Application of Z-Number Theory to Uncertainty Modeling in Energy Consumption Systems

Abstract

The article examines the application of Z-number theory in modeling uncertainty in energy consumption systems. It is shown that since modern energy systems are dynamic and multifactorial in nature, uncertainty arises from various sources in the process of forecasting and managing consumption. Although traditional probabilistic-statistical models take into account the random nature of information, they remain limited in providing a complete mathematical description of information with different levels of imprecision and reliability. The Z-number approach allows for the formal modeling of double uncertainty by combining two main characteristics of information within the same model. The study explains the mechanism of modeling energy consumption based on Z-numbers and shows its application possibilities in the fields of peak load forecasting, energy distribution optimization, and risk assessment in smart grid systems. Consequently, the application of Z-number theory creates a scientific and methodological basis for a more realistic and justified decision-making process in energy systems, a more accurate assessment of risks, and an increase in system stability.