INVESTIGATION AND IMPLEMENTATION OF THE FRACTAL PROPERTIES OF ELECTRIC LOAD ON CIVILIAN OBJECTS IN ORDER TO EFFICIENTLY PREDICT AND CONTROL ELECTRICAL CONSUMPTIONT

We have investigated the process of constructing the charts of electrical load, as well as electricity consumption, of many-storied apartment houses in a city's neighborhood, taking into consideration the fractal structure and the existence of a long-term dependence, inherent to self-affine stochastic processes. The results from studying daily, weekly, monthly, yearly charts have shown the presence of fractal properties and the existence of short-term and long-term memory. This makes it possible, in order to efficiently predict and control power consumption, to apply a fractal analysis, which establishes the dependence of future values on retrospective information. Feature of the current study is determining a critical value for the Hurst exponent, approaching which leads to that the system loses stability and enters an unstable state under which the parameters are changing rapidly. The Hurst exponent can be transformed into fractal dimensionality, which is a measure for the complexity of a load chart. In the theory of fractal sets and fractal geometry, of significant importance are the self-similar and fractal sets. By using the specified properties of the fractal, this study has proven the existence of a fractal principle in the formation of the dynamics of electrical load on civilian targets using the example of power consumption by many-storied apartment houses within a city's neighborhood. The calculation of the Hurst exponent has made it possible to determine that the series is persistent and suitable for adequate prediction and efficient energy consumption management. The relevance of the current research is predetermined by the application of fractal analysis to electricity consumption pattern particularly by civilian objects, since the scientific literature analyzes and predicts the processes that form electric load structure on energy systems, at industrial enterprise