Artificial intelligence

Abstract: The article presents an approach to the formation of a decision support system in the management of energy consumption of production technological systems. Such systems allow the company to detect and respond in a timely manner to the appearance of hidden energy losses, to carry out organizational measures aimed at energy saving and to optimize the timing and scope of repair and restoration work. The approach is based on the modeling of stationary sections of energy consumption, presented in the form of precedents, their accumulation and subsequent analysis in the space of influential technological parameters. In addition to the base of precedents, the system includes software modules for assessment and formation of the profile of hidden energy losses, modules of technical condition, forecast and formation of precedents. The analysis of precedents consists in the selection of similar cases of energy consumption, the formation of efficient energy consumption functions and the calculation of energy losses with its help. Hidden energy losses can be calculated in real time for all technological systems of the enterprise. This allows you to build a profile of energy losses of the enterprise. The advantage of this approach in comparison with the known ones is that it allows to adapt to technological systems with different energy sources. The article emphasizes that the method can work with the energy manager with both linear and nonlinear dependence of energy consumption on process parameters. However, the limitations of this approach are noted. Thus, the determination of latent energy losses and technical condition of the equipment requires the participation of qualified specialists of the enterprise, who must be able to analyze the results and propose measures to eliminate energy losses.

Keywords: monitoring, diagnostics of energy consumption, energy losses, precedent, technological system, energy consumption

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