevier B.V. B.V. All rights reserved.
Resumo:
In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.
Resumo:
Direct-sampling and remote-sensing measurements were made at the crater rim of Masaya volcano (Nicaragua) to sample the aerosol plume emanating from the active vent. We report the first measurements of the size distribution of fine silicate particles (d <10 mu m) in Masaya's plume, by automated scanning electron microscopy (QEMSCAN) analysis of a particle filter. The particle size distribution was approximately lognormal with modal d similar to 1.15 mu m. The majority of these particles were found to be spherical. These particles are interpreted to be droplets of quenched magma produced by a spattering process. Compositional analyses confirm earlier reports that the fine silicate particles show a range of compositions between that of the degassing magma and nearly pure silica and that the extent of compositional variability decreases with increasing particle size. These results indicate that fine silicate particles are altered owing to reactions with acidic droplets in the plume. The emission flux of fine silicate particles was estimated as similar to 10(11) s(-1), equivalent to similar to 55 kg d(-1). Sun photometry, aerosol spectrometry, and thermal precipitation were used to determine the overall particle size distribution of the plume (0.01 < d(mu m) < 10). Sun photometry and aerosol spectrometry measurements indicate the presence of a large number of particles (assumed to be aqueous) with d similar to 1 mu m. Aerosol spectrometry measurements further show an increase in particle size as the nighttime approached. The emission flux of particles from Masaya was estimated as similar to 10(17) s(-1), equivalent to similar to 5.5 Mg d(-1) where d < 4 mu m.
Resumo:
Particle size distributions for soluble and insoluble species in Mt. Etna's summit plumes were measured across an extended size range (10 nm < d < 100 mu m) using a combination of techniques. Automated scanning electron microscopy (QEMSCAN) was used to chemically analyze many thousands of insoluble particles (collected on pumped filters) allowing the relationships between particle size, shape, and composition to be investigated. The size distribution of fine silicate particles (d < 10 mu m) was found to be lognormal, consistent with formation by bursting of gas bubbles at the surface of the magma. The compositions of fine silicate particles were found to vary between magmatic and nearly pure silica; this is consistent with depletion of metal ions by reactions in the acidic environment of the gas plume and vent. Measurements of the size, shape and composition of fine silicate particles may potentially offer insights into preemission, synemission, and postemission processes. The mass flux of fine silicate particles from Mt. Etna released during noneruptive volcanic degassing in 2004 and 2005 was estimated to be similar to 7000 kg d(-1). Analysis of particles in the range 0.1 < d/mu m < 100 by ion chromatography shows that there are persistent differences in the size distributions of sulfate aerosols between the two main summit plumes. Analysis of particles in the range 0.01 mu m < d < 0.1 mu m by scanning transmission electron microscopy (STEM) shows that there are significant levels of nanoparticles in the Mt. Etna plumes although their compositions remain uncertain.
Resumo:
We studied the statistical distribution of student's performance, which is measured through their marks, in university entrance examination (Vestibular) of UNESP (Universidade Estadual Paulista) with respect to (i) period of study - day versus night period (ii) teaching conditions - private versus public school (iii) economical conditions - high versus low family income. We observed long ubiquitous power law tails in physical and biological sciences in all cases. The mean value increases with better study conditions followed by better teaching and economical conditions. In humanities, the distribution is close to normal distribution with very small tail. This indicates that these power law tails in science subjects axe due to the nature of the subjects themselves. Further and better study, teaching and economical conditions axe more important for physical and biological sciences in comparison to humanities at this level of study. We explain these statistical distributions through Gradually Truncated Power law distributions. We discuss the possible reason for this peculiar behavior.
Analytical and Monte Carlo approaches to evaluate probability distributions of interruption duration
Resumo:
Regulatory authorities in many countries, in order to maintain an acceptable balance between appropriate customer service qualities and costs, are introducing a performance-based regulation. These regulations impose penalties-and, in some cases, rewards-that introduce a component of financial risk to an electric power utility due to the uncertainty associated with preserving a specific level of system reliability. In Brazil, for instance, one of the reliability indices receiving special attention by the utilities is the maximum continuous interruption duration (MCID) per customer.This parameter is responsible for the majority of penalties in many electric distribution utilities. This paper describes analytical and Monte Carlo simulation approaches to evaluate probability distributions of interruption duration indices. More emphasis will be given to the development of an analytical method to assess the probability distribution associated with the parameter MCID and the correspond ng penalties. Case studies on a simple distribution network and on a real Brazilian distribution system are presented and discussed.
Resumo:
We studied the statistical distribution of candidate's performance which is measured through their marks in university entrance examination (Vestibular) of UNESP (Universidade Estadual Paulista) for years 1998, 1999, and 2000. All students are divided in three groups: Physical, Biological and Humanities. We paid special attention to the examination of Portuguese language which is common for all and examinations for the particular area. We observed long ubiquitous power law tails in Physical and Biological sciences. This indicate the presence of strong positive feedback in sciences. We are able to explain completely these statistical distributions through Gradually Truncated Power law distributions which we developed recently to explain statistical behavior of financial market. The statistical distribution in case of Portuguese language and humanities is close to normal distribution. We discuss the possible reason for this peculiar behavior.
Resumo:
In this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in a particular area, without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE.
Resumo:
This paper presents an approach for probabilistic analysis of unbalanced three-phase weakly meshed distribution systems considering uncertainty in load demand. In order to achieve high computational efficiency this approach uses both an efficient method for probabilistic analysis and a radial power flow. The probabilistic approach used is the well-known Two-Point Estimate Method. Meanwhile, the compensation-based radial power flow is used in order to extract benefits from the topological characteristics of the distribution systems. The generation model proposed allows modeling either PQ or PV bus on the connection point between the network and the distributed generator. In addition allows control of the generator operating conditions, such as the field current and the power delivery at terminals. Results on test with IEEE 37 bus system is given to illustrate the operation and effectiveness of the proposed approach. A Monte Carlo Simulations method is used to validate the results. © 2011 IEEE.