Controle de uma microrrede ilhada baseada em geração eólica-diesel com alto nível de inserção de geração eólica

The insertion of distributed generation units in the electric power systems have contributed to the popularization of microgrid concepts. With the microgrids, several potential benefits can be achieved in regard to power quality and supply reliability. However, several technical challenges related to the control and operation of microgrids, which are associated with high insertion of generation systems based on static converters, must be overcame. Among the opportunities in the context of microgrids, there is the islanded operation of microgrids temporarily disconnected from the electric power systems and also the autonomous operation of geographically isolated microgrids. The frequency in large power systems is traditionally controlled by the generation units based on traditional synchronous generator. The insertion of distributed generation units based on static power converters may bring difficulties to the frequency control in microgrids, due to the reduction of the equivalent inertia of conventional synchronous generators present in islanded and isolated microgrids. In this context, it becomes necessary the proposition of new operational and control strategies for microgrids control, taking into account the presence of distributed generation units based on full-rated converter. This paper proposes an operational and control strategy for the islanded operation of a winddiesel microgrid with high insertion level of wind generation. The microgrid adopted in this study comprises of a wind energy conversion system with synchronous generator based on full rated converter, a diesel generator (DIG) and a dump load. Due to the high insertion level of wind generation, the wind unit operates in Vf mode and the diesel generator operates in PQ mode. The diesel generator and the dump load are used to regulate the DC-link voltage of the wind generation unit. The proposed control allows the islanded operation of the microgrid only with wind generation, wind-only mode (WO), and with wind-diesel generation, wind-diesel mode (WD). For the wind-only mode, with 100% of penetration level of wind generation, it is proposed a DC-link voltage control loop based on the use of a DC dump load. For the winddiesel mode, it is proposed a DC-link voltage control loop added to the diesel generator, which is connected to the AC side of the microgrid, in coordinated action with the dump load. The proposed operational and control strategy does not require the use of batteries and aims to maximize the energy production from wind generation, ensuring the uninterrupted operation of the microgrid. The results have showed that the operational and control strategy allowed the stable operation of the islanded microgrid and that the DC-link voltage control loop added to the diesel generator and the dump load proved to be effective during the typical variations of wind speed and load.

Análise e proposição de estratégias de estimação e controle de velocidade para motores de indução trifásicos

This study presents a proposal of speed servomechanisms without the use of mechanical sensors (sensorless) using induction motors. A comparison is performed and propose techniques for pet rotor speed, analyzing performance in different conditions of speed and load. For the determination of control technique, initially, is performed an analysis of the technical literature of the main control and speed estimation used, with their characteristics and limitations. The proposed technique for servo sensorless speed induction motor uses indirect field-oriented control (IFOC), composed of four controllers of the proportional-integral type (PI): rotor flux controller, speed controller and current controllers in the direct and quadrature shaft. As the main focus of the work is in the speed control loop was implemented in Matlab the recursive least squares algorithm (RLS) for identification of mechanical parameters, such as moment of inertia and friction coefficient. Thus, the speed of outer loop controller gains can be self adjusted to compensate for any changes in the mechanical parameters. For speed estimation techniques are analyzed: MRAS by rotóricos fluxes MRAS by counter EMF, MRAS by instantaneous reactive power, slip, locked loop phase (PLL) and sliding mode. A proposition of estimation in sliding mode based on speed, which is performed a change in rotor flux observer structure is displayed. To evaluate the techniques are performed theoretical analyzes in Matlab simulation environment and experimental platform in electrical machinery drives. The DSP TMS320F28069 was used for experimental implementation of speed estimation techniques and check the performance of the same in a wide speed range, including load insertion. From this analysis is carried out to implement closed-loop control of sensorless speed IFOC structure. The results demonstrated the real possibility of replacing mechanical sensors for estimation techniques proposed and analyzed. Among these, the estimator based on PLL demonstrated the best performance in various conditions, while the technique based on sliding mode has good capacity estimation in steady state and robustness to parametric variations.

