The reliability of a low-voltage asynchronous electric motor is primarily determined by the reliability of the stator winding insulation. Common reasons for the failure of the insulation system are the unsatisfactory quality of the enameled wires and electrical insulating materials used for imperfection and violation of the technological process of winding and insulating work, and the discrepancy between operating modes. In the vast majority of cases, failures occur due to damage to the inter-turn insulation as the weakest element. This causes the need to study the insulation system resistance to the formation of defects. The results of assessing the stability of the insulation of winding wires to defect formation are obtained, taking into account the features of the operational loads characteristic of frequency-controlled drives with pulse-width modulation of the output voltage and the influence of the inter-turn insulation defectiveness level on its reliability indicators is also studied. The authors have developed the measures to reduce the defectiveness of inter-turn insulation at the manufacturing stage and during operation. This will ensure a minimum level of insulation defects and increase the resource of asynchronous electric motors by reducing the number of failures.

To cool solar panels in hot season, it is necessary to use special cooling devices. The most optimal way of cooling is the use of liquid cooling, realized by means of a pump. This article provides an overview and evaluation of ways to cool solar panels using various devices. The relevance of the research is caused by the need to reduce the temperature of solar panels in order to increase the output power in the hot season. The main aim of the research is to compare and choose the most optimal way to cool solar panels. Methods: comparative analysis, mathematical modeling in the ANSYS environment. Results. Comparative characteristic of TEM, radiators, fans and liquid cooling is given, an example of cooling a solar panel using liquid cooling to spray a liquid flow of 29 l/min is calculated. The panels will cool down from 45 to 35 °C in 4,7 minutes. For one EasySunSolar solar panel with a capacity of 100 W, costing $100, taking into account electrical work, an additional heat sink module will cost about $50.

To cool solar panels in hot season, it is necessary to use special cooling devices. The most optimal way of cooling is the use of liquid cooling, realized by means of a pump. This article provides an overview and evaluation of ways to cool solar panels using various devices. The relevance of the research is caused by the need to reduce the temperature of solar panels in order to increase the output power in the hot season. The main aim of the research is to compare and choose the most optimal way to cool solar panels. Methods: comparative analysis, mathematical modeling in the ANSYS environment. Results. Comparative characteristic of TEM, radiators, fans and liquid cooling is given, an example of cooling a solar panel using liquid cooling to spray a liquid flow of 29 l/min is calculated. The panels will cool down from 45 to 35 °C in 4,7 minutes. For one EasySunSolar solar panel with a capacity of 100 W, costing $100, taking into account electrical work, an additional heat sink module will cost about $50.

Currently, there are practically no automated systems for controlling power flow within the specified limits when the power line is overloaded by active power. Regulation is assigned to the dispatchers of the power system or is carried out by means of emergency automation, which disconnects consumers. Therefore, an urgent task is to expand the arsenal of tools for automatic control of active power flow in overload mode. Relevance. A significant increase in electricity consumers leads to a complication of the electric power system. The workload for dispatching personnel is increasing. Maintaining the smooth operation of the elements of the power system is a very important and responsible task. In modern electric power industry, timely warning and elimination of overloads of network elements are relevant. The study aims are development and research of an intelligent automatic control system for the flow of active power along a power line based on the mathematical apparatus of fuzzy logic. The system is based on the use of the regulating effect of the load. Research methodology. Methods of calculating static load model during their actualization were used. The method of fuzzy sets was used in the construction of an intelligence control system for active power flows in overload condition. The effectiveness was estimated by expert methods. Results. The use of artificial intelligence methods for automatic regulation of transformer voltage under load allows up to 5–7 % reducing the flow of active power in overload mode.

Currently, there are practically no automated systems for controlling power flow within the specified limits when the power line is overloaded by active power. Regulation is assigned to the dispatchers of the power system or is carried out by means of emergency automation, which disconnects consumers. Therefore, an urgent task is to expand the arsenal of tools for automatic control of active power flow in overload mode. Relevance. A significant increase in electricity consumers leads to a complication of the electric power system. The workload for dispatching personnel is increasing. Maintaining the smooth operation of the elements of the power system is a very important and responsible task. In modern electric power industry, timely warning and elimination of overloads of network elements are relevant. The study aims are development and research of an intelligent automatic control system for the flow of active power along a power line based on the mathematical apparatus of fuzzy logic. The system is based on the use of the regulating effect of the load. Research methodology. Methods of calculating static load model during their actualization were used. The method of fuzzy sets was used in the construction of an intelligence control system for active power flows in overload condition. The effectiveness was estimated by expert methods. Results. The use of artificial intelligence methods for automatic regulation of transformer voltage under load allows up to 5–7 % reducing the flow of active power in overload mode.