Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

A Cellular Automaton Approach to Spatial Electric Load Forecasting

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Bilevel Approach to Transmission Expansion Planning Within a Market Environment

We present a bilevel model for transmission expansion planning within a market environment, where producers and consumers trade freely electric energy through a pool. The target of the transmission planner, modeled through the upper-level problem, is to minimize network investment cost while facilitating energy trading. This upper-level problem is constrained by a collection of lower-level market clearing problems representing pool trading, and whose individual objective functions correspond to social welfare. Using the duality theory the proposed bilevel model is recast as a mixed-integer linear programming problem, which is solvable using branch-and-cut solvers. Detailed results from an illustrative example and a case study are presented and discussed. Finally, some relevant conclusions are drawn.

The Hamilton-Jacobi approach to Teleparallelism

We intend to analyse the constraint structure of Teleparallelism employing the Hamilton-Jacobi formalism for singular systems. This study is conducted without using an ADM 3+1 decomposition and without fixing time gauge condition. It can be verified that the field equations constitute an integrable system.

A study of habitat fragmentation in Southeastern Brazil using remote sensing and geographic information systems (GIS)

The purpose of this work was to study fragmentation of forest formations (mesophytic forest, riparian woodland and savannah vegetation (cerrado)) in a 15,774-ha study area located in the Municipal District of Botucatu in Southeastern Brazil (São Paulo State). A land use and land cover map was made from a color composition of a Landsat-5 thematic mapper (TM) image. The edge effect caused by habitat fragmentation was assessed by overlaying, on a geographic information system (GIS), the land use and land cover data with the spectral ratio. The degree of habitat fragmentation was analyzed by deriving: 1. mean patch area and perimeter; 2. patch number and density; 3. perimeter-area ratio, fractal dimension (D), and shape diversity index (SI); and 4. distance between patches and dispersion index (R). In addition, the following relationships were modeled: 1. distribution of natural vegetation patch sizes; 2. perimeter-area relationship and the number and area of natural vegetation patches; 3. edge effect caused by habitat fragmentation, the values of R indicated that savannah patches (R = 0.86) were aggregated while patches of natural vegetation as a whole (R = 1.02) were randomly dispersed in the landscape. There was a high frequency of small patches in the landscape whereas large patches were rare. In the perimeter-area relationship, there was no sign of scale distinction in the patch shapes, In the patch number-landscape area relationship, D, though apparently scale-dependent, tends to be constant as area increases. This phenomenon was correlated with the tendency to reach a constant density as the working scale was increased, on the edge effect analysis, the edge-center distance was properly estimated by a model in which the edge-center distance was considered a function of the to;al patch area and the SI. (C) 1997 Elsevier B.V. B.V.

A CASE tool for the modeling of methods and information systems

MODSI is a multi-models tool for information systems modeling. A modeling process in MODSI can be driven according to three different approaches: informal, semi-formal and formal. The MODSI tool is therefore based on the linked usage of these three modeling approaches. It can be employed at two different levels: the meta-modeling of a method and the modeling of an information system.In this paper we start presenting different types of modeling by making an analysis of their particular features. Then, we introduce the meta-model defined in our tool, as well as the tool functional architecture. Finally, we describe and illustrate the various usage levels of this tool.

A new approach to the solution of the optimal power flow problem based on the modified Newton's method associated to an augmented Lagrangian function

This paper presents a new algorithm for optimal power flow problem. The algorithm is based on Newton's method which it works with an Augmented Lagrangian function associated with the original problem. The function aggregates all the equality and inequality constraints and is solved using the modified-Newton method. The test results have shown the effectiveness of the approach using the IEEE 30 and 638 bus systems.

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine's capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine's potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

A recursive approach to space resection using straight lines

An approach using straight lines as features to solve the photogrammetric space resection problem is presented. An explicit mathematical model relating straight lines, in both object and image space, is used. Based on this model, Kalman Filtering is applied to solve the space resection problem. The recursive property of the filter is used in an iterative process which uses the sequentially estimated camera location parameters to feedback to the feature extraction process in the image. This feedback process leads to a gradual reduction of the image space for feature searching, and consequently eliminates the bottleneck due to the high computational cost of the image segmentation phase. It also enables feature extraction and the determination of feature correspondence in image and object space in an automatic way, i.e., without operator interference. Results obtained from simulated and real data show that highly accurate space resection parameters are obtained as well as a progressive processing time reduction. The obtained accuracy, the automatic correspondence process, and the short related processing time show that the proposed approach can be used in many real-time machine vision systems, making possible the implementation of applications not feasible until now.

