Parameterized fast decoupled power flow methods for obtaining the maximum loading point of power systems. Part I. Mathematical modeling

The conventional Newton and fast decoupled power flow (FDPF) methods have been considered inadequate to obtain the maximum loading point of power systems due to ill-conditioning problems at and near this critical point. It is well known that the PV and Q-theta decoupling assumptions of the fast decoupled power flow formulation no longer hold in the vicinity of the critical point. Moreover, the Jacobian matrix of the Newton method becomes singular at this point. However, the maximum loading point can be efficiently computed through parameterization techniques of continuation methods. In this paper it is shown that by using either theta or V as a parameter, the new fast decoupled power flow versions (XB and BX) become adequate for the computation of the maximum loading point only with a few small modifications. The possible use of reactive power injection in a selected PV bus (Q(PV)) as continuation parameter (mu) for the computation of the maximum loading point is also shown. A trivial secant predictor, the modified zero-order polynomial which uses the current solution and a fixed increment in the parameter (V, theta, or mu) as an estimate for the next solution, is used in predictor step. These new versions are compared to each other with the purpose of pointing out their features, as well as the influence of reactive power and transformer tap limits. The results obtained with the new approach for the IEEE test systems (14, 30, 57 and 118 buses) are presented and discussed in the companion paper. The results show that the characteristics of the conventional method are enhanced and the region of convergence around the singular solution is enlarged. In addition, it is shown that parameters can be switched during the tracing process in order to efficiently determine all the PV curve points with few iterations. (C) 2003 Elsevier B.V. All rights reserved.

Mathematical modeling of the ester oil-refrigerant R134A mixture two-phase flow with foam formation through a small diameter tube

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mathematical modeling and control of population systems: Applications in biological pest control

The aim of this paper is to apply methods from optimal control theory, and from the theory of dynamic systems to the mathematical modeling of biological pest control. The linear feedback control problem for nonlinear systems has been formulated in order to obtain the optimal pest control strategy only through the introduction of natural enemies. Asymptotic stability of the closed-loop nonlinear Kolmogorov system is guaranteed by means of a Lyapunov function which can clearly be seen to be the solution of the Hamilton-Jacobi-Bellman equation, thus guaranteeing both stability and optimality. Numerical simulations for three possible scenarios of biological pest control based on the Lotka-Volterra models are provided to show the effectiveness of this method. (c) 2007 Elsevier B.V. All rights reserved.

Study of alternative schemes for the parameterization step of the continuation power flow method based on physical parameters, part I: Mathematical modeling

The conventional power flow method is considered to be inadequate to obtain the maximum loading point because of the singularity of Jacobian matrix. Continuation methods are efficient tools for solving this kind of problem since different parameterization schemes can be used to avoid such ill-conditioning problems. This paper presents the details of new schemes for the parameterization step of the continuation power flow method. The new parameterization options are based on physical parameters, namely, the total power losses (real and reactive), the power at the slack bus (real or reactive), the reactive power at generation buses, and transmission line power losses (real and reactive). The simulation results obtained with the new approach for the IEEE test systems (14, 30, 57, and 118 buses) are presented and discussed in the companion paper. The results show that the characteristics of the conventional method are not only preserved but also improved.

Basic ingredients for mathematical modeling of tumor growth in vitro: Cooperative effects and search for space

Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.

Mathematical modeling and analysis of the flocculation process in chambers in series

In this study, the flocculation process in continuous systems with chambers in series was analyzed using the classical kinetic model of aggregation and break-up proposed by Argaman and Kaufman, which incorporates two main parameters: K (a) and K (b). Typical values for these parameters were used, i. e., K (a) = 3.68 x 10(-5)-1.83 x 10(-4) and K (b) = 1.83 x 10(-7)-2.30 x 10(-7) s(-1). The analysis consisted of performing simulations of system behavior under different operating conditions, including variations in the number of chambers used and the utilization of fixed or scaled velocity gradients in the units. The response variable analyzed in all simulations was the total retention time necessary to achieve a given flocculation efficiency, which was determined by means of conventional solution methods of nonlinear algebraic equations, corresponding to the material balances on the system. Values for the number of chambers ranging from 1 to 5, velocity gradients of 20-60 s(-1) and flocculation efficiencies of 50-90 % were adopted.

