Modern energy strategies aimed at the development of energy industry presuppose a significant change in the structure of process of formation, transmission, consumption of electrical energy and increasing energy efficiency by introducing modern technologies at all stages. The growth of capacities of industrial enterprises in the conditions of wholesale market of electrical energy and capacity in the modern energy system determines the need for development technologies of predictive control of power consumption process of these enterprises. The introduction of such technologies at the control rooms of the operational management of enterprises will allow to reduce the number of human errors, the number of emergency stops of technological process, increase the reliability of power system mode, rationally manage the process of power consumption of enterprises. In this regard, forecasting the load demand and consumption is an important stage in the functioning and planning of modern power systems. An accurate, correctly compiled forecast is the key to effective management of energy consumption process and reliable operation of the enterprise. Forecasting errors lead to imbalanced supply-demand, which negatively affects operating costs, reliability and efficiency.
The article reveals relevance of the problem of unbalance of line voltages in closed electrical networks with distributed generation as a source of electromagnetic interference, in particular, the problem of electromagnetic compatibility of coastal and ship technical equipment. There is presented mathematical description of the process of occurrence of conductive low-frequency EMF by the voltage unbalance coefficient in the reverse sequence and an algorithm for finding it; using the equations, parameters of this coefficient are described, such as mathematical expectation, standard deviation, probability of occurrence for the billing period, as a result, a computer program has been developed to calculate these parameters; a method for processing the obtained data of power quality indicators according to the found coefficient has been developed; an algorithm for balancing voltages in an electrical network based on finding the most optimal power supply scheme for end consumers (certificate of state registration of an electronic resource No. 23664).
Development of modern high-speed technologies for thermal spraying proves that deposition of high-quality dense coatings requires velocity of sprayed particles to be 600 m/s and above. Plasma spraying is the most versatile and highly productive deposition method of various functional coatings without any limitations on the melting points of the sprayed materials. Present work describes a DC plasma torch designed for operation in a supersonic mode. The supersonic plasma torch features de Laval nozzle, utilization of air as a plasma-forming gas, and annular injection unit for delivery of the powder to the plasma jet. The comparison of NiCr and NiAl coatings deposited both in subsonic and supersonic modes are presented. Methods for further increasing the sprayed particles’velocity and the requirements for their heating temperature are proposed.
The characteristics of coatings designed to protect against cavitation and waterjet wear, obtained by supersonic atmospheric plasma spraying using air as a plasma-forming gas, are studied. The following powder materials were selected for coating: WC/10Co4Cr; Ni-Cr-B-Si-C; Ni-Al; Ni-Ti; bronze. Metallographic studies of the structures of specimens with applied coatings and measurements of their microhardness were carried out. Due to the fact that the tests of materials for hydroabrasive wear are not standardized, studies were carried out on the resistance of coatings to dry abrasive wear according to the ASTM G65-04 standard and to dry reciprocating friction according to the ASTM G133 standard. The conducted studies of the structures of the sprayed coatings suggest that the use of supersonic deposition modes guarantees the production of high-density coatings with a porosity of less than 1 %.
It is important to note that the generated power of renewable sources depends on the natural conditions at a particular geographic point, the level of wind flow speeds and solar radiation. The patterns characterizing these parameters depend on the time of year, locality and are purely probabilistic in nature. Taking into account the above-mentioned conditions for the effective implementation of “green” objects in the power supply system, the purpose of this work is to build forecasting models that are more likely to be able to determine what part of the load can be covered by the power supply system based on wind power and solar installations. This purpose was achieved by constructing and training artificial neural networks with data on the speed of wind flow and solar radiation obtained from real renewable energy facilities. The most significant result is the identification of the necessary forecasting horizon, taking into account the preservation of a relatively good quality of metrics, as well as understanding what additional data is required to improve this quality. The significance of the results obtained lies in the fact that they make it possible to determine what reserve capacity is required to be included in the project.
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