A Bayesian approach to estimate the accuracy of in-house ELISA assay to measure rabies antibodies from compulsory vaccinated dogs and cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A neural approach to evaluate the effect of lightning in power transformers

This paper proposes the application of computational intelligence techniques to assist complex problems concerning lightning in transformers. In order to estimate the currents related to lightning in a transformer, a neural tool is presented. ATP has generated the training vectors. The input variables used in Artificial Neural Networks (ANN) were the wave front time, the wave tail time, the voltage variation rate and the output variable is the maximum current in the secondary of the transformer. These parameters can define the behavior and severity of lightning. Based on these concepts and from the results obtained, it can be verified that the overvoltages at the secondary of transformer are also affected by the discharge waveform in a similar way to the primary side. By using the tool developed, the high voltage process in the distribution transformers can be mapped and estimated with more precision aiding the transformer project process, minimizing empirics and evaluation errors, and contributing to minimize the failure rate of transformers. © 2009 The Berkeley Electronic Press. All rights reserved.

Fostering economic policy coordination in Latin America: the REDIMA approach to escaping the prisoner's dilemma

Includes bibliography

A new approach to development banking in Jamaica

Includes bibliography

A social network approach to trust management in VANETs

In the past few years, vehicular ad hoc networks(VANETs) was studied extensively by researchers. VANETs is a type of P2P network, though it has some distinct characters (fast moving, short lived connection etc.). In this paper, we present several limitations of current trust management schemes in VANETs and propose ways to counter them. We first review several trust management techniques in VANETs and argue that the ephemeral nature of VANETs render them useless in practical situations. We identify that the problem of information cascading and oversampling, which commonly arise in social networks, also adversely affects trust management schemes in VANETs. To the best of our knowledge, we are the first to introduce information cascading and oversampling to VANETs. We show that simple voting for decision making leads to oversampling and gives incorrect results in VANETs. To overcome this problem, we propose a novel voting scheme. In our scheme, each vehicle has different voting weight according to its distance from the event. The vehicle which is more closer to the event possesses higher weight. Simulations show that our proposed algorithm performs better than simple voting, increasing the correctness of voting. © 2012 Springer Science + Business Media, LLC.

Unbiased approach to diagnose the nutrient status of red guava (Psidium guajava)

Fertilization of guava relies on soil and tissue testing. The interpretation of tissue test is currently conducted by comparing nutrient concentrations or dual ratios with critical values or ranges. The critical value approach is affected by nutrient interactions. Nutrient interactions can be described by dual ratios where two nutrients are compressed into a single expression or a ternary diagrams where one redundant proportion can be computed by difference between 100% and the sum of the other two. There are D(D-1) possible dual ratios in a D-parts composition and most of them are thus redundant. Nutrients are components of a mixture that convey relative, not absolute information on the composition. There are D-1 balances between components or ingredients in any mixture. Compositional data are intrinsically redundant, scale dependent and non-normally distributed. Based on the principles of equilibrium and orthogonality, the nutrient balance concept projects D-1 isometric log ratio (ilr) coordinates into the Euclidean space. The D-1 balances between groups of nutrients are ordered to reflect knowledge in plant physiology, soil fertility and crop management. Our objective was to evaluate the ilr approach using nutrient data from a guava orchard survey and fertilizer trials across the state of São Paulo, Brazil. Cationic balances varied widely between orchards. We found that the Redfield N/P ratio of 13 was critical for high guava yield. We present guava yield maps in ternary diagrams. Although the ratio between nutrients changing in the same direction with time is often assumed to be stationary, most guava nutrient balances and dual ratios were found to be non-stationary. The ilr model provided an unbiased nutrient diagnosis of guava. © ISHS.