Wave impedance selection for passivity-based bilateral teleoperation

When a task must be executed in a remote or dangerous environment, teleoperation systems may be employed to extend the influence of the human operator. In the case of manipulation tasks, haptic feedback of the forces experienced by the remote (slave) system is often highly useful in improving an operator's ability to perform effectively. In many of these cases (especially teleoperation over the internet and ground-to-space teleoperation), substantial communication latency exists in the control loop and has the strong tendency to cause instability of the system. The first viable solution to this problem in the literature was based on a scattering/wave transformation from transmission line theory. This wave transformation requires the designer to select a wave impedance parameter appropriate to the teleoperation system. It is widely recognized that a small value of wave impedance is well suited to free motion and a large value is preferable for contact tasks. Beyond this basic observation, however, very little guidance exists in the literature regarding the selection of an appropriate value. Moreover, prior research on impedance selection generally fails to account for the fact that in any realistic contact task there will simultaneously exist contact considerations (perpendicular to the surface of contact) and quasi-free-motion considerations (parallel to the surface of contact). The primary contribution of the present work is to introduce an approximate linearized optimum for the choice of wave impedance and to apply this quasi-optimal choice to the Cartesian reality of such a contact task, in which it cannot be expected that a given joint will be either perfectly normal to or perfectly parallel to the motion constraint. The proposed scheme selects a wave impedance matrix that is appropriate to the conditions encountered by the manipulator. This choice may be implemented as a static wave impedance value or as a time-varying choice updated according to the instantaneous conditions encountered. A Lyapunov-like analysis is presented demonstrating that time variation in wave impedance will not violate the passivity of the system. Experimental trials, both in simulation and on a haptic feedback device, are presented validating the technique. Consideration is also given to the case of an uncertain environment, in which an a priori impedance choice may not be possible.

Controle aplicado a poços com método de elevação e bombeio centrífugo submerso

The Electrical Submersible Pumping is an artificial lift method for oil wells employed in onshore and offshore areas. The economic revenue of the petroleum production in a well depends on the oil flow and the availability of lifting equipment. The fewer the failures, the lower the revenue shortfall and costs to repair it. The frequency with which failures occur depends on the operating conditions to which the pumps are submitted. In high-productivity offshore wells monitoring is done by operators with engineering support 24h/day, which is not economically viable for the land areas. In this context, the automation of onshore wells has clear economic advantages. This work proposes a system capable of automatically control the operation of electrical submersible pumps, installed in oil wells, by an adjustment at the electric motor rotation based on signals provided by sensors installed on the surface and subsurface, keeping the pump operating within the recommended range, closest to the well s potential. Techniques are developed to estimate unmeasured variables, enabling the automation of wells that do not have all the required sensors. The automatic adjustment, according to an algorithm that runs on a programmable logic controller maintains the flow and submergence within acceptable parameters avoiding undesirable operating conditions, as the gas interference and high engine temperature, without need to resort to stopping the engine, which would reduce the its useful life. The control strategy described, based on modeling of physical phenomena and operational experience reported in literature, is materialized in terms of a fuzzy controller based on rules, and all generated information can be accompanied by a supervisory system

Laser cladding and its potential to reduce particulate matter emissions from the automotive and locomotive sector

Laser Cladding (LC) is an emerging technology which is used both for coating applications as well as near-net shape fabrication. Despite its significant advantages, such as low dilution and metallurgical bond with the substrate, it still faces issues such as process control and repeatability, which restricts the extension to its applications. The following thesis evaluates the LC technology and tests its potential to be applied to reduce particulate matter emissions from the automotive and locomotive sector. The evaluation of LC technology was carried out for the deposition of multi-layer and multi-track coatings. 316L stainless steel coatings were deposited to study the minimisation of geometric distortions in thin-walled samples. Laser power, as well as scan strategy, were the main variables to achieve this goal. The use of constant power, reduction at successive layers, a control loop control system, and two different scan strategies were studied. The closed-loop control system was found to be practical only when coupled with the correct scan strategy for the deposition of thin walls. Three overlapped layers of aluminium bronze were deposited onto a structural steel pipe for multitrack coatings. The effect of laser power, scan speed and hatch distance on the final geometry of coating were studied independently, and a combined parameter was established to effectively control each geometrical characteristic (clad width, clad height and percentage of dilution). LC was then applied to coat commercial GCI brake discs with tool steel. The optical micrography showed that even with preheating, the cracks that originated from the substrate towards the coating were still present. The commercial brake discs emitted airborne particles whose concentration and size depended on the test conditions used for simulation in the laboratory. The contact of LC cladded wheel with rail emitted significantly less ultra-fine particles while maintaining the acceptable values of coefficient of friction.

