Brazil has started an energy transition process through more efficient electric motors. The new legislation determining the IE3 Class as the minimum efficiency level in commercial electric motors became valid in August 2019. Currently, four induction motor classes are defined by the IEC 60034-30-1, with the IE4 class being the most efficient, and in the same way, proposals to achieve IE5 efficiency class are available in the market. Considering the upcoming new technologies, it is necessary to know the impact of power systems disturbances in IM's in view of future substitutions. This paper presents a detailed analysis of the impact of different percentages of under and over voltage unbalances on the temperature and performance of electric motors classes IE2, IE3 and IE4. Results show that the IE4 hybrid motor presents non-linear characteristics, being observed this motor shows less dependence on voltage variation, mainly undervoltage unbalance. An analysis of how this phenomenon impacts on the current harmonic distortions in the induction motors operation is also developed through Spearman's correlation matrices. Finally, models that represent the temperature increase of each motor with different voltage unbalance conditions are presented.

The search for more competitive equipment in the global market has led to the implementation of new materials and technologies in the search for greater energy efficiency. This is certainly a guideline followed by the electric motor industry that has introduced new technologies in rotating machines, such as the permanent magnet motor, evolving into increasingly efficient motor classes. However, subjecting these efficient motors under nonideal electric grid power conditions, such as voltage unbalance, can cause these efficient machines to generate additional distortions in the voltage and current waveforms, which in turn not only affect the performance of electric motors themselves but also that of the electrical system in general. This work presents a comparison between energy efficiency gain and the corresponding power quality degradation through a detailed harmonic analysis of the effects of voltage harmonics and voltage unbalance in three 0.75-kW electric motors classes: IE2, IE3, and IE4, The results show that for increasing percentages of a specific harmonic distortion, other harmonics are also increased in the higher efficiency electric motors sample analyzed, and similar responses were also observed for large percentages of voltage unbalance, mainly in the line-start permanent magnet motor class IE4. The results achieved are interesting but rigorously reflect only the tested motor sample and cannot be generalized to all motors, in other power ranges, of the respective motor classes tested. For generalization, exhaustive tests must be accomplished to formulate general conclusions according to the electric motors' classes commercially available.

Global energy systems are undergoing a transition process towards renewable energy and energy efficiency practices. Induction motors play an important role in this energy transformation process since they are widely used as industrial loads, representing more than 53% of global energy consumption. With more countries adopting minimum energy performance standards through more efficient induction motors, comparisons between these new technologies in the presence of electrical disturbances must be systematically evaluated before adopting a substitution policy in the industry. To this end, this work presents a comparative analysis of the impact of harmonic voltages on the performance and temperature rise of electric motors classes IE2, IE3 and IE4 in the same operational conditions in view of future substitutions. The results show that under ideal operating conditions the IE4 class permanent magnet motor has better performance in terms of consumption and temperature, however presenting non-linear characteristics. In the presence of voltage harmonics, this scenario changes completely according to the harmonic content. Finally, aiming to analyze the harmonics influence in the motor temperature rise a statistical analysis by means of Spearman correlation matrices is presented.

This study addresses the problem of determining which non‐linear loads can be considered potential harmonic sources to the voltage harmonic distortions observed in the utility grid voltages. Statistical regression models are used to establish correlations between the simultaneously measured harmonic voltages, in the grid, and harmonic currents, at each non‐linear individual load. First, the R ‐squared statistic is used to decide the goodness of fit of the developed models, giving indication on the relevance of the model. In order to overcome the limitation of the linear regression model based on voltage and current magnitudes measurements only, that imposes a constant behaviour for the background harmonic sources, a non‐parametric regression model is suggested and a comparison between the performances of the two models is carried out. Field data from two real electrical systems, one having a 138 kV substation in which a large industrial load and a 34.5 kV rural long feeder are connected; and the other having four urban 13.8 kV feeders supplying industrial and commercial loads, were used to develop and validate the statistical models used in the application.

Energy losses are a fundamental issue in the electricity distribution sector, being an inevitable consequence of transporting energy from supplying sources to consumers’ installations and are becoming one of the factors to be considered in planning and operation of electrical distribution networks. So, electrical distribution losses must be continuously monitored so that they are kept within acceptable levels to ensure the business profitability as well as the good power quality of supplied energy. In this context, this work introduces a modified methodology for technical losses calculation with the application of the concept of reduced equivalent networks, via definition of an Equivalent Operational Impedance, taking as a starting point the electrical network modeling in the Open Distribution System Simulator (OpenDSS). The losses calculation also considers customer’s energy billing measurement data, measurements of injected energy and power factor at the feeder’s coupling bus at the substation, also considering measurement campaigns to characterize the load consumption profiles for working days, Saturdays and Sundays. The proposed methodology disaggregates energy injections in billed energy, technical and non-technical losses parcels, and presents, as the results have demonstrated, a good precision in the proposed calculation procedures.

This paper presents a procedure to estimate the impacts on voltage harmonic distortion at a point of interest due to multiple nonlinear loads in the electrical network. Despite artificial neural networks (ANN) being a widely used technique for the solution of a large amount and variety of issues in electric power systems, including harmonics modeling, its utilization to establish relationships among the harmonic voltage at a point of interest in the electric grid and the corresponding harmonic currents generated by nonlinear loads was not found in the literature, thus this innovative procedure is considered in this article. A simultaneous measurement campaign must be carried out in all nonlinear loads and at the point of interest for data acquisition to train and test the ANN model. A sensitivity analysis is proposed to establish the percent contribution of load currents on the observed voltage distortion, which constitutes an original definition presented in this paper. Initially, alternative transient program (ATP) simulations are used to calculate harmonic voltages at points of interest in an industrial test system due to nonlinear loads whose harmonic currents are known. The resulting impacts on voltage harmonic distortions obtained by the ATP simulations are taken as reference values to compare with those obtained by using the proposed procedure based on ANN. By comparing ATP results with those obtained by the ANN model, it is observed that the proposed methodology is able to classify correctly the impact degree of nonlinear load currents on voltage harmonic distortions at points of interest, as proposed in this paper.