Analytical and Monte Carlo approaches to evaluate probability distributions of interruption duration

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.

Discrete coherent states and probability distributions in finite-dimensional spaces

Operator bases are discussed in connection with the construction of phase space representatives of operators in finite-dimensional spaces, and their properties are presented. It is also shown how these operator bases allow for the construction of a finite harmonic oscillator-like coherent state. Creation and annihilation operators for the Fock finite-dimensional space are discussed and their expressions in terms of the operator bases are explicitly written. The relevant finite-dimensional probability distributions are obtained and their limiting behavior for an infinite-dimensional space are calculated which agree with the well known results. (C) 1996 Academic Press, Inc.

Improving methods in gap ecology: Revisiting size and shape distributions using a model selection approach

Questions: We assess gap size and shape distributions, two important descriptors of the forest disturbance regime, by asking: which statistical model best describes gap size distribution; can simple geometric forms adequately describe gap shape; does gap size or shape vary with forest type, gap age or the method used for gap delimitation; and how similar are the studied forests and other tropical and temperate forests? Location: Southeastern Atlantic Forest, Brazil. Methods: Analysing over 150 gaps in two distinct forest types (seasonal and rain forests), a model selection framework was used to select appropriate probability distributions and functions to describe gap size and gap shape. The first was described using univariate probability distributions, whereas the latter was assessed based on the gap area-perimeter relationship. Comparisons of gap size and shape between sites, as well as size and age classes were then made based on the likelihood of models having different assumptions for the values of their parameters. Results: The log-normal distribution was the best descriptor of gap size distribution, independently of the forest type or gap delimitation method. Because gaps became more irregular as they increased in size, all geometric forms (triangle, rectangle and ellipse) were poor descriptors of gap shape. Only when small and large gaps (> 100 or 400m2 depending on the delimitation method) were treated separately did the rectangle and isosceles triangle become accurate predictors of gap shape. Ellipsoidal shapes were poor descriptors. At both sites, gaps were at least 50% longer than they were wide, a finding with important implications for gap microclimate (e.g. light entrance regime) and, consequently, for gap regeneration. Conclusions: In addition to more appropriate descriptions of gap size and shape, the model selection framework used here efficiently provided a means by which to compare the patterns of two different types of forest. With this framework we were able to recommend the log-normal parameters μ and σ for future comparisons of gap size distribution, and to propose possible mechanisms related to random rates of gap expansion and closure. We also showed that gap shape varied highly and that no single geometric form was able to predict the shape of all gaps, the ellipse in particular should no longer be used as a standard gap shape. © 2012 International Association for Vegetation Science.

Alternative distributions to estimate usual intake of nutrients for groups

When assessing food intake patterns in groups of individuals, a major problem is finding usual intake distribution. This study aimed at searching for a probability distribution to estimate the usual intake of nutrients using data from a cross-sectional investigation on nutrition students from a public university in São Paulo state, Brazil. Data on 119 women aged 19 to 30 years old were used. All women answered a questionnaire about their lifestyle, diet and demographics. Food intake was evaluated from a non-consecutive three-day 24-hour food record. Different probability distributions were tested for vitamins C and E, panthotenic acid, folate, zinc, copper and calcium where data normalization was not possible. Empirical comparisons were performed, and inadequacy prevalence was calculated by comparing with the NRC method. It was concluded that if a more realistic distribution for usual intake is found, results can be more accurate as compared to those achieved by other methods.

Spatial distribution of Diaphorina citri Kuwayama (Hemiptera: Psyllidae) in citrus orchards

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Catch-per-unit-effort: which estimator is best?

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Universality of Brunnian (N-body Borromean) four- and five-body systems

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

Effective Fokker-Planck equation for birhythmic modified van der Pol oscillator

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Stability of trapped Bose-Einstein condensates

In three-dimensional trapped Bose-Einstein condensate (BEC), described by the time-dependent Gross-Pitaevskii-Ginzburg equation, we study the effect of initial conditions on stability using a Gaussian variational approach and exact numerical simulations. We also discuss the validity of the criterion for stability suggested by Vakhitov and Kolokolov. The maximum initial chirp (initial focusing defocusing of cloud) that can lead a stable condensate to collapse even before the number of atoms reaches its critical limit is obtained for several specific cases. When we consider two- and three-body nonlinear terms, with negative cubic and positive quintic terms, we have the conditions for the existence of two phases in the condensate. In this case, the magnitude of the oscillations between the two phases are studied considering sufficient large initial chirps. The occurrence of collapse in a BEC with repulsive two-body interaction is also shown to be possible.

Local dimension and finite time prediction in spatiotemporal chaotic systems

Predictability is related to the uncertainty in the outcome of future events during the evolution of the state of a system. The cluster weighted modeling (CWM) is interpreted as a tool to detect such an uncertainty and used it in spatially distributed systems. As such, the simple prediction algorithm in conjunction with the CWM forms a powerful set of methods to relate predictability and dimension.

Chronological Monte Carlo-based assessment of distribution system reliability

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, which 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 per customer (MCID). This paper describes a chronological Monte Carlo simulation approach to evaluate probability distributions of reliability indices, including the MCID, and the corresponding penalties. In order to get the desired efficiency, modern computational techniques are used for modeling (UML -Unified Modeling Language) as well as for programming (Object- Oriented Programming). Case studies on a simple distribution network and on real Brazilian distribution systems are presented and discussed. © Copyright KTH 2006.

Mathematical decomposition technique applied to the probabilistic power flow problem

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.

Probabilistic analysis of the distributed power generation in weakly meshed distribution systems

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.

Fluxo de potência trifásico probabilístico para redes de distribuição usando o método de estimação por pontos

In this paper the point estimation method is applied to solve the probabilistic power flow problem for unbalanced three-phase distribution systems. Through the implementation of this method the probability distribution functions of voltages (magnitude and angle) as well as the active and reactive power flows in the branches of the distribution system are determined. Two different approaches of the point estimation method are presented (2m and 2m+1 point schemes). In order to test the proposed methodology, the IEEE 34 and 123 bus test systems are used. The results obtained with both schemes are compared with the ones obtained by a Monte Carlo Simulation (MCS).

Spatial Distribution of Euschistus heros (F.) (Hemiptera: Pentatomidae) in Soybean

Soybean bugs are major crop pests that cause significant reduction in harvest yield and influence grain quality. The aim of this study was to verify the spatial distribution of Euschistus heros (F.) (Hemiptera: Pentatomidae) in conventional and transgenic soybean cultivars. The experiment was conducted during the 2010-2011 crop season in UNESP/FCAV, Jaboticabal, SP, Brazil, in two fields of 10,000-m2 area that were subdivided into 100 plots (10 m × 10 m). The cultivars sown were M 7908 RR and its isoline M-SOY 8001. The number of the first to fifth instars and the number of adults were determined. To evaluate insect dispersion in the area, the following indices were used: variance/mean ratio, Morisita index, Green coefficient, and the k exponent of the negative binomial distribution. To study probabilistic models to describe the spatial distribution of the insects, the adjustments of the Poisson and negative binomial distributions were tested. The first to third instars showed aggregated spatial distribution, whereas the fourth and fifth instars, and adults, isolated or grouped, showed variation in the arrangement, ranging from moderately aggregated to randomly dispersed. During the adjustment of probability distributions, the negative binomial distribution model showed adjustment for the first to third instars, fourth and fifth instars, adults, and fourth and fifth instars plus adults. © 2013 Sociedade Entomológica do Brasil.