Інтелектуальне прогнозувальне керування та реконфігурація мережі в реальному часі для мінімізації втрат енергії в мікромережах

The increasing deployment of distributed energy resources, renewable generation technologies, and energy storage systems has transformed Microgrids into highly dynamic and complex energy systems. Under such conditions, traditional network control approaches based on static operating assumptions are often unable to respond effectively to rapid changes in load demand, renewable power generation, and network operating conditions. This paper proposes an intelligent predictive control framework combined with real-time network reconfiguration for minimizing energy losses in Microgrids. The developed approach integrates short-term forecasting of load demand and distributed generation with adaptive decision-making mechanisms capable of continuously adjusting network topology according to anticipated operating conditions. A predictive control model is developed to estimate future system states and evaluate potential reconfiguration actions before their implementation. The proposed framework incorporates real-time monitoring, state estimation, forecasting algorithms, and optimization procedures to determine energy-efficient operating strategies while satisfying technical and operational constraints. The reconfiguration process considers network losses, voltage regulation requirements, feeder loading conditions, and distributed energy resource availability. Simulation studies demonstrate that predictive control enables proactive network management and provides improved loss reduction compared with conventional reactive control strategies. The proposed methodology contributes to the development of intelligent Microgrid energy management systems capable of enhancing operational efficiency, flexibility, and reliability in modern distributed power networks.