A Trans-dimensional inversion algorithm to model deformation sources with unconstrained shape in finite element domains

Ground deformation provides valuable insights on subsurface processes with pattens reflecting the characteristics of the source at depth. In active volcanic sites displacements can be observed in unrest phases; therefore, a correct interpretation is essential to assess the hazard potential. Inverse modeling is employed to obtain quantitative estimates of parameters describing the source. However, despite the robustness of the available approaches, a realistic imaging of these reservoirs is still challenging. While analytical models return quick but simplistic results, assuming an isotropic and elastic crust, more sophisticated numerical models, accounting for the effects of topographic loads, crust inelasticity and structural discontinuities, require much higher computational effort and information about the crust rheology may be challenging to infer. All these approaches are based on a-priori source shape constraints, influencing the solution reliability. In this thesis, we present a new approach aimed at overcoming the aforementioned limitations, modeling sources free of a-priori shape constraints with the advantages of FEM simulations, but with a cost-efficient procedure. The source is represented as an assembly of elementary units, consisting in cubic elements of a regular FE mesh loaded with a unitary stress tensors. The surface response due to each of the six stress tensor components is computed and linearly combined to obtain the total displacement field. In this way, the source can assume potentially any shape. Our tests prove the equivalence of the deformation fields due to our assembly and that of corresponding cavities with uniform boundary pressure. Our ability to simulate pressurized cavities in a continuum domain permits to pre-compute surface responses, avoiding remeshing. A Bayesian trans-dimensional inversion algorithm implementing this strategy is developed. 3D Voronoi cells are used to sample the model domain, selecting the elementary units contributing to the source solution and those remaining inactive as part of the crust.

Automated image analysis of lung branching morphogenesis

Regulating mechanisms of branchingmorphogenesis of fetal lung rat explants have been an essential tool formolecular research.This work presents a new methodology to accurately quantify the epithelial, outer contour, and peripheral airway buds of lung explants during cellular development frommicroscopic images. Methods.Theouter contour was defined using an adaptive and multiscale threshold algorithm whose level was automatically calculated based on an entropy maximization criterion. The inner lung epithelium was defined by a clustering procedure that groups small image regions according to the minimum description length principle and local statistical properties. Finally, the number of peripheral buds was counted as the skeleton branched ends from a skeletonized image of the lung inner epithelia. Results. The time for lung branching morphometric analysis was reduced in 98% in contrast to themanualmethod. Best results were obtained in the first two days of cellular development, with lesser standard deviations. Nonsignificant differences were found between the automatic and manual results in all culture days. Conclusions. The proposed method introduces a series of advantages related to its intuitive use and accuracy, making the technique suitable to images with different lighting characteristics and allowing a reliable comparison between different researchers.

Three-phase three-level current-source converter for EVs fast battery charging systems

This paper presents a three-phase three-level fast battery charger for electric vehicles (EVs) based in a current-source converter (CSC). Compared with the traditional voltage-source converters used for fast battery chargers, the CSC can be seen as a natural buck-type converter, i.e., the output voltage can assume a wide range of values, which varies between zero and the maximum instantaneous value of the power grid phase-to-phase voltage. Moreover, using the CSC it is not necessary to use a dc-dc back-end converter in the battery side, and it is also possible to control the grid current in order to obtain a sinusoidal waveform, and in phase with the power grid voltage (unitary power factor). Along the paper is described in detail the proposed CSC for EVs fast battery charging systems: the circuit topology, the power control theory, the current control strategy and the grid synchronization algorithm. Several simulation results of the EV fast battery charger operating with a maximum power of 50 kW are presented.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

A new approach for the solution of the optimal set-point tracking problem for nonlinear systems

In this paper, a discrete time dynamic integrated system optimisation and parameter estimation algorithm is applied to the solution of the nonlinear tracking optimal control problem. A version of the algorithm with a linear-quadratic model-based problem is developed and implemented in software. The algorithm implemented is tested with simulation examples.