Mathematical modeling of a continuous alcoholic fermentation process in a two-stage tower reactor cascade with flocculating yeast recycle

Experiments of continuous alcoholic fermentation of sugarcane juice with flocculating yeast recycle were conducted in a system of two 0.22-L tower bioreactors in series, operated at a range of dilution rates (D (1) = D (2) = 0.27-0.95 h(-1)), constant recycle ratio (alpha = F (R) /F = 4.0) and a sugar concentration in the feed stream (S (0)) around 150 g/L. The data obtained in these experimental conditions were used to adjust the parameters of a mathematical model previously developed for the single-stage process. This model considers each of the tower bioreactors as a perfectly mixed continuous reactor and the kinetics of cell growth and product formation takes into account the limitation by substrate and the inhibition by ethanol and biomass, as well as the substrate consumption for cellular maintenance. The model predictions agreed satisfactorily with the measurements taken in both stages of the cascade. The major differences with respect to the kinetic parameters previously estimated for a single-stage system were observed for the maximum specific growth rate, for the inhibition constants of cell growth and for the specific rate of substrate consumption for cell maintenance. Mathematical models were validated and used to simulate alternative operating conditions as well as to analyze the performance of the two-stage process against that of the single-stage process.

Management of vomplex systems: Modeling the biological pest control

The aim of this paper is to study the cropping system as complex one, applying methods from theory of dynamic systems and from the control theory to the mathematical modeling of the biological pest control. The complex system can be described by different mathematical models. Based on three models of the pest control, the various scenarios have been simulated in order to obtain the pest control strategy only through natural enemies' introduction. © 2008 World Scientific Publishing Company.

Modeling for performance analysis of electromagnetic zero-sequence suppressor

The purpose of this work is to present a frequency domain model to demonstrate the operation of an electromagnetic arrangement for controlling the injection of zero-sequence currents in the electrical system. Considering the diversity of sequential distribution of harmonic components of a current, the device proposed can be used in the process of mitigation of zero-sequence components. This device, here called electromagnetic suppressor, consists of a blocker and filter both electromagnetic, whose joint operation can provide paths of high and low impedances that can be conveniently adjusted in order to search for a desired performance. This study presents physical considerations, mathematical modeling and computer simulations that clearly demonstrate the viability of this application as a more viable alternative in the conception of filtering systems. The performance analysis is based on the frequency response of harmonic transmittances. The efficacy of this technique in direct actions to maximize the harmonic mitigation process is demonstrated. ©2010 IEEE.

Measurements and modeling of reactive nitrogen deposition in southeast Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Mapeamento das formas do relevo para estimativa de custos de fertilização em cana-de-açúcar

A modelagem matemática associada ao conhecimento da variabilidade dos atributos do solo e mapeamento das formas do relevo pode auxiliar no manejo da fertilidade do solo em usinas sucroalcooleiras. O presente trabalho teve como objetivo avaliar o uso da geoestatística e da modelagem matemática na estimativa de custos de fertilização, em diferentes formas do relevo. em uma área de 200 ha, foram identificadas duas formas de relevo, uma côncava e outra convexa, sendo os solos coletados nos pontos de cruzamento de uma malha, com intervalos regulares de 50 m, perfazendo um total de 623 pontos. As amostras foram submetidas a análises químicas, e, posteriormente, os dados foram avaliados por meio da estatística descritiva, geoestatística e modelagem matemática. Os resultados mostraram que, quando as formas do relevo são incorporadas às análises geoestatística e de modelagem matemática, ocorre aumento na eficiência de aplicação do calcário, fósforo e potássio no solo.

Sensoriamento remoto e geoprocessamento aplicados ao uso da terra em microbacias hidrográficas, Botucatu - SP

O presente trabalho teve como objetivo identificar e quantificar o uso da terra em dez microbacias ocorrentes na bacia do Rio Capivara, município de Botucatu - SP, a partir da estruturação de um banco de dados utilizando o Sistema de Informações Geográficas (SIG) - IDRISI. Os resultados mostram que as classes de uso da terra, uso agrícola e pastagem, foram as mais significativas, pois ocuparam mais da metade da área das microbacias. O alto índice de uso da terra por pastagens, capoeiras, reflorestamento e matas reflete a predominância de solos arenosos com baixa fertilidade. As imagens obtidas do satélite LANDSAT 5 permitiram o mapeamento do uso da terra de maneira rápida, além de fornecer um excelente banco de dados para futuro planejamento e gerenciamento das atividades agropecuárias regionais. O SIG-IDRISI permitiu identificar, por meio de seus diferentes módulos para georreferenciamento, classificação digital e modelo matemático, as classes de uso da terra com rapidez.

Influence of design parameters on linear induction motor end effect

In this paper, a factor referred to as k(f) for linear induction motor end effect analysis is presented. The mathematical model takes into account the longitudinal entry end effect. The entry end effect produces considerable distortion in magnetic field distribution. It is shown how this influence is derived from the machine-developed force that is calculated through the application of the I-D theory. The k(f) factor establishes the relationship between the longitudinal end effect and machine parameters, mainly the number of magnetic poles, secondary resistivity, and frequency.

Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems

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.

Recursive hierarchic segmentation analysis of bone mineral density changes on digital panoramic images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)