The paper considers the influence of harmonics on the operating of electrical energy meters in a network with nonlinear loads. It is shown that electronic static meters of active energy are tested in the presence of distortions, and electronic static meters of reactive energy accuracy requirements do not take into account the possible presence of harmonics. It is revealed that the maximum influence on the error in active energy metering is exerted by the number of harmonics taken into account and their amplitude, and the error in reactive energy metering is additionally influenced by the phase angle at the fundamental and harmonic frequencies, which has been confirmed in laboratory conditions. Additionally, experimental studies of the capacitor bank’s influence on reactive energy metering has been carried out in the presence of nonlinear electrical loads. It is shown that when capacitor banks are connected, the error in reactive energy measurement and variation range of the phase shift angle of harmonics significantly increases. The assessment of the computational error of reactive power metering according to various equations were carried out based on the field measurements. If the voltage and current distortion values do not exceed the permissible values, the error can be estimated at, at most, 5–7%.

The article provides an analysis of the existing methods of identifying the consumer's contribution to voltage distortion at a point of common coupling. The considered methods do not allow correctly and fairly determining the source of harmonic distortions, or they have limited application and difficulties in implementation. The paper proposes new methods for determining the source of high harmonics. The developed methods and techniques are based on the analysis of the grid operation modes with two connected consumers using compensating devices, such as reactive power compensation devices and passive harmonic filters. It is shown that the most promising method is the application of harmonic filters, which allows determining the share of the consumer's contribution to the voltage distortion. The present research is carried out using a computer simulation of the existing electrical grid, to which consumers with nonlinear electric load are connected. These methods can be implemented to assess the power quality and the shareholding of different consumers connected at the point of common coupling. Furthermore, such methods appear to be feasible, as almost every enterprise currently has such facilities in operation.

The authors proposed a scheme of autonomous power supply for oil leakage detection systems in pipelines by applying the photovoltaic modules and thermoelectric generators as a power source. Laboratory experimental studies were carried out, the operating energy characteristics of the complex were obtained. A sufficient number of generating units has been determined for uninterrupted power supply to the data collection point of the oil leakage detection system.

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<p>The dependability of power electronics systems, such as three-phase inverters, is critical in a variety of applications. Different types of failures that occur in an inverter circuit might affect system operation and raise the entire cost of the manufacturing process. As a result, detecting and identifying inverter problems for such devices is critical in industry. This study presents the short-time Fourier transform (STFT) for fault classification and identification in three-phase type, voltage source inverter (VSI) switches. TFR represents the signal analysis of STFT, which includes total harmonic distortion, instantaneous RMS current, RMS fundamental current, total non harmonic distortion, total waveform distortion and average current. The features of the faults are used with a rule-based classifier based on the signal parameters to categorise and detect the switch faults. The suggested method's performance is evaluated using 60 signals containing short and open circuit faults with varying characteristics for each switch in VSI. The classification results demonstrate the proposed technique is good to be implemented for VSI switches faults classification, with an accuracy classification rate of 98.3 percent.</p>