Processing of Data on Power Consumption in the Management of Energy Resources of the Regional Electrical Complex

The article considers the theoretical justification of the stages of data processing on power consumption in the management of energy resources of the regional electrical complex. The development of modern technologies has made it possible to significantly increase the ability to measure parameters at electric power facilities, which is why it has become possible to accumulate large amounts of data using digital metering devices. Numerous studies of the structure and properties of the measurement data have led to the conclusion that they belong to non-Gaussian, i.e. the central limit theorems and the law of large numbers do not work on such data. Therefore, it is advisable to carry out their qualitative processing using the methods of rank analysis. The article proposes and theoretically substantiates an approach to creating a digital energy efficiency platform based on vector rank analysis in a computational and parametric complex. It will allow processing multidimensional arrays of non-Gaussian data and implementing scientific methods in order to obtain deterministic invariants for the decision-making preparation system. A distinctive feature of the digital energy efficiency platform is a one-parameter digital twin, the basis of which is an OLAP data cube by parameter, which allows long-term storage of arrays of non-Gaussian data of the regional electrical complex for electrical equipment used to generate deterministic invariants on the basis of which decisions are made.