Algoritmos genéticos: uso de lógica nebulosa e análise de convergência por cadeia de Markov

In this work, the Markov chain will be the tool used in the modeling and analysis of convergence of the genetic algorithm, both the standard version as for the other versions that allows the genetic algorithm. In addition, we intend to compare the performance of the standard version with the fuzzy version, believing that this version gives the genetic algorithm a great ability to find a global optimum, own the global optimization algorithms. The choice of this algorithm is due to the fact that it has become, over the past thirty yares, one of the more importan tool used to find a solution of de optimization problem. This choice is due to its effectiveness in finding a good quality solution to the problem, considering that the knowledge of a good quality solution becomes acceptable given that there may not be another algorithm able to get the optimal solution for many of these problems. However, this algorithm can be set, taking into account, that it is not only dependent on how the problem is represented as but also some of the operators are defined, to the standard version of this, when the parameters are kept fixed, to their versions with variables parameters. Therefore to achieve good performance with the aforementioned algorithm is necessary that it has an adequate criterion in the choice of its parameters, especially the rate of mutation and crossover rate or even the size of the population. It is important to remember that those implementations in which parameters are kept fixed throughout the execution, the modeling algorithm by Markov chain results in a homogeneous chain and when it allows the variation of parameters during the execution, the Markov chain that models becomes be non - homogeneous. Therefore, in an attempt to improve the algorithm performance, few studies have tried to make the setting of the parameters through strategies that capture the intrinsic characteristics of the problem. These characteristics are extracted from the present state of execution, in order to identify and preserve a pattern related to a solution of good quality and at the same time that standard discarding of low quality. Strategies for feature extraction can either use precise techniques as fuzzy techniques, in the latter case being made through a fuzzy controller. A Markov chain is used for modeling and convergence analysis of the algorithm, both in its standard version as for the other. In order to evaluate the performance of a non-homogeneous algorithm tests will be applied to compare the standard fuzzy algorithm with the genetic algorithm, and the rate of change adjusted by a fuzzy controller. To do so, pick up optimization problems whose number of solutions varies exponentially with the number of variables

Density and Spatial Distribution of Buffy-tufted-ear Marmosets (Callithrix aurita) in a Continuous Atlantic Forest

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

Predicting the potential distribution of the alien invasive American bullfrog (Lithobates catesbeianus) in Brazil

The non-native invasive anuran Lithobates catesbeianus is presently distributed in Brazil, especially in the Atlantic Rainforest biodiversity hotspot. Here, we use a maximum entropy ecological niche modeling algorithm (i) to model the North American native geographic distribution of this species and (ii) to project that model onto the whole of Brazil. After applying a threshold value that balances commission and omission errors, the projection results suggested high probabilities of occurrence mostly in southern and southeastern Brazil. We also present the first report on the species known distribution in Brazil, showing good agreement with model predictions. If the predictive map is interpreted as depicting invasiveness potential of L. catesbeianus, strategies to prevent further invasion in Brazil should be focused especially in the Atlantic Rainforest biodiversity hotspot.

Multiple minima hypersurfaces procedures for biomimetic ligands screening

In this work the interaction of the pesticide carbaryl with two groups of biomimetic ligands, peptides and MIPs was screened by multiple minima hypersurfaces (MMH) procedures, through the AM1 semiempirical method. Data related to the properties of the molecular association of the complex biomimetic ligand-pesticide were obtained and compared with another molecular modeling algorithm named Leapfrog, as included in the Sybyl software package, and experimental results from the literature, remarking good correlation between them. All important MMH program parameters (cells number, box size, conformers) were studied and optimized with the aim of getting the minimum computation time without losing the correlation with experimental data. The data demonstrated that MMH approach can be used as a fast biomimetic ligand screening tool for MIPs. In the case of peptides the computation time was not comparable with the molecular dynamics methods conventionally used for this approach. © 2011 Springer Science+Business Media B.V.