Marcio R. C. Reis

Firing angles optimization for Switched Reluctance Generator using Genetic Algorithms

This paper reports on a Switched Reluctance Machine (SRM) operating as generator excited through external power source. This device provides DC voltage output through its power converter. Parameters such as rotor speed, excitation voltage and firing angles interferes directly on the output voltage. Thus, many strategies have been studied and developed by scientific community in order to control the output voltage or achieve its maximization. This work proposes a driving strategy applied to the SRM that consists in obtaining the optimal firing angles in order to maximize the output voltage for given rotor speed and excitation. Simulations are presented for results analysis.

Heuristic and deterministic strategies applied on a PID controller tuning for speed control of a DC motor

This paper reports on a PID controller for speed control of a DC motor. The controller parameters were obtained through optimization methods employing heuristic and deterministic strategies. This methods were applied on a simulation model in order to verify which one provides better control results.

Calculation of sensitivity index using one-at-a-time measures based on graphical analysis

This work proposes different methods to calculate the sensitivity of system parameters based on graphic analysis. From percentages variations in base values of the parameters, one-at-a-time measures are taken to the construction of a graph that expresses the impact on the output caused by variations in the inputs. Two case studies are proposed, with simulated and experimental data, in which the proposed methods are applied and compared based on the values of the sensitivity indices for ranges of interest. All methods confirm quantitatively the most sensitive variables and the choice of one of the methods depends on the characteristics considered relevant for analysis, i.e., degree of sensitivity of a parameter in relation to another, the behavior of the curve and presence of peaks.

Parametric regression in synchronous and induction generators

The purpose of this work is to find the values of the electric parameters of synchronous and induction machines in order to validate the electrical interactions between an induction generator and a synchronous generator. The two generators will be connected in two ways: i) isolated to the common bus and ii) jointly connected to the common bus in permanent regime, subject to non-linear load. The results obtained from the comparison of the computational simulation and the experimental tests show that the model represents the real system. It is concluded that with the validation of the model it is possible to predict the behavior of the real system with the insertion of new perturbations.

Calculation and analysis of voltage violation problem on electricity distribution networks

The approach of this paper it is about voltage conformity delivered to the final customer, on electricity distribution networks. Have obtained physical and electrical characteristics information from the network coming from the database of the electricity company. The study presents the process of voltages estimation in primary and secondary circuits wich estimation of indicators of voltage violation. The presented cases studies approach a statistical analysis of sampling campaigns of distributor, voltage level analysis of one feeder circuit, the estimative of indicators of voltage violation and simulation validation with field measurements on the circuit. Through the found results it is possible to make better decisions of action to be taken and point out the circuit who needs maintenance.

Increasing efficiency of the switched reluctance generator using parametric regression and optimization methods

In this paper the switched reluctance generator (SRG) is explored considering the improvement of its efficiency. This machine generates a DC power that is directly related to input driving parameters. Simulation results are presented bringing a case study of parametric regression to track the best efficiency for any input parameters: excitation voltage and turn off angle. A method known as parametric regression is applied along with deterministic optimization in order to find an equation that provides the driving parameters so the machine can generate DC power associated to high efficiency.

Heuristic regression method for descriptive data analysis

The purpose of this paper is to use the hybridized optimization method in order to find mathematical structures for analysis of experimental data. The heuristic optimization method will be hybridized with deterministic optimization method in order to that structures found require not knowledge about data generated experimentally. Three case studies are proposed and discussed to validate the results. The proposed method has viable solution for the analysis of experimental data and extrapolation, with mathematical expression reduced.

Switched reluctance generator efficiency improvement for wind energy applications

Considering the actual environmental appeal due to excessive consumption of fossil fuels, is relevant the research and development of green power sources in order to conserve the natural resources. Wind energy has become a target of researches and highlights a clean energy scenario. Electrical machines have its reversibility and, operating as generators, can be useful for wind energy aaplications. The switched reluctance generator (SRG) has several advantagens for this application. In this paper, simulation results are presented for a SRG considering its driving. Optimization methods are applied in order to maximize its generated power increasing efficiency as well.

Parametric regression methodology and optimized control for DC motor

This paper presents a speed control for a DC motor. Despite the unknown parameters of the plant to be controlled, these parameters are found using a system identification method. The methodology implemented in this study is known as parametric regression and is based on an optimization technique. This optimization, through its fitness function, allows to find the system characteristics in order to make possible the system control. This control is applied to the DC motor speed through a cascade PI controller, acting on the motor current. Besides, the controller parameters are found through deterministic optimization technique, using the Quasi-Newton method. Simulation and experimental results are presented in order to validate the study and make possible the control of an unknown parameters system.

Optimization of the operation power of DC-DC converters applied to thermogenerators

The objective of this work is to develop a model that represents the thermoelectric generation plant with the purpose of optimizing the search of the maximum power point in the thermoelectric generators. Are used converters DC-DC controlled by artificial intelligence techniques. The method consists of regulating the voltage to connect various loads as batteries, and compare the optimal control methods with the classic control methods. The results show that the neural network makes it possible to carry out the process of learning the power pattern to estimate the work cycle quickly and efficiently. The Fuzzy controller totally eliminates overshoot and gets fast response time with satisfactory performance.