Prediction and analysis of power consumption and power loss at industrial facilities

Abstract

THE PURPOSE. Conduct a study to improve the reliability of forecasting the magnitude of power consumption and power losses at an industrial enterprise.METHODS. Methods are used to determine and predict the parameters of consumption and losses of electricity at industrial facilities.RESULTS. To clarify the magnitude of electricity losses, it is proposed to use coefficients that take into account the type of load curves and show the ratio of the values of the sum of the squares of currents (powers) of the variable load curve and the values of the sum of average currents (powers), that is. the ratio of power losses during load operation according to variable and uniform schedules (Kgraph), as well as a coefficient that takes into account the topology of the circuit (Ktop). The study of radial and main circuits of networks was carried out and the losses of electricity were determined using the proposed coefficients. The values of equivalent resistances of shop circuits of networks of various topologies are calculated. The operational data of the section of the workshop network are given. It was revealed that with a constant technological process, an increase in the equivalent resistance of the network circuit is due to an increase in the resistance of the contacts of switching devices installed on the lines. The value of the estimated supply of electricity was determined using the parameter of the average value of the equivalent resistance. At the same time, the error in calculating the estimated supply in relation to the actual annual supply of electricity amounted to 2,63%. According to the retrospective values of the average equivalent resistance of the circuit, it is possible to determine the predicted value of this parameter using the average value of the coefficient of change in the equivalent resistance. These characteristics of the scheme are recommended to be used in the assessment and forecasting of losses and the estimated supply of electricity, which will increase the reliability of the predicted parameters for industrial facilities.