System model of intelligent power supply management of transport infrastructure

The article considers the problem of formalizing the structure of intelligent transport infrastructure power supply management systems at the design stage. It is shown that the traditional approach to designing transport power supply systems, based on deterministic calculations of expected loads for a fixed set of operational scenarios, is methodologically limited, since it does not take into account the dynamic nature of the interaction of infrastructure elements, the probabilistic nature of load and generation fluctuations, as well as the need for operational adaptation of management decisions to changing operating conditions. The feasibility of using a systems approach to build a formalized model of an intelligent system that integrates the sensory, analytical, management and executive levels is substantiated. A generalized model of the system is developed in the form of a tuple that describes input parameters, internal states, output control decisions and transition and decision-making functions. A multi-criteria objective function for optimizing design solutions is proposed, which reconciles the economic, reliability and environmental components, as well as the reliability index of the system with the redundancy of power supply sources. The practical value of the proposed model for projects to restore damaged transport infrastructure in the conditions of post-war development is shown, in particular for substantiating decisions on capacity redundancy and integration of distributed and renewable energy sources. The limitations of the model associated with the quality of input data and the need to calibrate the weight coefficients of the objective function to specific project conditions are outlined, and the prospects for further research on automated tuning of model parameters based on accumulated operational data are also identified. The proposed approach can be used as a methodological basis for designing intelligent transport infrastructure power supply systems under conditions of increased uncertainty.