Dynamic Fractal Cluster Model of Informational Space Technological Process of Power Station

The paper analyzes factors affecting the reliability of informational signals, which may result in distortions in the data regarding emergency indicators of technological parameters in power equipment. We suggest utilizing the fractal-cluster theory framework to describe random informational signals within the informational space, which deviate from standard process parameter characteristics in power station technological processes. We identify fluctuations in the volume of informational three-dimensional phase space, which are characterized by the informational fractal dimension in decimal form. This observation pertains to random information signals with incidental features and demonstrates their correlation with changes in information quality within the informational space. During our research, we defined the analytical expressions facilitating the connection between the enhancement of informational quality, with consideration to deviations from standard process parameters, and variations in the informational dimension of random fractal signals across space coordinates and real-time. Our efforts aim to enhance the reliability of information management systems, software, and hardware in automated process control units during emergency operations of electricity equipment. Such process involves pinpointing reliable information regarding false positives and failures in detecting process parameter deviations. This can be done by tracking changes in electro-value process parameter characteristics in relation to alterations in random signal information within the volume of information space managed by information management systems, software, and hardware in automated process control units, utilizing fractal-cluster theory principles.