This article presents studies related to the driving and control of the switched reluctance generator in order to enhance its efficiency. This type of electrical machine is an option for wind energy conversion systems, favoring the generation of electricity in distributed generation systems and contributing positively to loads without access to the main grid. The studies developed in this paper verify the possibility of controlling the output voltage of the switched reluctance generator in parallel with an efficiency tracking technique acting on the switching angles of the power converter. Simulation and experimental results are presented in order to verify the feasibility of implementing this technique to enhance the efficiency of the generator.

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.

This work proposes a complexity metric which maps internal connections of the system and its relationship with the environment through the application of sensitivity analysis. The proposed methodology presents (i) system complexity metric, (ii) system sensitivity metric, and (iii) two models as case studies. Based on the system dynamics, the complexity metric maps the internal connections through the states of the system and the metric of sensitivity evaluates the contribution of each parameter to the output variability. The models are simulated in order to quantify the complexity and the sensitivity and to analyze the behavior of the systems leading to the assumption that the system complexity is closely linked to the most sensitive parameters. As findings from results, it may be observed that systems may exhibit high performance as a result of optimized configurations given by their natural complexity.

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.

This paper presents a tracking method to improve the performance of switched reluctance generators in areas with low wind speeds. The main contribution of this work is the proposal of an advanced control system that employs dynamic tracking techniques to optimize the energy efficiency and response of the switched reluctance generators under various operating conditions. The methodology encompasses the construction of the generator, the development of a wind turbine model, and the coupling of the turbine with the switched reluctance generators. Simulations are conducted using real wind speed data to evaluate the use of switched reluctance generators in wind energy generation. The performance of the switched reluctance generators is improved by applying a tracking technique that operates on the converter’s turn‐off angle, which controls the generator’s switching. The tracking and optimization techniques implemented in this work maximize the performance of switched reluctance generators in wind energy generation, both in standalone and self‐excited operations. The results demonstrate that satisfactory wind energy generation can be achieved using the SRG, with wind speeds of 5.40 m/s producing approximately 1.5 kW without optimization and around 1.65 kW with optimization, reaching about 70% efficiency with a custom‐built generator. This makes the technology viable for regions characterized by low wind speeds.

The main objective of this study is to apply structural equation modeling with partial least squares, and based on covariance, to assess the satisfaction of residential electricity consumers. The methodology used compares the results of both structural equation models to indicate the model that best fits the problem of measuring the satisfaction of residential consumers with electricity concessionaires and licensees. The sample used in the survey contained questionnaire responses from 86,175 individuals considering the period from 2014 to 2018. The constructs evaluated were satisfaction, quality, value, loyalty, and trust. A confidence interval analysis shows that all weights are significant, demonstrating the importance of all the indicators that represent the constructs. The trust, quality, and value constructs can explain 74.4% of the satisfaction construct variability, so this relationship’s explanatory capacity is considered substantial. Finally, the evaluation of the performance of the service provided by the electric energy concessionaires/licensees, measured by customer satisfaction, allows for the continuous improvement of services, and meeting, even if minimally, the expectations of its consumers.